Spaces:
Runtime error
Runtime error
Upload folder using huggingface_hub
Browse filesThis view is limited to 50 files because it contains too many changes.
See raw diff
- .gitattributes +3 -0
- VBench/.gitignore +173 -0
- VBench/LICENSE +201 -0
- VBench/MANIFEST.in +5 -0
- VBench/README-pypi.md +74 -0
- VBench/README.md +192 -0
- VBench/asset/fig_teaser_new.jpg +3 -0
- VBench/asset/radar-close.jpg +3 -0
- VBench/asset/radar-open.jpg +3 -0
- VBench/asset/vbench_logo_short.jpg +0 -0
- VBench/bin/evaluate +70 -0
- VBench/dimension_to_folder.json +18 -0
- VBench/evaluate.py +85 -0
- VBench/evaluate.sh +30 -0
- VBench/evaluation_results/README.md +2 -0
- VBench/pretrained/README.md +3 -0
- VBench/pretrained/aesthetic_model/model_path.txt +1 -0
- VBench/pretrained/amt_model/AMT-S.yaml +63 -0
- VBench/pretrained/amt_model/download.sh +1 -0
- VBench/pretrained/caption_model/model_path.txt +1 -0
- VBench/pretrained/clip_model/model_path.txt +2 -0
- VBench/pretrained/grit_model/model_path.txt +1 -0
- VBench/pretrained/pyiqa_model/model_path.txt +1 -0
- VBench/pretrained/raft_model/download.sh +5 -0
- VBench/pretrained/umt_model/kinetics_400_categroies.txt +400 -0
- VBench/pretrained/umt_model/model_path.txt +1 -0
- VBench/pretrained/viclip_model/model_path.txt +1 -0
- VBench/prompts/README.md +95 -0
- VBench/prompts/all_category.txt +800 -0
- VBench/prompts/all_dimension.txt +946 -0
- VBench/prompts/metadata/appearance_style.json +362 -0
- VBench/prompts/metadata/color.json +342 -0
- VBench/prompts/metadata/multiple_objects.json +330 -0
- VBench/prompts/metadata/object_class.json +318 -0
- VBench/prompts/metadata/spatial_relationship.json +506 -0
- VBench/prompts/prompts_per_category/animal.txt +100 -0
- VBench/prompts/prompts_per_category/architecture.txt +100 -0
- VBench/prompts/prompts_per_category/food.txt +100 -0
- VBench/prompts/prompts_per_category/human.txt +100 -0
- VBench/prompts/prompts_per_category/lifestyle.txt +100 -0
- VBench/prompts/prompts_per_category/plant.txt +100 -0
- VBench/prompts/prompts_per_category/scenery.txt +100 -0
- VBench/prompts/prompts_per_category/vehicles.txt +100 -0
- VBench/prompts/prompts_per_dimension/appearance_style.txt +90 -0
- VBench/prompts/prompts_per_dimension/color.txt +85 -0
- VBench/prompts/prompts_per_dimension/human_action.txt +100 -0
- VBench/prompts/prompts_per_dimension/multiple_objects.txt +82 -0
- VBench/prompts/prompts_per_dimension/object_class.txt +79 -0
- VBench/prompts/prompts_per_dimension/overall_consistency.txt +93 -0
- VBench/prompts/prompts_per_dimension/scene.txt +86 -0
.gitattributes
CHANGED
@@ -130,3 +130,6 @@ ECCV2022-RIFE-main/demo/I0_slomo_clipped.gif filter=lfs diff=lfs merge=lfs -text
|
|
130 |
uvq/models/compressionnet_baseline/variables/variables.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text
|
131 |
uvq/models/contentnet_baseline/variables/variables.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text
|
132 |
uvq/models/distortionnet_baseline/variables/variables.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
|
|
130 |
uvq/models/compressionnet_baseline/variables/variables.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text
|
131 |
uvq/models/contentnet_baseline/variables/variables.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text
|
132 |
uvq/models/distortionnet_baseline/variables/variables.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text
|
133 |
+
VBench/asset/fig_teaser_new.jpg filter=lfs diff=lfs merge=lfs -text
|
134 |
+
VBench/asset/radar-close.jpg filter=lfs diff=lfs merge=lfs -text
|
135 |
+
VBench/asset/radar-open.jpg filter=lfs diff=lfs merge=lfs -text
|
VBench/.gitignore
ADDED
@@ -0,0 +1,173 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# Byte-compiled / optimized / DLL files
|
2 |
+
__pycache__/
|
3 |
+
*.py[cod]
|
4 |
+
*$py.class
|
5 |
+
|
6 |
+
# C extensions
|
7 |
+
*.so
|
8 |
+
|
9 |
+
# Distribution / packaging
|
10 |
+
.Python
|
11 |
+
build/
|
12 |
+
develop-eggs/
|
13 |
+
dist/
|
14 |
+
downloads/
|
15 |
+
eggs/
|
16 |
+
.eggs/
|
17 |
+
lib/
|
18 |
+
lib64/
|
19 |
+
parts/
|
20 |
+
sdist/
|
21 |
+
var/
|
22 |
+
wheels/
|
23 |
+
share/python-wheels/
|
24 |
+
*.egg-info/
|
25 |
+
.installed.cfg
|
26 |
+
*.egg
|
27 |
+
MANIFEST
|
28 |
+
|
29 |
+
# PyInstaller
|
30 |
+
# Usually these files are written by a python script from a template
|
31 |
+
# before PyInstaller builds the exe, so as to inject date/other infos into it.
|
32 |
+
*.manifest
|
33 |
+
*.spec
|
34 |
+
|
35 |
+
# Installer logs
|
36 |
+
pip-log.txt
|
37 |
+
pip-delete-this-directory.txt
|
38 |
+
|
39 |
+
# Unit test / coverage reports
|
40 |
+
htmlcov/
|
41 |
+
.tox/
|
42 |
+
.nox/
|
43 |
+
.coverage
|
44 |
+
.coverage.*
|
45 |
+
.cache
|
46 |
+
nosetests.xml
|
47 |
+
coverage.xml
|
48 |
+
*.cover
|
49 |
+
*.py,cover
|
50 |
+
.hypothesis/
|
51 |
+
.pytest_cache/
|
52 |
+
cover/
|
53 |
+
|
54 |
+
# Translations
|
55 |
+
*.mo
|
56 |
+
*.pot
|
57 |
+
|
58 |
+
# Django stuff:
|
59 |
+
*.log
|
60 |
+
local_settings.py
|
61 |
+
db.sqlite3
|
62 |
+
db.sqlite3-journal
|
63 |
+
|
64 |
+
# Flask stuff:
|
65 |
+
instance/
|
66 |
+
.webassets-cache
|
67 |
+
|
68 |
+
# Scrapy stuff:
|
69 |
+
.scrapy
|
70 |
+
|
71 |
+
# Sphinx documentation
|
72 |
+
docs/_build/
|
73 |
+
|
74 |
+
# PyBuilder
|
75 |
+
.pybuilder/
|
76 |
+
target/
|
77 |
+
|
78 |
+
# Jupyter Notebook
|
79 |
+
.ipynb_checkpoints
|
80 |
+
|
81 |
+
# IPython
|
82 |
+
profile_default/
|
83 |
+
ipython_config.py
|
84 |
+
|
85 |
+
# pyenv
|
86 |
+
# For a library or package, you might want to ignore these files since the code is
|
87 |
+
# intended to run in multiple environments; otherwise, check them in:
|
88 |
+
# .python-version
|
89 |
+
|
90 |
+
# pipenv
|
91 |
+
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
|
92 |
+
# However, in case of collaboration, if having platform-specific dependencies or dependencies
|
93 |
+
# having no cross-platform support, pipenv may install dependencies that don't work, or not
|
94 |
+
# install all needed dependencies.
|
95 |
+
#Pipfile.lock
|
96 |
+
|
97 |
+
# poetry
|
98 |
+
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
|
99 |
+
# This is especially recommended for binary packages to ensure reproducibility, and is more
|
100 |
+
# commonly ignored for libraries.
|
101 |
+
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
|
102 |
+
#poetry.lock
|
103 |
+
|
104 |
+
# pdm
|
105 |
+
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
|
106 |
+
#pdm.lock
|
107 |
+
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
|
108 |
+
# in version control.
|
109 |
+
# https://pdm.fming.dev/#use-with-ide
|
110 |
+
.pdm.toml
|
111 |
+
|
112 |
+
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
|
113 |
+
__pypackages__/
|
114 |
+
|
115 |
+
# Celery stuff
|
116 |
+
celerybeat-schedule
|
117 |
+
celerybeat.pid
|
118 |
+
|
119 |
+
# SageMath parsed files
|
120 |
+
*.sage.py
|
121 |
+
|
122 |
+
# Environments
|
123 |
+
.env
|
124 |
+
.venv
|
125 |
+
env/
|
126 |
+
venv/
|
127 |
+
ENV/
|
128 |
+
env.bak/
|
129 |
+
venv.bak/
|
130 |
+
|
131 |
+
# Spyder project settings
|
132 |
+
.spyderproject
|
133 |
+
.spyproject
|
134 |
+
|
135 |
+
# Rope project settings
|
136 |
+
.ropeproject
|
137 |
+
|
138 |
+
# mkdocs documentation
|
139 |
+
/site
|
140 |
+
|
141 |
+
# mypy
|
142 |
+
.mypy_cache/
|
143 |
+
.dmypy.json
|
144 |
+
dmypy.json
|
145 |
+
|
146 |
+
# Pyre type checker
|
147 |
+
.pyre/
|
148 |
+
|
149 |
+
# pytype static type analyzer
|
150 |
+
.pytype/
|
151 |
+
|
152 |
+
# Cython debug symbols
|
153 |
+
cython_debug/
|
154 |
+
|
155 |
+
# pytorch checkpoints
|
156 |
+
*.pt
|
157 |
+
*.pth
|
158 |
+
*.ckpt
|
159 |
+
*.pkl
|
160 |
+
|
161 |
+
# sampled videos
|
162 |
+
*.mp4
|
163 |
+
*.avi
|
164 |
+
*.gif
|
165 |
+
|
166 |
+
# development logs
|
167 |
+
private_dev/*
|
168 |
+
evaluation_results/*.json
|
169 |
+
vbench/third_party/ViCLIP/bpe_simple_vocab_16e6.txt.gz
|
170 |
+
trash*
|
171 |
+
|
172 |
+
# image suite
|
173 |
+
vbench2_beta_i2v/data
|
VBench/LICENSE
ADDED
@@ -0,0 +1,201 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
Apache License
|
2 |
+
Version 2.0, January 2004
|
3 |
+
http://www.apache.org/licenses/
|
4 |
+
|
5 |
+
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
|
6 |
+
|
7 |
+
1. Definitions.
|
8 |
+
|
9 |
+
"License" shall mean the terms and conditions for use, reproduction,
|
10 |
+
and distribution as defined by Sections 1 through 9 of this document.
|
11 |
+
|
12 |
+
"Licensor" shall mean the copyright owner or entity authorized by
|
13 |
+
the copyright owner that is granting the License.
|
14 |
+
|
15 |
+
"Legal Entity" shall mean the union of the acting entity and all
|
16 |
+
other entities that control, are controlled by, or are under common
|
17 |
+
control with that entity. For the purposes of this definition,
|
18 |
+
"control" means (i) the power, direct or indirect, to cause the
|
19 |
+
direction or management of such entity, whether by contract or
|
20 |
+
otherwise, or (ii) ownership of fifty percent (50%) or more of the
|
21 |
+
outstanding shares, or (iii) beneficial ownership of such entity.
|
22 |
+
|
23 |
+
"You" (or "Your") shall mean an individual or Legal Entity
|
24 |
+
exercising permissions granted by this License.
|
25 |
+
|
26 |
+
"Source" form shall mean the preferred form for making modifications,
|
27 |
+
including but not limited to software source code, documentation
|
28 |
+
source, and configuration files.
|
29 |
+
|
30 |
+
"Object" form shall mean any form resulting from mechanical
|
31 |
+
transformation or translation of a Source form, including but
|
32 |
+
not limited to compiled object code, generated documentation,
|
33 |
+
and conversions to other media types.
|
34 |
+
|
35 |
+
"Work" shall mean the work of authorship, whether in Source or
|
36 |
+
Object form, made available under the License, as indicated by a
|
37 |
+
copyright notice that is included in or attached to the work
|
38 |
+
(an example is provided in the Appendix below).
|
39 |
+
|
40 |
+
"Derivative Works" shall mean any work, whether in Source or Object
|
41 |
+
form, that is based on (or derived from) the Work and for which the
|
42 |
+
editorial revisions, annotations, elaborations, or other modifications
|
43 |
+
represent, as a whole, an original work of authorship. For the purposes
|
44 |
+
of this License, Derivative Works shall not include works that remain
|
45 |
+
separable from, or merely link (or bind by name) to the interfaces of,
|
46 |
+
the Work and Derivative Works thereof.
|
47 |
+
|
48 |
+
"Contribution" shall mean any work of authorship, including
|
49 |
+
the original version of the Work and any modifications or additions
|
50 |
+
to that Work or Derivative Works thereof, that is intentionally
|
51 |
+
submitted to Licensor for inclusion in the Work by the copyright owner
|
52 |
+
or by an individual or Legal Entity authorized to submit on behalf of
|
53 |
+
the copyright owner. For the purposes of this definition, "submitted"
|
54 |
+
means any form of electronic, verbal, or written communication sent
|
55 |
+
to the Licensor or its representatives, including but not limited to
|
56 |
+
communication on electronic mailing lists, source code control systems,
|
57 |
+
and issue tracking systems that are managed by, or on behalf of, the
|
58 |
+
Licensor for the purpose of discussing and improving the Work, but
|
59 |
+
excluding communication that is conspicuously marked or otherwise
|
60 |
+
designated in writing by the copyright owner as "Not a Contribution."
|
61 |
+
|
62 |
+
"Contributor" shall mean Licensor and any individual or Legal Entity
|
63 |
+
on behalf of whom a Contribution has been received by Licensor and
|
64 |
+
subsequently incorporated within the Work.
|
65 |
+
|
66 |
+
2. Grant of Copyright License. Subject to the terms and conditions of
|
67 |
+
this License, each Contributor hereby grants to You a perpetual,
|
68 |
+
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
|
69 |
+
copyright license to reproduce, prepare Derivative Works of,
|
70 |
+
publicly display, publicly perform, sublicense, and distribute the
|
71 |
+
Work and such Derivative Works in Source or Object form.
|
72 |
+
|
73 |
+
3. Grant of Patent License. Subject to the terms and conditions of
|
74 |
+
this License, each Contributor hereby grants to You a perpetual,
|
75 |
+
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
|
76 |
+
(except as stated in this section) patent license to make, have made,
|
77 |
+
use, offer to sell, sell, import, and otherwise transfer the Work,
|
78 |
+
where such license applies only to those patent claims licensable
|
79 |
+
by such Contributor that are necessarily infringed by their
|
80 |
+
Contribution(s) alone or by combination of their Contribution(s)
|
81 |
+
with the Work to which such Contribution(s) was submitted. If You
|
82 |
+
institute patent litigation against any entity (including a
|
83 |
+
cross-claim or counterclaim in a lawsuit) alleging that the Work
|
84 |
+
or a Contribution incorporated within the Work constitutes direct
|
85 |
+
or contributory patent infringement, then any patent licenses
|
86 |
+
granted to You under this License for that Work shall terminate
|
87 |
+
as of the date such litigation is filed.
|
88 |
+
|
89 |
+
4. Redistribution. You may reproduce and distribute copies of the
|
90 |
+
Work or Derivative Works thereof in any medium, with or without
|
91 |
+
modifications, and in Source or Object form, provided that You
|
92 |
+
meet the following conditions:
|
93 |
+
|
94 |
+
(a) You must give any other recipients of the Work or
|
95 |
+
Derivative Works a copy of this License; and
|
96 |
+
|
97 |
+
(b) You must cause any modified files to carry prominent notices
|
98 |
+
stating that You changed the files; and
|
99 |
+
|
100 |
+
(c) You must retain, in the Source form of any Derivative Works
|
101 |
+
that You distribute, all copyright, patent, trademark, and
|
102 |
+
attribution notices from the Source form of the Work,
|
103 |
+
excluding those notices that do not pertain to any part of
|
104 |
+
the Derivative Works; and
|
105 |
+
|
106 |
+
(d) If the Work includes a "NOTICE" text file as part of its
|
107 |
+
distribution, then any Derivative Works that You distribute must
|
108 |
+
include a readable copy of the attribution notices contained
|
109 |
+
within such NOTICE file, excluding those notices that do not
|
110 |
+
pertain to any part of the Derivative Works, in at least one
|
111 |
+
of the following places: within a NOTICE text file distributed
|
112 |
+
as part of the Derivative Works; within the Source form or
|
113 |
+
documentation, if provided along with the Derivative Works; or,
|
114 |
+
within a display generated by the Derivative Works, if and
|
115 |
+
wherever such third-party notices normally appear. The contents
|
116 |
+
of the NOTICE file are for informational purposes only and
|
117 |
+
do not modify the License. You may add Your own attribution
|
118 |
+
notices within Derivative Works that You distribute, alongside
|
119 |
+
or as an addendum to the NOTICE text from the Work, provided
|
120 |
+
that such additional attribution notices cannot be construed
|
121 |
+
as modifying the License.
|
122 |
+
|
123 |
+
You may add Your own copyright statement to Your modifications and
|
124 |
+
may provide additional or different license terms and conditions
|
125 |
+
for use, reproduction, or distribution of Your modifications, or
|
126 |
+
for any such Derivative Works as a whole, provided Your use,
|
127 |
+
reproduction, and distribution of the Work otherwise complies with
|
128 |
+
the conditions stated in this License.
|
129 |
+
|
130 |
+
5. Submission of Contributions. Unless You explicitly state otherwise,
|
131 |
+
any Contribution intentionally submitted for inclusion in the Work
|
132 |
+
by You to the Licensor shall be under the terms and conditions of
|
133 |
+
this License, without any additional terms or conditions.
|
134 |
+
Notwithstanding the above, nothing herein shall supersede or modify
|
135 |
+
the terms of any separate license agreement you may have executed
|
136 |
+
with Licensor regarding such Contributions.
|
137 |
+
|
138 |
+
6. Trademarks. This License does not grant permission to use the trade
|
139 |
+
names, trademarks, service marks, or product names of the Licensor,
|
140 |
+
except as required for reasonable and customary use in describing the
|
141 |
+
origin of the Work and reproducing the content of the NOTICE file.
|
142 |
+
|
143 |
+
7. Disclaimer of Warranty. Unless required by applicable law or
|
144 |
+
agreed to in writing, Licensor provides the Work (and each
|
145 |
+
Contributor provides its Contributions) on an "AS IS" BASIS,
|
146 |
+
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
|
147 |
+
implied, including, without limitation, any warranties or conditions
|
148 |
+
of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
|
149 |
+
PARTICULAR PURPOSE. You are solely responsible for determining the
|
150 |
+
appropriateness of using or redistributing the Work and assume any
|
151 |
+
risks associated with Your exercise of permissions under this License.
|
152 |
+
|
153 |
+
8. Limitation of Liability. In no event and under no legal theory,
|
154 |
+
whether in tort (including negligence), contract, or otherwise,
|
155 |
+
unless required by applicable law (such as deliberate and grossly
|
156 |
+
negligent acts) or agreed to in writing, shall any Contributor be
|
157 |
+
liable to You for damages, including any direct, indirect, special,
|
158 |
+
incidental, or consequential damages of any character arising as a
|
159 |
+
result of this License or out of the use or inability to use the
|
160 |
+
Work (including but not limited to damages for loss of goodwill,
|
161 |
+
work stoppage, computer failure or malfunction, or any and all
|
162 |
+
other commercial damages or losses), even if such Contributor
|
163 |
+
has been advised of the possibility of such damages.
|
164 |
+
|
165 |
+
9. Accepting Warranty or Additional Liability. While redistributing
|
166 |
+
the Work or Derivative Works thereof, You may choose to offer,
|
167 |
+
and charge a fee for, acceptance of support, warranty, indemnity,
|
168 |
+
or other liability obligations and/or rights consistent with this
|
169 |
+
License. However, in accepting such obligations, You may act only
|
170 |
+
on Your own behalf and on Your sole responsibility, not on behalf
|
171 |
+
of any other Contributor, and only if You agree to indemnify,
|
172 |
+
defend, and hold each Contributor harmless for any liability
|
173 |
+
incurred by, or claims asserted against, such Contributor by reason
|
174 |
+
of your accepting any such warranty or additional liability.
|
175 |
+
|
176 |
+
END OF TERMS AND CONDITIONS
|
177 |
+
|
178 |
+
APPENDIX: How to apply the Apache License to your work.
|
179 |
+
|
180 |
+
To apply the Apache License to your work, attach the following
|
181 |
+
boilerplate notice, with the fields enclosed by brackets "[]"
|
182 |
+
replaced with your own identifying information. (Don't include
|
183 |
+
the brackets!) The text should be enclosed in the appropriate
|
184 |
+
comment syntax for the file format. We also recommend that a
|
185 |
+
file or class name and description of purpose be included on the
|
186 |
+
same "printed page" as the copyright notice for easier
|
187 |
+
identification within third-party archives.
|
188 |
+
|
189 |
+
Copyright [yyyy] [name of copyright owner]
|
190 |
+
|
191 |
+
Licensed under the Apache License, Version 2.0 (the "License");
|
192 |
+
you may not use this file except in compliance with the License.
|
193 |
+
You may obtain a copy of the License at
|
194 |
+
|
195 |
+
http://www.apache.org/licenses/LICENSE-2.0
|
196 |
+
|
197 |
+
Unless required by applicable law or agreed to in writing, software
|
198 |
+
distributed under the License is distributed on an "AS IS" BASIS,
|
199 |
+
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
200 |
+
See the License for the specific language governing permissions and
|
201 |
+
limitations under the License.
|
VBench/MANIFEST.in
ADDED
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
include version.txt
|
2 |
+
include requirements.txt
|
3 |
+
recursive-include vbench/third_party *.yaml
|
4 |
+
recursive-include vbench *.json
|
5 |
+
recursive-include vbench/third_party *.txt
|
VBench/README-pypi.md
ADDED
@@ -0,0 +1,74 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
![vbench_logo](https://raw.githubusercontent.com/Vchitect/VBench/master/asset/vbench_logo_short.jpg)
|
2 |
+
|
3 |
+
**VBench** is a comprehensive benchmark suite for video generative models. You can use **VBench** to evaluate video generation models from 16 different ability aspects.
|
4 |
+
|
5 |
+
This project is the PyPI implementation of the following research:
|
6 |
+
> **VBench: Comprehensive Benchmark Suite for Video Generative Models**<br>
|
7 |
+
> [Ziqi Huang](https://ziqihuangg.github.io/)<sup>∗</sup>, [Yinan He](https://github.com/yinanhe)<sup>∗</sup>, [Jiashuo Yu](https://scholar.google.com/citations?user=iH0Aq0YAAAAJ&hl=zh-CN)<sup>∗</sup>, [Fan Zhang](https://github.com/zhangfan-p)<sup>∗</sup>, [Chenyang Si](https://chenyangsi.top/), [Yuming Jiang](https://yumingj.github.io/), [Yuanhan Zhang](https://zhangyuanhan-ai.github.io/), [Tianxing Wu](https://tianxingwu.github.io/), [Qingyang Jin](https://github.com/Vchitect/VBench), [Nattapol Chanpaisit](https://nattapolchan.github.io/me), [Yaohui Wang](https://wyhsirius.github.io/), [Xinyuan Chen](https://scholar.google.com/citations?user=3fWSC8YAAAAJ), [Limin Wang](https://wanglimin.github.io), [Dahua Lin](http://dahua.site/)<sup>+</sup>, [Yu Qiao](http://mmlab.siat.ac.cn/yuqiao/index.html)<sup>+</sup>, [Ziwei Liu](https://liuziwei7.github.io/)<sup>+</sup><br>
|
8 |
+
|
9 |
+
[![Paper](https://img.shields.io/badge/cs.CV-Paper-b31b1b?logo=arxiv&logoColor=red)](https://arxiv.org/abs/2311.17982)
|
10 |
+
[![Project Page](https://img.shields.io/badge/VBench-Website-green?logo=googlechrome&logoColor=green)](https://vchitect.github.io/VBench-project/)
|
11 |
+
[![HuggingFace](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Leaderboard-blue)](https://huggingface.co/spaces/Vchitect/VBench_Leaderboard)
|
12 |
+
[![Video](https://img.shields.io/badge/YouTube-Video-c4302b?logo=youtube&logoColor=red)](https://www.youtube.com/watch?v=7IhCC8Qqn8Y)
|
13 |
+
[![Visitor](https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fgithub.com%2FVchitect%2FVBench&count_bg=%23FFA500&title_bg=%23555555&icon=&icon_color=%23E7E7E7&title=visitors&edge_flat=false)](https://hits.seeyoufarm.com)
|
14 |
+
|
15 |
+
## Installation
|
16 |
+
```
|
17 |
+
pip install vbench
|
18 |
+
```
|
19 |
+
|
20 |
+
To evaluate some video generation ability aspects, you need to install [detectron2](https://github.com/facebookresearch/detectron2) via:
|
21 |
+
```
|
22 |
+
pip install detectron2@git+https://github.com/facebookresearch/detectron2.git
|
23 |
+
```
|
24 |
+
|
25 |
+
If there is an error during [detectron2](https://github.com/facebookresearch/detectron2) installation, see [here](https://detectron2.readthedocs.io/en/latest/tutorials/install.html).
|
26 |
+
|
27 |
+
## Usage
|
28 |
+
##### command line
|
29 |
+
```bash
|
30 |
+
vbench evaluate --videos_path $VIDEO_PATH --dimension $DIMENSION
|
31 |
+
```
|
32 |
+
For example:
|
33 |
+
```bash
|
34 |
+
vbench evaluate --videos_path "sampled_videos/lavie/human_action" --dimension "human_action"
|
35 |
+
```
|
36 |
+
##### python
|
37 |
+
```python
|
38 |
+
from vbench import VBench
|
39 |
+
my_VBench = VBench(device, <path/to/VBench_full_info.json>, <path/to/save/dir>)
|
40 |
+
my_VBench.evaluate(
|
41 |
+
videos_path = <video_path>,
|
42 |
+
name = <name>,
|
43 |
+
dimension_list = [<dimension>, <dimension>, ...],
|
44 |
+
)
|
45 |
+
```
|
46 |
+
For example:
|
47 |
+
```python
|
48 |
+
from vbench import VBench
|
49 |
+
my_VBench = VBench(device, "VBench_full_info.json", "evaluation_results")
|
50 |
+
my_VBench.evaluate(
|
51 |
+
videos_path = "sampled_videos/lavie/human_action",
|
52 |
+
name = "lavie_human_action",
|
53 |
+
dimension_list = ["human_action"],
|
54 |
+
)
|
55 |
+
```
|
56 |
+
|
57 |
+
## Prompt Suite
|
58 |
+
|
59 |
+
We provide prompt lists are at `prompts/`.
|
60 |
+
|
61 |
+
Check out [details of prompt suites](https://github.com/Vchitect/VBench/tree/master/prompts), and instructions for [**how to sample videos for evaluation**](https://github.com/Vchitect/VBench/tree/master/prompts).
|
62 |
+
|
63 |
+
## Citation
|
64 |
+
|
65 |
+
If you find this package useful for your reports or publications, please consider citing the VBench paper:
|
66 |
+
|
67 |
+
```bibtex
|
68 |
+
@article{huang2023vbench,
|
69 |
+
title={{VBench}: Comprehensive Benchmark Suite for Video Generative Models},
|
70 |
+
author={Huang, Ziqi and He, Yinan and Yu, Jiashuo and Zhang, Fan and Si, Chenyang and Jiang, Yuming and Zhang, Yuanhan and Wu, Tianxing and Jin, Qingyang and Chanpaisit, Nattapol and Wang, Yaohui and Chen, Xinyuan and Wang, Limin and Lin, Dahua and Qiao, Yu and Liu, Ziwei},
|
71 |
+
journal={arXiv preprint arXiv:2311.17982},
|
72 |
+
year={2023}
|
73 |
+
}
|
74 |
+
```
|
VBench/README.md
ADDED
@@ -0,0 +1,192 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
![vbench_logo](https://raw.githubusercontent.com/Vchitect/VBench/master/asset/vbench_logo_short.jpg)
|
2 |
+
|
3 |
+
<!-- [![arXiv](https://img.shields.io/badge/arXiv-2311.99999-b31b1b.svg)](https://arxiv.org/abs/2311.99999) -->
|
4 |
+
[![Paper](https://img.shields.io/badge/cs.CV-Paper-b31b1b?logo=arxiv&logoColor=red)](https://arxiv.org/abs/2311.17982)
|
5 |
+
[![Project Page](https://img.shields.io/badge/VBench-Website-green?logo=googlechrome&logoColor=green)](https://vchitect.github.io/VBench-project/)
|
6 |
+
[![PyPI](https://img.shields.io/pypi/v/vbench)](https://pypi.org/project/vbench/)
|
7 |
+
[![HuggingFace](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Leaderboard-blue)](https://huggingface.co/spaces/Vchitect/VBench_Leaderboard)
|
8 |
+
[![Video](https://img.shields.io/badge/YouTube-Video-c4302b?logo=youtube&logoColor=red)](https://www.youtube.com/watch?v=7IhCC8Qqn8Y)
|
9 |
+
[![Visitor](https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fgithub.com%2FVchitect%2FVBench&count_bg=%23FFA500&title_bg=%23555555&icon=&icon_color=%23E7E7E7&title=visitors&edge_flat=false)](https://hits.seeyoufarm.com)
|
10 |
+
|
11 |
+
|
12 |
+
This repository contains the implementation of the following paper:
|
13 |
+
> **VBench: Comprehensive Benchmark Suite for Video Generative Models**<br>
|
14 |
+
> [Ziqi Huang](https://ziqihuangg.github.io/)<sup>∗</sup>, [Yinan He](https://github.com/yinanhe)<sup>∗</sup>, [Jiashuo Yu](https://scholar.google.com/citations?user=iH0Aq0YAAAAJ&hl=zh-CN)<sup>∗</sup>, [Fan Zhang](https://github.com/zhangfan-p)<sup>∗</sup>, [Chenyang Si](https://chenyangsi.top/), [Yuming Jiang](https://yumingj.github.io/), [Yuanhan Zhang](https://zhangyuanhan-ai.github.io/), [Tianxing Wu](https://tianxingwu.github.io/), [Qingyang Jin](https://github.com/Vchitect/VBench), [Nattapol Chanpaisit](https://nattapolchan.github.io/me), [Yaohui Wang](https://wyhsirius.github.io/), [Xinyuan Chen](https://scholar.google.com/citations?user=3fWSC8YAAAAJ), [Limin Wang](https://wanglimin.github.io), [Dahua Lin](http://dahua.site/)<sup>+</sup>, [Yu Qiao](http://mmlab.siat.ac.cn/yuqiao/index.html)<sup>+</sup>, [Ziwei Liu](https://liuziwei7.github.io/)<sup>+</sup><br>
|
15 |
+
> IEEE/CVF Conference on Computer Vision and Pattern Recognition (**CVPR**), 2024
|
16 |
+
|
17 |
+
|
18 |
+
|
19 |
+
## :fire: Updates
|
20 |
+
- [03/2024] :fire::fire: **[VBench-Reliability](https://github.com/Vchitect/VBench/tree/master/vbench2_beta_reliability)** :fire::fire: We now support evaluating the **reliability** (*e.g.*, culture, fairness, bias, safety) of video generative models.
|
21 |
+
- [03/2024] :fire::fire: **[VBench-I2V](https://github.com/Vchitect/VBench/tree/master/vbench2_beta_i2v)** :fire::fire: We now support evaluating **Image-to-Video (I2V)** models. We also provide [Image Suite](https://drive.google.com/drive/folders/1fdOZKQ7HWZtgutCKKA7CMzOhMFUGv4Zx?usp=sharing).
|
22 |
+
- [03/2024] We support **evaluating customized videos**! See [here](https://github.com/Vchitect/VBench/?tab=readme-ov-file#new-evaluate-your-own-videos) for instructions.
|
23 |
+
- [01/2024] PyPI pacakge is released! [![PyPI](https://img.shields.io/pypi/v/vbench)](https://pypi.org/project/vbench/). Simply `pip install vbench`.
|
24 |
+
- [12/2023] :fire::fire: **[VBench](https://github.com/Vchitect/VBench?tab=readme-ov-file#usage)** :fire::fire: Evaluation code released for 16 **Text-to-Video (T2V) evaluation** dimensions.
|
25 |
+
- `['subject_consistency', 'background_consistency', 'temporal_flickering', 'motion_smoothness', 'dynamic_degree', 'aesthetic_quality', 'imaging_quality', 'object_class', 'multiple_objects', 'human_action', 'color', 'spatial_relationship', 'scene', 'temporal_style', 'appearance_style', 'overall_consistency']`
|
26 |
+
- [11/2023] Prompt Suites released. (See prompt lists [here](https://github.com/Vchitect/VBench/tree/master/prompts))
|
27 |
+
|
28 |
+
|
29 |
+
## :mega: Overview
|
30 |
+
![overall_structure](./asset/fig_teaser_new.jpg)
|
31 |
+
We propose **VBench**, a comprehensive benchmark suite for video generative models. We design a comprehensive and hierarchical <b>Evaluation Dimension Suite</b> to decompose "video generation quality" into multiple well-defined dimensions to facilitate fine-grained and objective evaluation. For each dimension and each content category, we carefully design a <b>Prompt Suite</b> as test cases, and sample <b>Generated Videos</b> from a set of video generation models. For each evaluation dimension, we specifically design an <b>Evaluation Method Suite</b>, which uses carefully crafted method or designated pipeline for automatic objective evaluation. We also conduct <b>Human Preference Annotation</b> for the generated videos for each dimension, and show that VBench evaluation results are <b>well aligned with human perceptions</b>. VBench can provide valuable insights from multiple perspectives.
|
32 |
+
|
33 |
+
|
34 |
+
## :mortar_board: Evaluation Results
|
35 |
+
<p align="center">
|
36 |
+
<img src="./asset/radar-open.jpg" width="48%" style="margin-right: 4%;" />
|
37 |
+
<img src="./asset/radar-close.jpg" width="48%" />
|
38 |
+
</p>
|
39 |
+
|
40 |
+
We visualize VBench evaluation results of various publicly available video generation models, as well as Gen-2 and Pika, across 16 VBench dimensions. We normalize the results per dimension for clearer comparisons. (See numeric values at our [Leaderboard](https://huggingface.co/spaces/Vchitect/VBench_Leaderboard))
|
41 |
+
|
42 |
+
<!-- The values have been normalized for better readability of the chart. The normalization process involves scaling each set of performance values to a common scale between 0.3 and 0.8. The formula used for normalization is: (value - min value) / (max value - min value). -->
|
43 |
+
|
44 |
+
|
45 |
+
## :hammer: Installation
|
46 |
+
### Install with pip
|
47 |
+
```
|
48 |
+
pip install vbench
|
49 |
+
```
|
50 |
+
|
51 |
+
To evaluate some video generation ability aspects, you need to install [detectron2](https://github.com/facebookresearch/detectron2) via:
|
52 |
+
```
|
53 |
+
pip install detectron2@git+https://github.com/facebookresearch/detectron2.git
|
54 |
+
```
|
55 |
+
|
56 |
+
If there is an error during [detectron2](https://github.com/facebookresearch/detectron2) installation, see [here](https://detectron2.readthedocs.io/en/latest/tutorials/install.html).
|
57 |
+
|
58 |
+
Download [VBench_full_info.json](https://github.com/Vchitect/VBench/blob/master/vbench/VBench_full_info.json) to your running directory to read the benchmark prompt suites.
|
59 |
+
|
60 |
+
### Install with git clone
|
61 |
+
git clone https://github.com/Vchitect/VBench.git
|
62 |
+
pip install -r VBench/requirements.txt
|
63 |
+
pip install VBench
|
64 |
+
|
65 |
+
If there is an error during [detectron2](https://github.com/facebookresearch/detectron2) installation, see [here](https://detectron2.readthedocs.io/en/latest/tutorials/install.html).
|
66 |
+
|
67 |
+
## Usage
|
68 |
+
Use VBench to evaluate videos, and video generative models.
|
69 |
+
- A Side Note: VBench is designed for evaluating different models on a standard benchmark. Therefore, by default, we enforce evaluation on the **standard VBench prompt lists** to ensure **fair comparisons** among different video generation models. That's also why we give warnings when a required video is not found. This is done via defining the set of prompts in [VBench_full_info.json](https://github.com/Vchitect/VBench/blob/master/vbench/VBench_full_info.json). However, we understand that many users would like to use VBench to evaluate their own videos, or videos generated from prompts that does not belong to the VBench Prompt Suite, so we also added the function of **Evaluating Your Own Videos**. Simply turn the `custom_input` flag on, and you can evaluate your own videos.
|
70 |
+
|
71 |
+
|
72 |
+
### **[New]** Evaluate Your Own Videos
|
73 |
+
We support evaluating any video. Simply provide the path to the video file, or the path to the folder that contains your videos. There is no requirement on the videos' names.
|
74 |
+
- Note: We support customized videos / prompts for the following dimensions: `'subject_consistency', 'background_consistency', 'motion_smoothness', 'dynamic_degree', 'aesthetic_quality', 'imaging_quality'`
|
75 |
+
|
76 |
+
|
77 |
+
To evaluate videos with customed input prompt, run our script with the `custom_input` flag on:
|
78 |
+
```
|
79 |
+
python evaluate.py \
|
80 |
+
--dimension $DIMENSION \
|
81 |
+
--videos_path /path/to/folder_or_video/ \
|
82 |
+
--custom_input
|
83 |
+
```
|
84 |
+
alternatively you can use our command:
|
85 |
+
```
|
86 |
+
vbench evaluate \
|
87 |
+
--dimension $DIMENSION \
|
88 |
+
--videos_path /path/to/folder_or_video/ \
|
89 |
+
--custom_input
|
90 |
+
```
|
91 |
+
|
92 |
+
### Evaluation on the Standard Prompt Suite of VBench
|
93 |
+
|
94 |
+
##### command line
|
95 |
+
```bash
|
96 |
+
vbench evaluate --videos_path $VIDEO_PATH --dimension $DIMENSION
|
97 |
+
```
|
98 |
+
For example:
|
99 |
+
```bash
|
100 |
+
vbench evaluate --videos_path "sampled_videos/lavie/human_action" --dimension "human_action"
|
101 |
+
```
|
102 |
+
##### python
|
103 |
+
```python
|
104 |
+
from vbench import VBench
|
105 |
+
my_VBench = VBench(device, <path/to/VBench_full_info.json>, <path/to/save/dir>)
|
106 |
+
my_VBench.evaluate(
|
107 |
+
videos_path = <video_path>,
|
108 |
+
name = <name>,
|
109 |
+
dimension_list = [<dimension>, <dimension>, ...],
|
110 |
+
)
|
111 |
+
```
|
112 |
+
For example:
|
113 |
+
```python
|
114 |
+
from vbench import VBench
|
115 |
+
my_VBench = VBench(device, "vbench/VBench_full_info.json", "evaluation_results")
|
116 |
+
my_VBench.evaluate(
|
117 |
+
videos_path = "sampled_videos/lavie/human_action",
|
118 |
+
name = "lavie_human_action",
|
119 |
+
dimension_list = ["human_action"],
|
120 |
+
)
|
121 |
+
```
|
122 |
+
|
123 |
+
### Example of Evaluating VideoCrafter-1.0
|
124 |
+
We have provided scripts to download VideoCrafter-1.0 samples, and the corresponding evaluation scripts.
|
125 |
+
```
|
126 |
+
# download sampled videos
|
127 |
+
sh scripts/download_videocrafter1.sh
|
128 |
+
|
129 |
+
# evaluate VideoCrafter-1.0
|
130 |
+
sh scripts/evaluate_videocrafter1.sh
|
131 |
+
```
|
132 |
+
|
133 |
+
|
134 |
+
|
135 |
+
## :gem: Pre-Trained Models
|
136 |
+
[Optional] Please download the pre-trained weights according to the guidance in the `model_path.txt` file for each model in the `pretrained` folder to `~/.cache/vbench`.
|
137 |
+
|
138 |
+
## :bookmark_tabs: Prompt Suite
|
139 |
+
|
140 |
+
We provide prompt lists are at `prompts/`.
|
141 |
+
|
142 |
+
Check out [details of prompt suites](https://github.com/Vchitect/VBench/tree/master/prompts), and instructions for [**how to sample videos for evaluation**](https://github.com/Vchitect/VBench/tree/master/prompts).
|
143 |
+
|
144 |
+
## :surfer: Evaluation Method Suite
|
145 |
+
|
146 |
+
To perform evaluation on one dimension, run this:
|
147 |
+
```
|
148 |
+
python evaluate.py --videos_path $VIDEOS_PATH --dimension $DIMENSION
|
149 |
+
```
|
150 |
+
- The complete list of dimensions:
|
151 |
+
```
|
152 |
+
['subject_consistency', 'background_consistency', 'temporal_flickering', 'motion_smoothness', 'dynamic_degree', 'aesthetic_quality', 'imaging_quality', 'object_class', 'multiple_objects', 'human_action', 'color', 'spatial_relationship', 'scene', 'temporal_style', 'appearance_style', 'overall_consistency']
|
153 |
+
```
|
154 |
+
|
155 |
+
Alternatively, you can evaluate multiple models and multiple dimensions using this script:
|
156 |
+
```
|
157 |
+
bash evaluate.sh
|
158 |
+
```
|
159 |
+
- The default sampled video paths:
|
160 |
+
```
|
161 |
+
vbench_videos/{model}/{dimension}/{prompt}-{index}.mp4/gif
|
162 |
+
```
|
163 |
+
|
164 |
+
To filter static videos in the temporal flickering dimension, run this:
|
165 |
+
```
|
166 |
+
python static_filter.py --videos_path $VIDEOS_PATH
|
167 |
+
```
|
168 |
+
|
169 |
+
|
170 |
+
## :black_nib: Citation
|
171 |
+
|
172 |
+
If you find our repo useful for your research, please consider citing our paper:
|
173 |
+
|
174 |
+
```bibtex
|
175 |
+
@InProceedings{huang2023vbench,
|
176 |
+
title={{VBench}: Comprehensive Benchmark Suite for Video Generative Models},
|
177 |
+
author={Huang, Ziqi and He, Yinan and Yu, Jiashuo and Zhang, Fan and Si, Chenyang and Jiang, Yuming and Zhang, Yuanhan and Wu, Tianxing and Jin, Qingyang and Chanpaisit, Nattapol and Wang, Yaohui and Chen, Xinyuan and Wang, Limin and Lin, Dahua and Qiao, Yu and Liu, Ziwei},
|
178 |
+
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
|
179 |
+
year={2024}
|
180 |
+
}
|
181 |
+
```
|
182 |
+
|
183 |
+
|
184 |
+
## :hearts: Acknowledgement
|
185 |
+
|
186 |
+
### VBench Contributors
|
187 |
+
Order is based on the time joining the project:
|
188 |
+
> [Ziqi Huang](https://ziqihuangg.github.io/), [Yinan He](https://github.com/yinanhe), [Jiashuo Yu](https://scholar.google.com/citations?user=iH0Aq0YAAAAJ&hl=zh-CN), [Fan Zhang](https://github.com/zhangfan-p), [Nattapol Chanpaisit](https://nattapolchan.github.io/me), [Xiaojie Xu](https://github.com/xjxu21).
|
189 |
+
|
190 |
+
### Open-Sourced Repositories
|
191 |
+
This project wouldn't be possible without the following open-sourced repositories:
|
192 |
+
[AMT](https://github.com/MCG-NKU/AMT/), [UMT](https://github.com/OpenGVLab/unmasked_teacher), [RAM](https://github.com/xinyu1205/recognize-anything), [CLIP](https://github.com/openai/CLIP), [RAFT](https://github.com/princeton-vl/RAFT), [GRiT](https://github.com/JialianW/GRiT), [IQA-PyTorch](https://github.com/chaofengc/IQA-PyTorch/), [ViCLIP](https://github.com/OpenGVLab/InternVideo/tree/main/Data/InternVid), and [LAION Aesthetic Predictor](https://github.com/LAION-AI/aesthetic-predictor).
|
VBench/asset/fig_teaser_new.jpg
ADDED
Git LFS Details
|
VBench/asset/radar-close.jpg
ADDED
Git LFS Details
|
VBench/asset/radar-open.jpg
ADDED
Git LFS Details
|
VBench/asset/vbench_logo_short.jpg
ADDED
VBench/bin/evaluate
ADDED
@@ -0,0 +1,70 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
#!/usr/bin/env python3
|
2 |
+
|
3 |
+
import torch
|
4 |
+
import vbench
|
5 |
+
from vbench import VBench
|
6 |
+
|
7 |
+
|
8 |
+
import argparse
|
9 |
+
|
10 |
+
def parse_args():
|
11 |
+
|
12 |
+
parser = argparse.ArgumentParser(description='VBench')
|
13 |
+
parser.add_argument(
|
14 |
+
"--output_path",
|
15 |
+
type=str,
|
16 |
+
default='./evaluation_results/',
|
17 |
+
help="output path to save the evaluation results",
|
18 |
+
)
|
19 |
+
parser.add_argument(
|
20 |
+
"--full_json_dir",
|
21 |
+
type=str,
|
22 |
+
default='./VBench_full_info.json',
|
23 |
+
help="path to save the json file that contains the prompt and dimension information",
|
24 |
+
)
|
25 |
+
parser.add_argument(
|
26 |
+
"--videos_path",
|
27 |
+
type=str,
|
28 |
+
required=True,
|
29 |
+
help="folder that contains the sampled videos",
|
30 |
+
)
|
31 |
+
parser.add_argument(
|
32 |
+
"--dimension",
|
33 |
+
type=str,
|
34 |
+
required=True,
|
35 |
+
help="evaluation dimensions",
|
36 |
+
)
|
37 |
+
parser.add_argument(
|
38 |
+
"--load_ckpt_from_local",
|
39 |
+
type=bool,
|
40 |
+
required=False,
|
41 |
+
help="whether load checkpoints from local default paths (assuming you have downloaded the checkpoints locally",
|
42 |
+
)
|
43 |
+
parser.add_argument(
|
44 |
+
"--read_frame",
|
45 |
+
type=bool,
|
46 |
+
required=False,
|
47 |
+
help="whether directly read frames, or directly read videos",
|
48 |
+
)
|
49 |
+
args = parser.parse_args()
|
50 |
+
return args
|
51 |
+
|
52 |
+
def main():
|
53 |
+
args = parse_args()
|
54 |
+
print(f'args: {args}')
|
55 |
+
|
56 |
+
device = torch.device("cuda")
|
57 |
+
my_VBench = VBench(device, args.full_json_dir, args.output_path)
|
58 |
+
|
59 |
+
print(f'start evaluation')
|
60 |
+
my_VBench.evaluate(
|
61 |
+
videos_path = args.videos_path,
|
62 |
+
name = args.dimension,
|
63 |
+
dimension_list = [args.dimension],
|
64 |
+
local=args.load_ckpt_from_local,
|
65 |
+
read_frame=args.read_frame,
|
66 |
+
)
|
67 |
+
print('done')
|
68 |
+
|
69 |
+
if __name__ == "__main__":
|
70 |
+
main()
|
VBench/dimension_to_folder.json
ADDED
@@ -0,0 +1,18 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"subject_consistency": "subject_consistency",
|
3 |
+
"background_consistency": "scene",
|
4 |
+
"aesthetic_quality": "overall_consistency",
|
5 |
+
"imaging_quality": "overall_consistency",
|
6 |
+
"object_class": "object_class",
|
7 |
+
"multiple_objects": "multiple_objects",
|
8 |
+
"color": "color",
|
9 |
+
"spatial_relationship": "spatial_relationship",
|
10 |
+
"scene": "scene",
|
11 |
+
"temporal_style": "temporal_style",
|
12 |
+
"overall_consistency": "overall_consistency",
|
13 |
+
"human_action": "human_action",
|
14 |
+
"temporal_flickering": "temporal_flickering",
|
15 |
+
"motion_smoothness": "subject_consistency",
|
16 |
+
"dynamic_degree": "subject_consistency",
|
17 |
+
"appearance_style": "appearance_style"
|
18 |
+
}
|
VBench/evaluate.py
ADDED
@@ -0,0 +1,85 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import torch
|
2 |
+
import os
|
3 |
+
from vbench import VBench
|
4 |
+
from datetime import datetime
|
5 |
+
|
6 |
+
import argparse
|
7 |
+
|
8 |
+
def parse_args():
|
9 |
+
|
10 |
+
CUR_DIR = os.path.dirname(os.path.abspath(__file__))
|
11 |
+
parser = argparse.ArgumentParser(description='VBench')
|
12 |
+
parser.add_argument(
|
13 |
+
"--output_path",
|
14 |
+
type=str,
|
15 |
+
default='./evaluation_results/',
|
16 |
+
help="output path to save the evaluation results",
|
17 |
+
)
|
18 |
+
parser.add_argument(
|
19 |
+
"--full_json_dir",
|
20 |
+
type=str,
|
21 |
+
default=f'{CUR_DIR}/vbench/VBench_full_info.json',
|
22 |
+
help="path to save the json file that contains the prompt and dimension information",
|
23 |
+
)
|
24 |
+
parser.add_argument(
|
25 |
+
"--videos_path",
|
26 |
+
type=str,
|
27 |
+
required=True,
|
28 |
+
help="folder that contains the sampled videos",
|
29 |
+
)
|
30 |
+
parser.add_argument(
|
31 |
+
"--dimension",
|
32 |
+
nargs='+',
|
33 |
+
required=True,
|
34 |
+
help="list of evaluation dimensions, usage: --dimension <dim_1> <dim_2>",
|
35 |
+
)
|
36 |
+
parser.add_argument(
|
37 |
+
"--load_ckpt_from_local",
|
38 |
+
type=bool,
|
39 |
+
required=False,
|
40 |
+
help="whether load checkpoints from local default paths (assuming you have downloaded the checkpoints locally",
|
41 |
+
)
|
42 |
+
parser.add_argument(
|
43 |
+
"--read_frame",
|
44 |
+
type=bool,
|
45 |
+
required=False,
|
46 |
+
help="whether directly read frames, or directly read videos",
|
47 |
+
)
|
48 |
+
parser.add_argument(
|
49 |
+
"--custom_input",
|
50 |
+
action="store_true",
|
51 |
+
required=False,
|
52 |
+
help="whether use custom input prompt or vbench prompt"
|
53 |
+
)
|
54 |
+
parser.add_argument(
|
55 |
+
"--output_filename",
|
56 |
+
type=str,
|
57 |
+
required=True,
|
58 |
+
help="filename before _full_info or _eval_results",
|
59 |
+
)
|
60 |
+
args = parser.parse_args()
|
61 |
+
return args
|
62 |
+
|
63 |
+
|
64 |
+
def main():
|
65 |
+
args = parse_args()
|
66 |
+
print(f'args: {args}')
|
67 |
+
|
68 |
+
device = torch.device("cuda")
|
69 |
+
my_VBench = VBench(device, args.full_json_dir, args.output_path)
|
70 |
+
|
71 |
+
print(f'start evaluation')
|
72 |
+
# current_time = datetime.now().strftime('%Y-%m-%d-%H:%M:%S')
|
73 |
+
my_VBench.evaluate(
|
74 |
+
videos_path = args.videos_path,
|
75 |
+
name = args.output_filename,
|
76 |
+
dimension_list = args.dimension,
|
77 |
+
local=args.load_ckpt_from_local,
|
78 |
+
read_frame=args.read_frame,
|
79 |
+
custom_prompt=args.custom_input,
|
80 |
+
)
|
81 |
+
print('done')
|
82 |
+
|
83 |
+
|
84 |
+
if __name__ == "__main__":
|
85 |
+
main()
|
VBench/evaluate.sh
ADDED
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
#!/bin/bash
|
2 |
+
|
3 |
+
# Define the model list
|
4 |
+
models=("lavie" "modelscope" "videocrafter" "cogvideo")
|
5 |
+
|
6 |
+
# Define the dimension list
|
7 |
+
dimensions=("subject_consistency" "background_consistency" "aesthetic_quality" "imaging_quality" "object_class" "multiple_objects" "color" "spatial_relationship" "scene" "temporal_style" "overall_consistency" "human_action" "temporal_flickering" "motion_smoothness" "dynamic_degree" "appearance_style")
|
8 |
+
|
9 |
+
# Corresponding folder names
|
10 |
+
folders=("subject_consistency" "scene" "overall_consistency" "overall_consistency" "object_class" "multiple_objects" "color" "spatial_relationship" "scene" "temporal_style" "overall_consistency" "human_action" "temporal_flickering" "subject_consistency" "subject_consistency" "appearance_style")
|
11 |
+
|
12 |
+
# Base path for videos
|
13 |
+
base_path='./vbench_videos/' # TODO: change to local path
|
14 |
+
|
15 |
+
# Loop over each model
|
16 |
+
for model in "${models[@]}"; do
|
17 |
+
# Loop over each dimension
|
18 |
+
for i in "${!dimensions[@]}"; do
|
19 |
+
# Get the dimension and corresponding folder
|
20 |
+
dimension=${dimensions[i]}
|
21 |
+
folder=${folders[i]}
|
22 |
+
|
23 |
+
# Construct the video path
|
24 |
+
videos_path="${base_path}${model}/${folder}"
|
25 |
+
echo "$dimension $videos_path"
|
26 |
+
|
27 |
+
# Run the evaluation script
|
28 |
+
python evaluate.py --videos_path $videos_path --dimension $dimension
|
29 |
+
done
|
30 |
+
done
|
VBench/evaluation_results/README.md
ADDED
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
1 |
+
# :bar_chart: Evaluation Results
|
2 |
+
Evaluation results will be saved here.
|
VBench/pretrained/README.md
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
# :gem: Pre-Trained Models
|
2 |
+
[Optional] Please download the pre-trained weights according to the guidance in the `model_path.txt` file for each model (see each folder).
|
3 |
+
|
VBench/pretrained/aesthetic_model/model_path.txt
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
wget https://github.com/LAION-AI/aesthetic-predictor/blob/main/sa_0_4_vit_l_14_linear.pth -P ~/.cache/vbench/aesthetic_model/emb_reader
|
VBench/pretrained/amt_model/AMT-S.yaml
ADDED
@@ -0,0 +1,63 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
exp_name: floloss1e-2_300epoch_bs24_lr2e-4
|
2 |
+
seed: 2023
|
3 |
+
epochs: 300
|
4 |
+
distributed: true
|
5 |
+
lr: 2e-4
|
6 |
+
lr_min: 2e-5
|
7 |
+
weight_decay: 0.0
|
8 |
+
resume_state: null
|
9 |
+
save_dir: work_dir
|
10 |
+
eval_interval: 1
|
11 |
+
|
12 |
+
network:
|
13 |
+
name: networks.AMT-S.Model
|
14 |
+
params:
|
15 |
+
corr_radius: 3
|
16 |
+
corr_lvls: 4
|
17 |
+
num_flows: 3
|
18 |
+
|
19 |
+
data:
|
20 |
+
train:
|
21 |
+
name: datasets.vimeo_datasets.Vimeo90K_Train_Dataset
|
22 |
+
params:
|
23 |
+
dataset_dir: data/vimeo_triplet
|
24 |
+
val:
|
25 |
+
name: datasets.vimeo_datasets.Vimeo90K_Test_Dataset
|
26 |
+
params:
|
27 |
+
dataset_dir: data/vimeo_triplet
|
28 |
+
train_loader:
|
29 |
+
batch_size: 24
|
30 |
+
num_workers: 12
|
31 |
+
val_loader:
|
32 |
+
batch_size: 24
|
33 |
+
num_workers: 3
|
34 |
+
|
35 |
+
logger:
|
36 |
+
use_wandb: false
|
37 |
+
resume_id: null
|
38 |
+
|
39 |
+
losses:
|
40 |
+
- {
|
41 |
+
name: losses.loss.CharbonnierLoss,
|
42 |
+
nickname: l_rec,
|
43 |
+
params: {
|
44 |
+
loss_weight: 1.0,
|
45 |
+
keys: [imgt_pred, imgt]
|
46 |
+
}
|
47 |
+
}
|
48 |
+
- {
|
49 |
+
name: losses.loss.TernaryLoss,
|
50 |
+
nickname: l_ter,
|
51 |
+
params: {
|
52 |
+
loss_weight: 1.0,
|
53 |
+
keys: [imgt_pred, imgt]
|
54 |
+
}
|
55 |
+
}
|
56 |
+
- {
|
57 |
+
name: losses.loss.MultipleFlowLoss,
|
58 |
+
nickname: l_flo,
|
59 |
+
params: {
|
60 |
+
loss_weight: 0.002,
|
61 |
+
keys: [flow0_pred, flow1_pred, flow]
|
62 |
+
}
|
63 |
+
}
|
VBench/pretrained/amt_model/download.sh
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
wget https://huggingface.co/lalala125/AMT/resolve/main/amt-s.pth -P ~/.cache/amt_model
|
VBench/pretrained/caption_model/model_path.txt
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
wget https://huggingface.co/spaces/xinyu1205/recognize-anything/resolve/main/tag2text_swin_14m.pth -P ~/.cache/vbench/caption_model
|
VBench/pretrained/clip_model/model_path.txt
ADDED
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
1 |
+
wget https://openaipublic.azureedge.net/clip/models/40d365715913c9da98579312b702a82c18be219cc2a73407c4526f58eba950af/ViT-B-32.pt -P ~/.cache/vbench/clip_model
|
2 |
+
wget https://openaipublic.azureedge.net/clip/models/b8cca3fd41ae0c99ba7e8951adf17d267cdb84cd88be6f7c2e0eca1737a03836/ViT-L-14.pt -P ~/.cache/vbench/clip_model
|
VBench/pretrained/grit_model/model_path.txt
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
wget https://datarelease.blob.core.windows.net/grit/models/grit_b_densecap_objectdet.pth -P ~/.cache/vbench/grit_model
|
VBench/pretrained/pyiqa_model/model_path.txt
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
wget https://github.com/chaofengc/IQA-PyTorch/releases/download/v0.1-weights/musiq_spaq_ckpt-358bb6af.pth -P ~/.cache/vbench/pyiqa_model
|
VBench/pretrained/raft_model/download.sh
ADDED
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
#!/bin/bash
|
2 |
+
CACHE_DIR=~/.cache/vbench
|
3 |
+
wget -P $CACHE_DIR/raft_model/ https://dl.dropboxusercontent.com/s/4j4z58wuv8o0mfz/models.zip
|
4 |
+
unzip -d ${CACHE_DIR}/raft_model/ $CACHE_DIR/raft_model/models.zip
|
5 |
+
rm -r $CACHE_DIR/raft_model/models.zip
|
VBench/pretrained/umt_model/kinetics_400_categroies.txt
ADDED
@@ -0,0 +1,400 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
riding a bike 0
|
2 |
+
marching 1
|
3 |
+
dodgeball 2
|
4 |
+
playing cymbals 3
|
5 |
+
checking tires 4
|
6 |
+
roller skating 5
|
7 |
+
tasting beer 6
|
8 |
+
clapping 7
|
9 |
+
drawing 8
|
10 |
+
juggling fire 9
|
11 |
+
bobsledding 10
|
12 |
+
petting animal (not cat) 11
|
13 |
+
spray painting 12
|
14 |
+
training dog 13
|
15 |
+
eating watermelon 14
|
16 |
+
building cabinet 15
|
17 |
+
applauding 16
|
18 |
+
playing harp 17
|
19 |
+
balloon blowing 18
|
20 |
+
sled dog racing 19
|
21 |
+
wrestling 20
|
22 |
+
pole vault 21
|
23 |
+
hurling (sport) 22
|
24 |
+
riding scooter 23
|
25 |
+
shearing sheep 24
|
26 |
+
sweeping floor 25
|
27 |
+
eating carrots 26
|
28 |
+
skateboarding 27
|
29 |
+
dunking basketball 28
|
30 |
+
disc golfing 29
|
31 |
+
eating spaghetti 30
|
32 |
+
playing flute 31
|
33 |
+
riding mechanical bull 32
|
34 |
+
making sushi 33
|
35 |
+
trapezing 34
|
36 |
+
picking fruit 35
|
37 |
+
stretching leg 36
|
38 |
+
playing ukulele 37
|
39 |
+
tying tie 38
|
40 |
+
skydiving 39
|
41 |
+
playing cello 40
|
42 |
+
jumping into pool 41
|
43 |
+
shooting goal (soccer) 42
|
44 |
+
trimming trees 43
|
45 |
+
bookbinding 44
|
46 |
+
ski jumping 45
|
47 |
+
walking the dog 46
|
48 |
+
riding unicycle 47
|
49 |
+
shaving head 48
|
50 |
+
hopscotch 49
|
51 |
+
playing piano 50
|
52 |
+
parasailing 51
|
53 |
+
bartending 52
|
54 |
+
kicking field goal 53
|
55 |
+
finger snapping 54
|
56 |
+
dining 55
|
57 |
+
yawning 56
|
58 |
+
peeling potatoes 57
|
59 |
+
canoeing or kayaking 58
|
60 |
+
front raises 59
|
61 |
+
laughing 60
|
62 |
+
dancing macarena 61
|
63 |
+
digging 62
|
64 |
+
reading newspaper 63
|
65 |
+
hitting baseball 64
|
66 |
+
clay pottery making 65
|
67 |
+
exercising with an exercise ball 66
|
68 |
+
playing saxophone 67
|
69 |
+
shooting basketball 68
|
70 |
+
washing hair 69
|
71 |
+
lunge 70
|
72 |
+
brushing hair 71
|
73 |
+
curling hair 72
|
74 |
+
kitesurfing 73
|
75 |
+
tapping guitar 74
|
76 |
+
bending back 75
|
77 |
+
skipping rope 76
|
78 |
+
situp 77
|
79 |
+
folding paper 78
|
80 |
+
cracking neck 79
|
81 |
+
assembling computer 80
|
82 |
+
cleaning gutters 81
|
83 |
+
blowing out candles 82
|
84 |
+
shaking hands 83
|
85 |
+
dancing gangnam style 84
|
86 |
+
windsurfing 85
|
87 |
+
tap dancing 86
|
88 |
+
skiing (not slalom or crosscountry) 87
|
89 |
+
bandaging 88
|
90 |
+
push up 89
|
91 |
+
doing nails 90
|
92 |
+
punching person (boxing) 91
|
93 |
+
bouncing on trampoline 92
|
94 |
+
scrambling eggs 93
|
95 |
+
singing 94
|
96 |
+
cleaning floor 95
|
97 |
+
krumping 96
|
98 |
+
drumming fingers 97
|
99 |
+
snowmobiling 98
|
100 |
+
gymnastics tumbling 99
|
101 |
+
headbanging 100
|
102 |
+
catching or throwing frisbee 101
|
103 |
+
riding elephant 102
|
104 |
+
bee keeping 103
|
105 |
+
feeding birds 104
|
106 |
+
snatch weight lifting 105
|
107 |
+
mowing lawn 106
|
108 |
+
fixing hair 107
|
109 |
+
playing trumpet 108
|
110 |
+
flying kite 109
|
111 |
+
crossing river 110
|
112 |
+
swinging legs 111
|
113 |
+
sanding floor 112
|
114 |
+
belly dancing 113
|
115 |
+
sneezing 114
|
116 |
+
clean and jerk 115
|
117 |
+
side kick 116
|
118 |
+
filling eyebrows 117
|
119 |
+
shuffling cards 118
|
120 |
+
recording music 119
|
121 |
+
cartwheeling 120
|
122 |
+
feeding fish 121
|
123 |
+
folding clothes 122
|
124 |
+
water skiing 123
|
125 |
+
tobogganing 124
|
126 |
+
blowing leaves 125
|
127 |
+
smoking 126
|
128 |
+
unboxing 127
|
129 |
+
tai chi 128
|
130 |
+
waxing legs 129
|
131 |
+
riding camel 130
|
132 |
+
slapping 131
|
133 |
+
tossing salad 132
|
134 |
+
capoeira 133
|
135 |
+
playing cards 134
|
136 |
+
playing organ 135
|
137 |
+
playing violin 136
|
138 |
+
playing drums 137
|
139 |
+
tapping pen 138
|
140 |
+
vault 139
|
141 |
+
shoveling snow 140
|
142 |
+
playing tennis 141
|
143 |
+
getting a tattoo 142
|
144 |
+
making a sandwich 143
|
145 |
+
making tea 144
|
146 |
+
grinding meat 145
|
147 |
+
squat 146
|
148 |
+
eating doughnuts 147
|
149 |
+
ice fishing 148
|
150 |
+
snowkiting 149
|
151 |
+
kicking soccer ball 150
|
152 |
+
playing controller 151
|
153 |
+
giving or receiving award 152
|
154 |
+
welding 153
|
155 |
+
throwing discus 154
|
156 |
+
throwing axe 155
|
157 |
+
ripping paper 156
|
158 |
+
swimming butterfly stroke 157
|
159 |
+
air drumming 158
|
160 |
+
blowing nose 159
|
161 |
+
hockey stop 160
|
162 |
+
taking a shower 161
|
163 |
+
bench pressing 162
|
164 |
+
planting trees 163
|
165 |
+
pumping fist 164
|
166 |
+
climbing tree 165
|
167 |
+
tickling 166
|
168 |
+
high kick 167
|
169 |
+
waiting in line 168
|
170 |
+
slacklining 169
|
171 |
+
tango dancing 170
|
172 |
+
hurdling 171
|
173 |
+
carrying baby 172
|
174 |
+
celebrating 173
|
175 |
+
sharpening knives 174
|
176 |
+
passing American football (in game) 175
|
177 |
+
headbutting 176
|
178 |
+
playing recorder 177
|
179 |
+
brush painting 178
|
180 |
+
garbage collecting 179
|
181 |
+
robot dancing 180
|
182 |
+
shredding paper 181
|
183 |
+
pumping gas 182
|
184 |
+
rock climbing 183
|
185 |
+
hula hooping 184
|
186 |
+
braiding hair 185
|
187 |
+
opening present 186
|
188 |
+
texting 187
|
189 |
+
decorating the christmas tree 188
|
190 |
+
answering questions 189
|
191 |
+
playing keyboard 190
|
192 |
+
writing 191
|
193 |
+
bungee jumping 192
|
194 |
+
sniffing 193
|
195 |
+
eating burger 194
|
196 |
+
playing accordion 195
|
197 |
+
making pizza 196
|
198 |
+
playing volleyball 197
|
199 |
+
tasting food 198
|
200 |
+
pushing cart 199
|
201 |
+
spinning poi 200
|
202 |
+
cleaning windows 201
|
203 |
+
arm wrestling 202
|
204 |
+
changing oil 203
|
205 |
+
swimming breast stroke 204
|
206 |
+
tossing coin 205
|
207 |
+
deadlifting 206
|
208 |
+
hoverboarding 207
|
209 |
+
cutting watermelon 208
|
210 |
+
cheerleading 209
|
211 |
+
snorkeling 210
|
212 |
+
washing hands 211
|
213 |
+
eating cake 212
|
214 |
+
pull ups 213
|
215 |
+
surfing water 214
|
216 |
+
eating hotdog 215
|
217 |
+
holding snake 216
|
218 |
+
playing harmonica 217
|
219 |
+
ironing 218
|
220 |
+
cutting nails 219
|
221 |
+
golf chipping 220
|
222 |
+
shot put 221
|
223 |
+
hugging 222
|
224 |
+
playing clarinet 223
|
225 |
+
faceplanting 224
|
226 |
+
trimming or shaving beard 225
|
227 |
+
drinking shots 226
|
228 |
+
riding mountain bike 227
|
229 |
+
tying bow tie 228
|
230 |
+
swinging on something 229
|
231 |
+
skiing crosscountry 230
|
232 |
+
unloading truck 231
|
233 |
+
cleaning pool 232
|
234 |
+
jogging 233
|
235 |
+
ice climbing 234
|
236 |
+
mopping floor 235
|
237 |
+
making bed 236
|
238 |
+
diving cliff 237
|
239 |
+
washing dishes 238
|
240 |
+
grooming dog 239
|
241 |
+
weaving basket 240
|
242 |
+
frying vegetables 241
|
243 |
+
stomping grapes 242
|
244 |
+
moving furniture 243
|
245 |
+
cooking sausages 244
|
246 |
+
doing laundry 245
|
247 |
+
dying hair 246
|
248 |
+
knitting 247
|
249 |
+
reading book 248
|
250 |
+
baby waking up 249
|
251 |
+
punching bag 250
|
252 |
+
surfing crowd 251
|
253 |
+
cooking chicken 252
|
254 |
+
pushing car 253
|
255 |
+
springboard diving 254
|
256 |
+
swing dancing 255
|
257 |
+
massaging legs 256
|
258 |
+
beatboxing 257
|
259 |
+
breading or breadcrumbing 258
|
260 |
+
somersaulting 259
|
261 |
+
brushing teeth 260
|
262 |
+
stretching arm 261
|
263 |
+
juggling balls 262
|
264 |
+
massaging person's head 263
|
265 |
+
eating ice cream 264
|
266 |
+
extinguishing fire 265
|
267 |
+
hammer throw 266
|
268 |
+
whistling 267
|
269 |
+
crawling baby 268
|
270 |
+
using remote controller (not gaming) 269
|
271 |
+
playing cricket 270
|
272 |
+
opening bottle 271
|
273 |
+
playing xylophone 272
|
274 |
+
motorcycling 273
|
275 |
+
driving car 274
|
276 |
+
exercising arm 275
|
277 |
+
passing American football (not in game) 276
|
278 |
+
playing kickball 277
|
279 |
+
sticking tongue out 278
|
280 |
+
flipping pancake 279
|
281 |
+
catching fish 280
|
282 |
+
eating chips 281
|
283 |
+
shaking head 282
|
284 |
+
sword fighting 283
|
285 |
+
playing poker 284
|
286 |
+
cooking on campfire 285
|
287 |
+
doing aerobics 286
|
288 |
+
paragliding 287
|
289 |
+
using segway 288
|
290 |
+
folding napkins 289
|
291 |
+
playing bagpipes 290
|
292 |
+
gargling 291
|
293 |
+
skiing slalom 292
|
294 |
+
strumming guitar 293
|
295 |
+
javelin throw 294
|
296 |
+
waxing back 295
|
297 |
+
riding or walking with horse 296
|
298 |
+
plastering 297
|
299 |
+
long jump 298
|
300 |
+
parkour 299
|
301 |
+
wrapping present 300
|
302 |
+
egg hunting 301
|
303 |
+
archery 302
|
304 |
+
cleaning toilet 303
|
305 |
+
swimming backstroke 304
|
306 |
+
snowboarding 305
|
307 |
+
catching or throwing baseball 306
|
308 |
+
massaging back 307
|
309 |
+
blowing glass 308
|
310 |
+
playing guitar 309
|
311 |
+
playing chess 310
|
312 |
+
golf driving 311
|
313 |
+
presenting weather forecast 312
|
314 |
+
rock scissors paper 313
|
315 |
+
high jump 314
|
316 |
+
baking cookies 315
|
317 |
+
using computer 316
|
318 |
+
washing feet 317
|
319 |
+
arranging flowers 318
|
320 |
+
playing bass guitar 319
|
321 |
+
spraying 320
|
322 |
+
cutting pineapple 321
|
323 |
+
waxing chest 322
|
324 |
+
auctioning 323
|
325 |
+
jetskiing 324
|
326 |
+
drinking 325
|
327 |
+
busking 326
|
328 |
+
playing monopoly 327
|
329 |
+
salsa dancing 328
|
330 |
+
waxing eyebrows 329
|
331 |
+
watering plants 330
|
332 |
+
zumba 331
|
333 |
+
chopping wood 332
|
334 |
+
pushing wheelchair 333
|
335 |
+
carving pumpkin 334
|
336 |
+
building shed 335
|
337 |
+
making jewelry 336
|
338 |
+
catching or throwing softball 337
|
339 |
+
bending metal 338
|
340 |
+
ice skating 339
|
341 |
+
dancing charleston 340
|
342 |
+
abseiling 341
|
343 |
+
climbing a rope 342
|
344 |
+
crying 343
|
345 |
+
cleaning shoes 344
|
346 |
+
dancing ballet 345
|
347 |
+
driving tractor 346
|
348 |
+
triple jump 347
|
349 |
+
throwing ball 348
|
350 |
+
getting a haircut 349
|
351 |
+
running on treadmill 350
|
352 |
+
climbing ladder 351
|
353 |
+
blasting sand 352
|
354 |
+
playing trombone 353
|
355 |
+
drop kicking 354
|
356 |
+
country line dancing 355
|
357 |
+
changing wheel 356
|
358 |
+
feeding goats 357
|
359 |
+
tying knot (not on a tie) 358
|
360 |
+
setting table 359
|
361 |
+
shaving legs 360
|
362 |
+
kissing 361
|
363 |
+
riding mule 362
|
364 |
+
counting money 363
|
365 |
+
laying bricks 364
|
366 |
+
barbequing 365
|
367 |
+
news anchoring 366
|
368 |
+
smoking hookah 367
|
369 |
+
cooking egg 368
|
370 |
+
peeling apples 369
|
371 |
+
yoga 370
|
372 |
+
sharpening pencil 371
|
373 |
+
dribbling basketball 372
|
374 |
+
petting cat 373
|
375 |
+
playing ice hockey 374
|
376 |
+
milking cow 375
|
377 |
+
shining shoes 376
|
378 |
+
juggling soccer ball 377
|
379 |
+
scuba diving 378
|
380 |
+
playing squash or racquetball 379
|
381 |
+
drinking beer 380
|
382 |
+
sign language interpreting 381
|
383 |
+
playing basketball 382
|
384 |
+
breakdancing 383
|
385 |
+
testifying 384
|
386 |
+
making snowman 385
|
387 |
+
golf putting 386
|
388 |
+
playing didgeridoo 387
|
389 |
+
biking through snow 388
|
390 |
+
sailing 389
|
391 |
+
jumpstyle dancing 390
|
392 |
+
water sliding 391
|
393 |
+
grooming horse 392
|
394 |
+
massaging feet 393
|
395 |
+
playing paintball 394
|
396 |
+
making a cake 395
|
397 |
+
bowling 396
|
398 |
+
contact juggling 397
|
399 |
+
applying cream 398
|
400 |
+
playing badminton 399
|
VBench/pretrained/umt_model/model_path.txt
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
wget https://pjlab-gvm-data.oss-cn-shanghai.aliyuncs.com/umt/single_modality/l16_ptk710_ftk710_ftk400_f16_res224.pth -P ~/.cache/vbench/umt_model/
|
VBench/pretrained/viclip_model/model_path.txt
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
wget https://pjlab-gvm-data.oss-cn-shanghai.aliyuncs.com/internvideo/viclip/ViClip-InternVid-10M-FLT.pth -P ~/.cache/vbench/ViCLIP
|
VBench/prompts/README.md
ADDED
@@ -0,0 +1,95 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# :bookmark_tabs: Prompt Suite
|
2 |
+
|
3 |
+
We design compact yet representative prompts in terms of both the evaluation dimensions and the content categories.
|
4 |
+
|
5 |
+
|
6 |
+
## Prompts per Dimension
|
7 |
+
`prompts/prompts_per_dimension`: For each VBench evaluation dimension, we carefully designed a set of around 100 prompts as the test cases.
|
8 |
+
We provide a combined list `prompts/all_dimension.txt`, which combines all the prompts under `prompts/prompts_per_dimension`.
|
9 |
+
|
10 |
+
## Prompts per Category
|
11 |
+
`prompts/prompts_per_category`: 100 prompts for each of the 8 content categories: `Animal`, `Architecture`, `Food`, `Human`, `Lifestyle`, `Plant`, `Scenery`, `Vehicles`.
|
12 |
+
We provide a combined list `prompts/all_category.txt`, which combines all the prompts under `prompts/prompts_per_category`.
|
13 |
+
|
14 |
+
## Metadata
|
15 |
+
`prompts/metadata`: metadata for some prompt lists, such as the `color` and `object_class` labels for prompts that need to be semantically parsed.
|
16 |
+
|
17 |
+
|
18 |
+
# How to Sample Videos for Evaluation
|
19 |
+
|
20 |
+
We specify how to sample from `Prompts per Category` for VBench evaluation, and that for `Prompts per Category` can be carried out similarly.
|
21 |
+
|
22 |
+
|
23 |
+
## Evaluate Some Dimensions
|
24 |
+
|
25 |
+
### Pseudo-Code for Sampling
|
26 |
+
- If you only want to evaluate certain dimensions, below are the pseudo-code for sampling.
|
27 |
+
```
|
28 |
+
dimension_list = ['object_class', 'overall_consistency']
|
29 |
+
|
30 |
+
for dimension in dimension_list:
|
31 |
+
|
32 |
+
# set random seed
|
33 |
+
if args.seed:
|
34 |
+
torch.manual_seed(args.seed)
|
35 |
+
|
36 |
+
# read prompt list
|
37 |
+
with open(f'./prompts/prompts_per_dimension/{dimension}.txt', 'r') as f:
|
38 |
+
prompt_list = f.readlines()
|
39 |
+
prompt_list = [prompt.strip() for prompt in prompt_list]
|
40 |
+
|
41 |
+
for prompt in prompt_list:
|
42 |
+
|
43 |
+
# sample 5 videos for each prompt
|
44 |
+
for index in range(5):
|
45 |
+
|
46 |
+
# perform sampling
|
47 |
+
video = sample_func(prompt, index)
|
48 |
+
cur_save_path = f'{args.save_path}/{prompt}-{index}.mp4'
|
49 |
+
torchvision.io.write_video(cur_save_path, video, fps=8)
|
50 |
+
```
|
51 |
+
|
52 |
+
### Further Explanations
|
53 |
+
|
54 |
+
To sample videos for VBench evaluation:
|
55 |
+
- Sample videos from all the `txt` files in `prompts/prompts_per_dimension`.
|
56 |
+
- For each prompt, sample 5 videos.
|
57 |
+
- **Random Seed**: At the beginning of sampling from each `txt` file, set the random seed. For some models, the random seed is independently and randomly drawn for each video sample, and this is also acceptable, but it would be the best to record the random seed of every video being sampled. We need to ensure: (1) The random seeds are random, and not cherry picked. (2) The sampling process is reproducible, so that the evaluation results are reproducible.
|
58 |
+
- Name the videos in the form of `$prompt-$index.mp4`, `$index` takes value of `0, 1, 2, 3, 4`. For example:
|
59 |
+
```
|
60 |
+
├── A 3D model of a 1800s victorian house.-0.mp4
|
61 |
+
├── A 3D model of a 1800s victorian house.-1.mp4
|
62 |
+
├── A 3D model of a 1800s victorian house.-2.mp4
|
63 |
+
├── A 3D model of a 1800s victorian house.-3.mp4
|
64 |
+
├── A 3D model of a 1800s victorian house.-4.mp4
|
65 |
+
├── A beautiful coastal beach in spring, waves lapping on sand by Hokusai, in the style of Ukiyo-0.mp4
|
66 |
+
├── A beautiful coastal beach in spring, waves lapping on sand by Hokusai, in the style of Ukiyo-1.mp4
|
67 |
+
├── A beautiful coastal beach in spring, waves lapping on sand by Hokusai, in the style of Ukiyo-2.mp4
|
68 |
+
├── A beautiful coastal beach in spring, waves lapping on sand by Hokusai, in the style of Ukiyo-3.mp4
|
69 |
+
├── A beautiful coastal beach in spring, waves lapping on sand by Hokusai, in the style of Ukiyo-4.mp4
|
70 |
+
......
|
71 |
+
```
|
72 |
+
## Evaluate All Dimensions
|
73 |
+
|
74 |
+
- If you want to evaluate all the dimensions, below are the pseudo-code for sampling.
|
75 |
+
```
|
76 |
+
# set random seed
|
77 |
+
if args.seed:
|
78 |
+
torch.manual_seed(args.seed)
|
79 |
+
|
80 |
+
# read prompt list
|
81 |
+
with open(f'./prompts/all_dimension.txt', 'r') as f:
|
82 |
+
prompt_list = f.readlines()
|
83 |
+
prompt_list = [prompt.strip() for prompt in prompt_list]
|
84 |
+
|
85 |
+
for prompt in prompt_list:
|
86 |
+
|
87 |
+
# sample 5 videos for each prompt
|
88 |
+
for index in range(5):
|
89 |
+
|
90 |
+
# perform sampling
|
91 |
+
video = sample_func(prompt, index)
|
92 |
+
cur_save_path = f'{args.save_path}/{prompt}-{index}.mp4'
|
93 |
+
torchvision.io.write_video(cur_save_path, video, fps=8)
|
94 |
+
```
|
95 |
+
|
VBench/prompts/all_category.txt
ADDED
@@ -0,0 +1,800 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
a black dog wearing halloween costume
|
2 |
+
spider making a web
|
3 |
+
bat eating fruits while hanging
|
4 |
+
a snake crawling on a wooden flooring
|
5 |
+
a close up video of a dragonfly
|
6 |
+
macro shot of ladybug on green leaf plant
|
7 |
+
chameleon eating ant
|
8 |
+
a bee feeding on nectars
|
9 |
+
bird nests on a tree captured with moving camera
|
10 |
+
a squirrel eating nuts
|
11 |
+
close up video of snail
|
12 |
+
top view of a hermit crab crawling on a wooden surface
|
13 |
+
cat licking another cat
|
14 |
+
red dragonfly perched on green leaf
|
15 |
+
close up view of a brown caterpillar crawling on green leaf
|
16 |
+
ants eating dead spider
|
17 |
+
an eagle on a tree branch
|
18 |
+
a frog eating an ant
|
19 |
+
white rabbit near the fence
|
20 |
+
a gorilla eating a carrot
|
21 |
+
close up of wolf
|
22 |
+
a meerkat looking around
|
23 |
+
a hyena in a zoo
|
24 |
+
lemur eating grass leaves
|
25 |
+
an owl being trained by a man
|
26 |
+
a lizard on a bamboo
|
27 |
+
brown chicken hunting for its food
|
28 |
+
video of parrots perched on bird stand
|
29 |
+
underwater footage of an octopus in a coral reef
|
30 |
+
a cute pomeranian dog playing with a soccer ball
|
31 |
+
white fox on rock
|
32 |
+
close up footage of a horse figurine
|
33 |
+
giraffe feeding on a tree in a savannah
|
34 |
+
curious cat sitting and looking around
|
35 |
+
hummingbird hawk moth flying near pink flowers
|
36 |
+
close up of a scorpion on a rock
|
37 |
+
close up on fish in net
|
38 |
+
koala eating leaves from a branch
|
39 |
+
a pod of dolphins swirling in the sea catching forage fish
|
40 |
+
low angle view of a hawk perched on a tree branch
|
41 |
+
a lion standing on wild grass
|
42 |
+
deer grazing in the field
|
43 |
+
elephant herd in a savanna
|
44 |
+
close up on lobster under water
|
45 |
+
hedgehog crossing road in forest
|
46 |
+
a sheep eating yellow flowers from behind a wire fence
|
47 |
+
twin sisters and a turtle
|
48 |
+
a pig wallowing in mud
|
49 |
+
flock of goose eating on the lake water
|
50 |
+
cow in a field irritated with flies
|
51 |
+
a close up shot of a fly
|
52 |
+
cheetah lying on the grass
|
53 |
+
close up of a lemur
|
54 |
+
close up shot of a kangaroo itching in the sand
|
55 |
+
a tortoise covered with algae
|
56 |
+
turkey in cage
|
57 |
+
a great blue heron bird in the lakeside
|
58 |
+
crab with shell in aquarium
|
59 |
+
a seagull walking on shore
|
60 |
+
an american crocodile
|
61 |
+
a tiger walking inside a cage
|
62 |
+
alligator in the nature
|
63 |
+
a raccoon climbing a tree
|
64 |
+
wild rabbit in a green meadow
|
65 |
+
group of ring tailed lemurs
|
66 |
+
a clouded leopard on a tree branch
|
67 |
+
duck grooming its feathers
|
68 |
+
an african penguin walking on a beach
|
69 |
+
a video of a peacock
|
70 |
+
close up shot of a wild bear
|
71 |
+
baby rhino plays with mom
|
72 |
+
porcupine climbs tree branches
|
73 |
+
close up of a natterjack toad on a rock
|
74 |
+
a sleeping orangutan
|
75 |
+
mother whale swimming with babies
|
76 |
+
a bear wearing red jersey
|
77 |
+
pink jellyfish swimming underwater in a blue sea
|
78 |
+
beautiful clown fish swimming
|
79 |
+
animation of disposable objects shaped as a whale
|
80 |
+
paper cut out of a pair of hands a whale and a heart
|
81 |
+
vertical video of camel roaming in the field during daytime
|
82 |
+
a still video of mosquito biting human
|
83 |
+
a curious sloth hanging from a tree branch
|
84 |
+
a plastic flamingo bird stumbles from the wind
|
85 |
+
a wolf in its natural habitat
|
86 |
+
a monkey sitting in the stone and scratching his head
|
87 |
+
bat hanging upside down
|
88 |
+
a red panda eating leaves
|
89 |
+
snake on ground
|
90 |
+
a harbour seal swimming near the shore
|
91 |
+
shark swimming in the sea
|
92 |
+
otter on branch while eating
|
93 |
+
goat standing over a rock
|
94 |
+
a troop of monkey on top of a mountain
|
95 |
+
a zebra eating grass on the field
|
96 |
+
a colorful butterfly perching on a bud
|
97 |
+
a snail crawling on a leaf
|
98 |
+
zookeeper showering a baby elephant
|
99 |
+
a beetle emerging from the sand
|
100 |
+
a nine banded armadillo searching for food
|
101 |
+
an apartment building with balcony
|
102 |
+
asian garden and medieval castle
|
103 |
+
illuminated tower in berlin
|
104 |
+
a wooden house overseeing the lake
|
105 |
+
a crowd of people in a plaza in front of a government building
|
106 |
+
a church interior
|
107 |
+
jewish friends posing with hanukkah menorah in a cabin house
|
108 |
+
a destroyed building after a missile attack in ukraine
|
109 |
+
abandoned building in the woods
|
110 |
+
drone video of an abandoned school building in pripyat ukraine
|
111 |
+
elegant university building
|
112 |
+
architecture and designs of buildings in central london
|
113 |
+
a pancake tower with chocolate syrup and strawberries on top
|
114 |
+
an ancient white building
|
115 |
+
friends hanging out at a coffee house
|
116 |
+
house front door with christmas decorations
|
117 |
+
city night dark building
|
118 |
+
a bird house hanging on a tree branch
|
119 |
+
sacred sculpture in a temple
|
120 |
+
high angle shot of a clock tower
|
121 |
+
modern wooden house interior
|
122 |
+
the interior of an abandoned building
|
123 |
+
opera house overlooking sea
|
124 |
+
a concrete structure near the green trees
|
125 |
+
dome like building in scotland
|
126 |
+
low angle shot of a building
|
127 |
+
tower on hill
|
128 |
+
a miniature house
|
129 |
+
eiffel tower from the seine river
|
130 |
+
low angle footage of an apartment building
|
131 |
+
island with pier and antique building
|
132 |
+
asian historic architecture
|
133 |
+
drone footage of a beautiful mansion
|
134 |
+
mosque in the middle east
|
135 |
+
building a tent and hammock in the forest camping site
|
136 |
+
top view of a high rise building
|
137 |
+
house covered in snow
|
138 |
+
skyscraper at night
|
139 |
+
house in village
|
140 |
+
a casino with people outside the building
|
141 |
+
silhouette of a building
|
142 |
+
a woman climbing a tree house
|
143 |
+
drone view of house near lake during golden hour
|
144 |
+
an under construction concrete house
|
145 |
+
a watch tower by the sea
|
146 |
+
exterior view of arabic style building
|
147 |
+
video of a hotel building
|
148 |
+
red paper lantern decorations hanging outside a building
|
149 |
+
house on seashore
|
150 |
+
aerial footage of the palace of culture and science building in warsaw poland
|
151 |
+
aerial video of stuttgart tv tower in germany
|
152 |
+
aerial view of the highway and building in a city
|
153 |
+
drone shot of a skyscraper san francisco california usa
|
154 |
+
waterfall and house
|
155 |
+
view of the sky through a building
|
156 |
+
drone footage of a house on top of the mountain
|
157 |
+
abandoned house in the nature
|
158 |
+
clouds hovering over a mansion
|
159 |
+
light house on the ocean
|
160 |
+
buddhist temple at sunrise
|
161 |
+
people walking by a graveyard near a mosque at sunset
|
162 |
+
view of lifeguard tower on the beach
|
163 |
+
scenic view of a house in the mountains
|
164 |
+
the landscape in front of a government building
|
165 |
+
aerial footage of a building and its surrounding landscape in winter
|
166 |
+
time lapse of a cloudy sky behind a transmission tower
|
167 |
+
blue ocean near the brown castle
|
168 |
+
fog over temple
|
169 |
+
house in countryside top view
|
170 |
+
building under construction
|
171 |
+
turkish flag waving on old tower
|
172 |
+
the georgian building
|
173 |
+
close up shot of a steel structure
|
174 |
+
the atrium and interior design of a multi floor building
|
175 |
+
city view reflected on a glass building
|
176 |
+
aerial view of a luxurious house with pool
|
177 |
+
an unpaved road leading to the house
|
178 |
+
drone footage of a lookout tower in mountain landscape
|
179 |
+
wind turbines on hill behind building
|
180 |
+
time lapse footage of the sun light in front of a small house porch
|
181 |
+
a building built with lots of stairways
|
182 |
+
overcast over house on seashore
|
183 |
+
the view of the sydney opera house from the other side of the harbor
|
184 |
+
candle on a jar and a house figurine on a surface
|
185 |
+
video of a farm and house
|
186 |
+
a dilapidated building made of bricks
|
187 |
+
a view of a unique building from a moving vehicle
|
188 |
+
aerial footage of a tall building in cambodia
|
189 |
+
push in shot of a huge house
|
190 |
+
a beach house built over a seawall protected from the sea waves
|
191 |
+
exotic house surrounded by trees
|
192 |
+
drone video of a house surrounded by tropical vegetation
|
193 |
+
drone footage of a building beside a pond
|
194 |
+
observation tower on hill in forest
|
195 |
+
a tree house in the woods
|
196 |
+
a video of vessel structure during daytime
|
197 |
+
fire in front of illuminated building at night
|
198 |
+
a footage of a wooden house on a wheat field
|
199 |
+
tilt shot of a solar panel below a light tower
|
200 |
+
water tower on the desert
|
201 |
+
freshly baked finger looking cookies
|
202 |
+
video of fake blood in wine glass
|
203 |
+
halloween food art
|
204 |
+
a person slicing a vegetable
|
205 |
+
a serving of pumpkin dish in a plate
|
206 |
+
close up view of green leafy vegetable
|
207 |
+
a birthday cake in the plate
|
208 |
+
video of a slice papaya fruit
|
209 |
+
a muffin with a burning candle and a love sign by a ceramic mug
|
210 |
+
a jack o lantern designed cookie
|
211 |
+
baked bread with chocolate
|
212 |
+
a broccoli soup on wooden table
|
213 |
+
a freshly brewed coffee on a pink mug
|
214 |
+
grabbing sourdough neapolitan style pizza slices
|
215 |
+
person cooking mushrooms in frying pan
|
216 |
+
rice grains placed on a reusable cloth bag
|
217 |
+
slices of kiwi fruit
|
218 |
+
grilling a steak on a pan grill
|
219 |
+
close up of bread popping out of a toaster
|
220 |
+
man eating noodle
|
221 |
+
preparing a cocktail drink
|
222 |
+
close up pasta with bacon on plate
|
223 |
+
milk and cinnamon rolls
|
224 |
+
boy getting a dumpling using chopsticks
|
225 |
+
a mother preparing food with her kids
|
226 |
+
man using his phone while eating
|
227 |
+
fresh salmon salad on a plate
|
228 |
+
cutting cucumbers into long thin slices as ingredient for sushi roll
|
229 |
+
a steaming cup of tea by the window
|
230 |
+
a glass filled with beer
|
231 |
+
a kid eating popcorn while watching tv
|
232 |
+
close up shot of fried fish on the plate
|
233 |
+
a man eating a donut
|
234 |
+
person making a vegetarian dish
|
235 |
+
spreading cheese on bagel
|
236 |
+
close up view of a man drinking red wine
|
237 |
+
a couple having breakfast in a restaurant
|
238 |
+
a student eating her sandwich
|
239 |
+
girl peeling a banana
|
240 |
+
red rice in a small bowl
|
241 |
+
pancake with blueberry on the top
|
242 |
+
green apple fruit on white wooden table
|
243 |
+
a man eating a taco by the bar
|
244 |
+
making of a burrito
|
245 |
+
squeezing lemon into salad
|
246 |
+
a chef cutting sushi rolls
|
247 |
+
video of a delicious dessert
|
248 |
+
deep frying a crab on a wok in high fire
|
249 |
+
close up video of a orange juice
|
250 |
+
video of a cooked chicken breast
|
251 |
+
woman holding a pineapple
|
252 |
+
a woman eating a bar of chocolate
|
253 |
+
decorating christmas cookie
|
254 |
+
squeezing a slice of fruit
|
255 |
+
tuna sashimi on a plate
|
256 |
+
a strawberry fruit mixed in an alcoholic drink
|
257 |
+
preparing hot dogs in a grill
|
258 |
+
a woman cutting a tomato
|
259 |
+
an orange fruit cut in half
|
260 |
+
a coconut fruit with drinking straw
|
261 |
+
woman holding a dragon fruit
|
262 |
+
a woman pouring hot beverage on a cup
|
263 |
+
waffles with whipped cream and fruit
|
264 |
+
focus shot of an insect at the bottom of a fruit
|
265 |
+
preparing a healthy broccoli dish
|
266 |
+
man eating snack at picnic
|
267 |
+
close up video of a grilled shrimp skewer
|
268 |
+
a woman mixing a smoothie drinks
|
269 |
+
close up video of woman having a bite of jelly
|
270 |
+
businessman drinking whiskey at the bar counter of a hotel lounge
|
271 |
+
cutting an onion with a knife over a wooden chopping board
|
272 |
+
fresh lemonade in bottles
|
273 |
+
grilling a meat on a charcoal grill
|
274 |
+
people enjoying asian cuisine
|
275 |
+
close up footage of a hot dish on a clay pot
|
276 |
+
pork ribs dish
|
277 |
+
waffle with strawberry and syrup for breakfast
|
278 |
+
tofu dish with rose garnish
|
279 |
+
uncooked pork meat
|
280 |
+
egg yolk being dumped over gourmet dish
|
281 |
+
tasty brunch dish close up
|
282 |
+
little boy pretending to eat the watermelon
|
283 |
+
slicing roasted beef
|
284 |
+
close up of a chef adding teriyaki sauce to a dish
|
285 |
+
flat lay mexican dish
|
286 |
+
a person placing an octopus dish on a marble surface
|
287 |
+
close up of tea leaves brewing in a glass kettle
|
288 |
+
adding fresh herbs to soup dish
|
289 |
+
a scoop of roasted coffee beans
|
290 |
+
fresh dim sum set up on a bamboo steam tray for cooking
|
291 |
+
a girl putting ketchup on food at the kitchen
|
292 |
+
cooking on electric stove
|
293 |
+
a woman with a slice of a pie
|
294 |
+
grapes and wine on a wooden board
|
295 |
+
man taking picture of his food
|
296 |
+
hamburger and fries on restaurant table
|
297 |
+
close up video of japanese food
|
298 |
+
a cracker sandwich with cheese filling for snack
|
299 |
+
barista preparing matcha tea
|
300 |
+
close up of onion rings being deep fried
|
301 |
+
people carving a pumpkin
|
302 |
+
people sitting on a sofa
|
303 |
+
a man with a muertos face painting
|
304 |
+
man walking in the dark
|
305 |
+
men in front of their computer editing photos
|
306 |
+
men loading christmas tree on tow truck
|
307 |
+
woman washing the dishes
|
308 |
+
woman adding honey to the cinnamon rolls
|
309 |
+
two women kissing and smiling
|
310 |
+
three women looking at watercolor paintings
|
311 |
+
a family wearing paper bag masks
|
312 |
+
a family posing for the camera
|
313 |
+
a boy covering a rose flower with a dome glass
|
314 |
+
boy sitting on grass petting a dog
|
315 |
+
a girl in her tennis sportswear
|
316 |
+
a girl coloring the cardboard
|
317 |
+
silhouette of the couple during sunset
|
318 |
+
couple dancing with body paint
|
319 |
+
a child playing with water
|
320 |
+
a woman with her child sitting on a couch in the living room
|
321 |
+
a group of friend place doing hand gestures of agreement
|
322 |
+
friends having a group selfie
|
323 |
+
friends talking while on the basketball court
|
324 |
+
group of people protesting
|
325 |
+
a group of campers with a cute dog
|
326 |
+
a group of photographers taking pictures at the north western gardens in llandudno north wales
|
327 |
+
a group of students laughing and talking
|
328 |
+
a group of martial artist warming up
|
329 |
+
a person playing golf
|
330 |
+
a person walking on a wet wooden bridge
|
331 |
+
person doing a leg exercise
|
332 |
+
ice hockey athlete on rink
|
333 |
+
a young athlete training in swimming
|
334 |
+
chess player dusting a chessboard
|
335 |
+
baseball player holding his bat
|
336 |
+
a bearded man putting a vinyl record on a vinyl player
|
337 |
+
an orchestra finishes a performance
|
338 |
+
people applauding the performance of the kids
|
339 |
+
band performance at the recording studio
|
340 |
+
father and his children playing jenga game
|
341 |
+
people playing a board game
|
342 |
+
man playing a video game
|
343 |
+
a man video recording the movie in theater
|
344 |
+
man and a woman eating while watching a movie
|
345 |
+
movie crew talking together
|
346 |
+
a director explaining the movie scene
|
347 |
+
man and woman listening to music on car
|
348 |
+
man playing music
|
349 |
+
couple dancing slow dance with sun glare
|
350 |
+
a ballerina practicing in the dance studio
|
351 |
+
father and son holding hands
|
352 |
+
father and daughter talking together
|
353 |
+
a mother and her kids engaged in a video call
|
354 |
+
mother and daughter reading a book together
|
355 |
+
a mother teaching her daughter playing a violin
|
356 |
+
kid in a halloween costume
|
357 |
+
a happy kid playing the ukulele
|
358 |
+
a chef slicing a cucumber
|
359 |
+
chef wearing his gloves properly
|
360 |
+
brother and sister using hammock
|
361 |
+
girl applying sunblock to her brother
|
362 |
+
a girl pushing the chair while her sister is on the chair
|
363 |
+
colleagues talking in office building
|
364 |
+
fighter practice kicking
|
365 |
+
a woman fighter in her cosplay costume
|
366 |
+
an engineer holding blueprints while talking with her colleague
|
367 |
+
a young woman looking at vr controllers with her friend
|
368 |
+
workmates teasing a colleague in the work
|
369 |
+
a male police officer talking on the radio
|
370 |
+
teacher holding a marker while talking
|
371 |
+
teacher writing on her notebook
|
372 |
+
a young student attending her online classes
|
373 |
+
a student showing his classmates his wand
|
374 |
+
a male vendor selling fruits
|
375 |
+
a shirtless male climber
|
376 |
+
a sound engineer listening to music
|
377 |
+
female talking to a psychiatrist in a therapy session
|
378 |
+
young female activist posing with flag
|
379 |
+
a man in a hoodie and woman with a red bandana talking to each other and smiling
|
380 |
+
a medium close up of women wearing kimonos
|
381 |
+
a male interviewer listening to a person talking
|
382 |
+
a social worker having a conversation with the foster parents
|
383 |
+
a farm worker harvesting onions
|
384 |
+
worker packing street food
|
385 |
+
worker and client at barber shop
|
386 |
+
elderly man lifting kettlebell
|
387 |
+
mom assisting son in riding a bicycle
|
388 |
+
dad watching her daughter eat
|
389 |
+
young guy with vr headset
|
390 |
+
pregnant woman exercising with trainer
|
391 |
+
a fortune teller talking to a client
|
392 |
+
wizard doing a ritual on a woman
|
393 |
+
a footage of an actor on a movie scene
|
394 |
+
a man holding a best actor trophy
|
395 |
+
a singer of a music band
|
396 |
+
a young singer performing on stage
|
397 |
+
young dancer practicing at home
|
398 |
+
seller showing room to a couple
|
399 |
+
cab driver talking to passenger
|
400 |
+
a policeman talking to the car driver
|
401 |
+
kids celebrating halloween at home
|
402 |
+
little boy helping mother in kitchen
|
403 |
+
video of a indoor green plant
|
404 |
+
a girl arranges a christmas garland hanging by the kitchen cabinet
|
405 |
+
candle burning in dark room
|
406 |
+
couple having fun and goofing around the bedroom
|
407 |
+
girls jumping up and down in the bedroom
|
408 |
+
woman and man in pajamas working from home
|
409 |
+
a muslim family sitting and talking in the living room
|
410 |
+
family enjoying snack time while sitting in the living room
|
411 |
+
woman holding an animal puppet and a little girl playing together at the living room
|
412 |
+
kids playing in the indoor tent
|
413 |
+
young people celebrating new year at the office
|
414 |
+
a woman writing on the sticky note in the office
|
415 |
+
a woman exercising at home over a yoga mat
|
416 |
+
girls preparing easter decorations at home
|
417 |
+
dog on floor in room
|
418 |
+
turning on a fluorescent light inside a room
|
419 |
+
colleagues talking to each other near the office windows
|
420 |
+
a woman recording herself while exercising at home
|
421 |
+
music room
|
422 |
+
different kind of tools kept in a utility room
|
423 |
+
sofa beds and other furniture
|
424 |
+
a girl finding her brother reading a book in the bedroom
|
425 |
+
an elegant ceramic plant pot and hanging plant on indoor
|
426 |
+
furniture inside a bedroom
|
427 |
+
interior design of the bar section
|
428 |
+
living room with party decoration
|
429 |
+
firewood burning in dark room
|
430 |
+
a young woman playing the ukulele at home
|
431 |
+
woman painting at home
|
432 |
+
a woman in a locker room
|
433 |
+
video of a bathroom interior
|
434 |
+
the interior design of a jewish synagogue
|
435 |
+
a woman in protective suit disinfecting the kitchen
|
436 |
+
modern minimalist home interior
|
437 |
+
modern interior design of a coffee shop
|
438 |
+
person arranging minimalist furniture
|
439 |
+
aerial shot of interior of the warehouse
|
440 |
+
a room of a manufacturing facility
|
441 |
+
interior of catholic
|
442 |
+
interior design of a restaurant
|
443 |
+
a female model in a changing room looking herself in mirror
|
444 |
+
men walking in the office hallway
|
445 |
+
people sitting in a conference room
|
446 |
+
the interior design of a shopping mall
|
447 |
+
chandeliers in room
|
448 |
+
lucerne railway station interior
|
449 |
+
a female fencer posing in a foggy room
|
450 |
+
a toolbox and a paint roller beside a huge package in a room
|
451 |
+
bedroom in hotel
|
452 |
+
a woman lying in the operating room
|
453 |
+
a chef holding and checking kitchen utensils
|
454 |
+
a couple singing in the shower room together
|
455 |
+
a woman cleaning mess in the living room
|
456 |
+
an empty meeting room with natural light
|
457 |
+
person dancing in a dark room
|
458 |
+
close up on blood in hospital room
|
459 |
+
a couple resting on their home floor
|
460 |
+
a young female staff at courier office
|
461 |
+
a man entering the gym locker room
|
462 |
+
a bored man sitting by the tv at home
|
463 |
+
woman dancing in indoor garden
|
464 |
+
rubble in the interior of an abandoned house
|
465 |
+
indoor farm in a greenhouse
|
466 |
+
man doing handstand in indoor garden
|
467 |
+
an abandoned indoor swimming pool
|
468 |
+
home decorations on top of a cabinet
|
469 |
+
graffiti art on the interior walls of an abandoned mansion
|
470 |
+
indoor wall climbing activity
|
471 |
+
sunlight inside a room
|
472 |
+
teenage girl roller skating at indoor rink
|
473 |
+
home deco with lighted
|
474 |
+
baby in the shower room
|
475 |
+
men enjoying office christmas party
|
476 |
+
a bedroom with a brick wall
|
477 |
+
actors prepping in the dressing room
|
478 |
+
kids playing at an indoor playground
|
479 |
+
a person sanitizing an office space using smoke machine
|
480 |
+
mother and daughter choosing clothes at home
|
481 |
+
a woman sitting by the indoor fire pit
|
482 |
+
man standing on the corner of the room while looking around
|
483 |
+
person assembling furniture
|
484 |
+
a family stacking cardboard boxes in a room
|
485 |
+
family having fun in the dining room
|
486 |
+
person disinfecting a room
|
487 |
+
a woman washing strawberries in the kitchen sink
|
488 |
+
modern office waiting room
|
489 |
+
close up view of a person slicing with a kitchen knife
|
490 |
+
boiling coffee on a stove in the kitchen
|
491 |
+
modern equipment used in a home studio
|
492 |
+
interior of a recording studio
|
493 |
+
people working in a call center office
|
494 |
+
band performing at a home concert
|
495 |
+
a group of people watching a concert in a room
|
496 |
+
people packing their furniture
|
497 |
+
young employees in office holding a certificate
|
498 |
+
a criminal inside a dark room handcuffed in a table
|
499 |
+
couple browsing and looking for furniture in the store
|
500 |
+
workspace at home
|
501 |
+
video of a indoor green plant
|
502 |
+
close up view of a plant
|
503 |
+
close up shot of a burning plant
|
504 |
+
plucking leaves from plant
|
505 |
+
a plant on gold pot with glass lid
|
506 |
+
a branch of a tree and a plant
|
507 |
+
a leafless tree
|
508 |
+
close up shot of fern leaf
|
509 |
+
close up video of strawberry plant
|
510 |
+
plant with blooming flowers
|
511 |
+
close up video of flower petals
|
512 |
+
watering yellow plant
|
513 |
+
beautiful flower decoration
|
514 |
+
cannabis flower in a jar
|
515 |
+
a footage of the tree leaves
|
516 |
+
a red leaf plant
|
517 |
+
close up view of a white christmas tree
|
518 |
+
snow pouring on a tree
|
519 |
+
close up shot of white flowers on the tree
|
520 |
+
leaves in the trees daytime
|
521 |
+
a dead tree lying on a grass field
|
522 |
+
tree branches in a flowing river
|
523 |
+
purple flowers with leaves
|
524 |
+
a coconut tree by the house
|
525 |
+
close up on flower in winter
|
526 |
+
bamboo leaves backlit by the sun
|
527 |
+
close up video of a wet flower
|
528 |
+
a man putting a flower in a box
|
529 |
+
dropping flower petals on a wooden bowl
|
530 |
+
a close up shot of gypsophila flower
|
531 |
+
variety of succulent plants on a garden
|
532 |
+
variety of trees and plants in a botanical garden
|
533 |
+
forest of deciduous trees
|
534 |
+
a stack of dried leaves burning in a forest
|
535 |
+
tall forest trees on a misty morning
|
536 |
+
close up view of dewdrops on a leaf
|
537 |
+
close up view of white petaled flower
|
538 |
+
removing a pineapple leaf
|
539 |
+
a dragonfly perched on a leaf
|
540 |
+
butterfly pollinating flower
|
541 |
+
person visiting and checking a corn plant
|
542 |
+
woman picking beans from a plant
|
543 |
+
woman plucking mint leaves
|
544 |
+
single tree in the middle of farmland
|
545 |
+
a plant on a soil
|
546 |
+
drone footage of a tree on farm field
|
547 |
+
a tractor harvesting lavender flower
|
548 |
+
people putting christmas ornaments on a christmas tree
|
549 |
+
jack o lantern hanging on a tree
|
550 |
+
tree with halloween decoration
|
551 |
+
flower field near the waterfall
|
552 |
+
truck carrying the tree logs
|
553 |
+
raindrops falling on leaves
|
554 |
+
shot of a palm tree swaying with the wind
|
555 |
+
squirrels on a tree branch
|
556 |
+
person holding a flower
|
557 |
+
a fallen tree trunk
|
558 |
+
tree with golden leaves
|
559 |
+
cherry tree
|
560 |
+
wind blows through leaves of the tree in autumn
|
561 |
+
a leaf on a glass
|
562 |
+
the long trunks of tall trees in the forest
|
563 |
+
trees in the forest during sunny day
|
564 |
+
close up video of tree bark
|
565 |
+
reflection of tree branches
|
566 |
+
trunks of many trees in the forest
|
567 |
+
tree leaves providing shades from the sun
|
568 |
+
leaves swaying in the wind
|
569 |
+
low angle shot of baobab tree
|
570 |
+
bare trees in forest
|
571 |
+
a plant surrounded by fallen leaves
|
572 |
+
a couple preparing food and pruning a plant
|
573 |
+
a man cutting a tree bark
|
574 |
+
oranges on a tree branch
|
575 |
+
plant connected on the stones
|
576 |
+
video of a sawmill machine cutting tree log
|
577 |
+
women drying flower petals
|
578 |
+
macro view of an agave plant
|
579 |
+
a video of a person tying a plant on a string
|
580 |
+
green moss in forest nature
|
581 |
+
coconut tree near sea under blue sky
|
582 |
+
the canopy of a coconut tree
|
583 |
+
a man leaning on a tree at the beach
|
584 |
+
a full grown plant on a pot
|
585 |
+
candle wax dripping on flower petals
|
586 |
+
close up of leaves in autumn
|
587 |
+
a woman opening a book with a flower inside
|
588 |
+
a man holding leaves looking at the camera
|
589 |
+
a shadow of a swaying plant
|
590 |
+
a tree and concrete structure under a blue and cloudy sky
|
591 |
+
trimming excess leaves on a potted plant
|
592 |
+
the changing color of the tree leaves during autumn season
|
593 |
+
a gooseberry tree swayed by the wind
|
594 |
+
forest trees and a medieval castle at sunset
|
595 |
+
woman cut down tree
|
596 |
+
an old oak tree in a park across the street from a hotel
|
597 |
+
wild flowers growing in a forest ground
|
598 |
+
a mossy fountain and green plants in a botanical garden
|
599 |
+
mansion with beautiful garden
|
600 |
+
ants on a dragon fruit flower
|
601 |
+
scenery of desert landscape
|
602 |
+
landscape agriculture farm tractor
|
603 |
+
burning slash piles in the forest
|
604 |
+
graveyard at sunset
|
605 |
+
view of a jack o lantern with pumpkins in a smoky garden
|
606 |
+
sun view through a spider web
|
607 |
+
view of the sea from an abandoned building
|
608 |
+
close up view of a full moon
|
609 |
+
close up view of lighted candles
|
610 |
+
close up view of swaying white flowers and leaves
|
611 |
+
scenery of a relaxing beach
|
612 |
+
selective focus video of grass during sunny day
|
613 |
+
aerial view of brown dry landscape
|
614 |
+
fireworks display in the sky at night
|
615 |
+
a bonfire near river
|
616 |
+
mountain view
|
617 |
+
waterfalls in between mountain
|
618 |
+
a picturesque view of nature
|
619 |
+
exotic view of a riverfront city
|
620 |
+
tall trees in the forest under the clear sky
|
621 |
+
snow on branches in forest
|
622 |
+
stream in the nature
|
623 |
+
an airplane flying above the sea of clouds
|
624 |
+
scenic video of sunset
|
625 |
+
view of houses with bush fence under a blue and cloudy sky
|
626 |
+
scenic view from wooden pathway
|
627 |
+
scenic view of a tropical beach
|
628 |
+
drone footage of waves crashing on beach shore
|
629 |
+
a scenic view of the golden hour at norway
|
630 |
+
time lapse video of foggy mountain forest
|
631 |
+
brown mountain during fall season
|
632 |
+
video of ocean during daytime
|
633 |
+
boat sailing in the ocean
|
634 |
+
top view of yachts
|
635 |
+
beautiful scenery of flowing waterfalls and river
|
636 |
+
wild ducks paddling on the lake surface
|
637 |
+
a relaxing scenery of beach view under cloudy sky
|
638 |
+
natural rock formations on beach under cloudy sky
|
639 |
+
a palm tree against blue sky
|
640 |
+
video of sailboat on a lake during sunset
|
641 |
+
aerial view of snow piles
|
642 |
+
time lapse of a sunset sky in the countryside
|
643 |
+
aerial footage of a statue
|
644 |
+
time lapse video of a farm during sunset
|
645 |
+
clouds formation in the sky at sunset
|
646 |
+
aerial shot of a village
|
647 |
+
drone shot of a beautiful sunrise at the mountains
|
648 |
+
time lapse video of foggy morning during sunrise
|
649 |
+
sun shining between tree leaves at sunrise
|
650 |
+
video of lake during dawn
|
651 |
+
vehicles traveling on roadway under cloudy sky
|
652 |
+
view of golden domed church
|
653 |
+
a monument under the blue sky
|
654 |
+
firecrackers in the sky
|
655 |
+
view of fruit signage in the farm
|
656 |
+
a dark clouds over shadowing the full moon
|
657 |
+
view of the amazon river
|
658 |
+
a big river swamp in a dense forest
|
659 |
+
a blooming cherry blossom tree under a blue sky with white clouds
|
660 |
+
a river waterfall cascading down the plunge basin
|
661 |
+
flooded landscape with palm trees
|
662 |
+
a blurry waterfall background
|
663 |
+
waterfall in the mountains
|
664 |
+
aerial footage of a city at night
|
665 |
+
pond by small waterfall in forest
|
666 |
+
aerial view of farmlands at the bay of lake
|
667 |
+
rice terraces in the countryside
|
668 |
+
a highway built across an agricultural area in the countryside
|
669 |
+
gloomy morning in the countryside
|
670 |
+
drone shot of an abandoned coliseum on a snowy mountain top
|
671 |
+
boat sailing in the middle of ocean
|
672 |
+
drone shot of the grass field
|
673 |
+
natural landscape of mountain and sea with islets developed into a community
|
674 |
+
aerial view of zaporizhia in ukraine
|
675 |
+
aerial footage of a herd
|
676 |
+
an aerial footage of a red sky
|
677 |
+
grass and plants growing in the remains of an abandoned house
|
678 |
+
view from hill on city
|
679 |
+
aerial view on orthodox church
|
680 |
+
aerial view of bay in croatia
|
681 |
+
a footage of a frozen river
|
682 |
+
overlooking view of a city at daylight
|
683 |
+
view outside the cemetery
|
684 |
+
clear sky with moon over meadow
|
685 |
+
clouds over railway
|
686 |
+
aerial footage of moving vehicles on the road at night
|
687 |
+
aerial view of town and park
|
688 |
+
top view of skyscrapers
|
689 |
+
top view of the empire state building in manhattan
|
690 |
+
top view of the central park in new york city
|
691 |
+
sheep running in a grass field
|
692 |
+
clear sky over factory
|
693 |
+
smoke and fire in birds eye view
|
694 |
+
view of a pathway with snow melting on its side
|
695 |
+
ferry under bridge on river near city in malaysia
|
696 |
+
mountain slopes covered in green vegetation
|
697 |
+
panoramic view of a town surrounded by snow covered mountains
|
698 |
+
aerial view of a palace
|
699 |
+
top view of vehicles driving on the intersection
|
700 |
+
a graveyard by a church in a mountain landscape
|
701 |
+
a modern railway station in malaysia use for public transportation
|
702 |
+
drone footage of amsterdam metro station
|
703 |
+
train arriving at a station
|
704 |
+
red vehicle driving on field
|
705 |
+
close up view of flashing emergency vehicle lighting
|
706 |
+
vehicle with fertilizer on field
|
707 |
+
a highway built across an agricultural area in the countryside
|
708 |
+
drone footage of motorcycles driving on country road between agricultural fields
|
709 |
+
a road in the woods under fog
|
710 |
+
footage of a car driving through a wheat field
|
711 |
+
vehicle stops for an ambulance passing through city traffic
|
712 |
+
emergency vehicle parked outside the casino
|
713 |
+
zombies attacking a woman and a boy inside a car
|
714 |
+
woman seating inside the car while chewing
|
715 |
+
video of passengers riding a double decker bus during night
|
716 |
+
traffic in london street at night
|
717 |
+
elderly couple checking engine of automobile
|
718 |
+
a green vintage automobile with an open hood parked in a parking area
|
719 |
+
close up of a prototype automobile with exposed engine on the back seat of the car
|
720 |
+
aerial view of road in forest
|
721 |
+
train departing from station
|
722 |
+
aerial view of a train passing by a bridge
|
723 |
+
video of a train tracks
|
724 |
+
video footage of a subway
|
725 |
+
video of blinking traffic lights
|
726 |
+
couple walking out on the subway
|
727 |
+
time lapse of a subway tunnel
|
728 |
+
monitor board inside the subway
|
729 |
+
metro train at night
|
730 |
+
zoom in video of a tram passing by city
|
731 |
+
young man using laptop in the tram
|
732 |
+
man reading a book at bus stop
|
733 |
+
close up shot of a moving taxi
|
734 |
+
night travel in london street on a public bus
|
735 |
+
red bus in a rainy city
|
736 |
+
flow of traffic in the city
|
737 |
+
close up shot of a yellow taxi turning left
|
738 |
+
two women calling for a taxi
|
739 |
+
drone view of an illuminated bridge across a river
|
740 |
+
policeman in police car talking on radio
|
741 |
+
airplane taking off at night
|
742 |
+
view through window in airplane
|
743 |
+
an airplane in the sky
|
744 |
+
helicopter landing on the street
|
745 |
+
a pilot getting out of a helicopter
|
746 |
+
a helicopter flying under blue sky
|
747 |
+
boat sailing in the middle of the ocean
|
748 |
+
girl playing with a toy boat
|
749 |
+
silhouette of a boat on sea during golden hour
|
750 |
+
a boat travelling around the lake
|
751 |
+
road on mountain ridge
|
752 |
+
ship sailing on danube river
|
753 |
+
slow motion video of a ship water trail in the sea
|
754 |
+
drone footage of a wreck ship on shore
|
755 |
+
a white yacht traveling on a river and passing under the bridge
|
756 |
+
female teenagers drinking champagne in the yacht
|
757 |
+
video of yacht sailing in the ocean
|
758 |
+
red combine harvester on road on field
|
759 |
+
a woman sitting on a bicycle while using a mobile phone
|
760 |
+
a woman sitting on a motorcycle looking around
|
761 |
+
three teenagers fixing a bicycle
|
762 |
+
a woman in a halloween costume posing on a motorcycle
|
763 |
+
a parked motorcycle on a foggy roadside
|
764 |
+
cable car near sea shore
|
765 |
+
a truck travelling in the road
|
766 |
+
footage of the road without any traffic
|
767 |
+
a road sign
|
768 |
+
love padlocks on a bridge
|
769 |
+
camera moving at highway construction site
|
770 |
+
vehicles driving on highway
|
771 |
+
a motorbike on highway at timelapse mode
|
772 |
+
point of view of a car driving through a tunnel
|
773 |
+
time lapse of heavy traffic on an avenue
|
774 |
+
ferry boat on city canal
|
775 |
+
black vintage car in museum
|
776 |
+
a zigzag road across a forest
|
777 |
+
people crossing the road
|
778 |
+
video of a kayak boat in a river
|
779 |
+
a person paddling a wooden boat in a lake
|
780 |
+
a car charging in the parking area
|
781 |
+
cars parked on the road
|
782 |
+
footage of the street with people and vehicle passing by in the rain
|
783 |
+
traffic on busy city street
|
784 |
+
a woman getting out of the car to walk with their dog
|
785 |
+
yacht sailing through the ocean
|
786 |
+
people in queue to military ship
|
787 |
+
man wearing motorcycle helmet looking at the camera
|
788 |
+
empty seats in the bus
|
789 |
+
empty boat on the water
|
790 |
+
cargo train traveling on the mountainside
|
791 |
+
cruise ship in harbor
|
792 |
+
counting down at traffic lights
|
793 |
+
pressing the car ignition
|
794 |
+
fire truck driving on the road
|
795 |
+
a footage of a broken bicycle
|
796 |
+
drone footage of an ambulance on the road
|
797 |
+
slow motion footage of a racing car
|
798 |
+
ship sailing on sea against sunset
|
799 |
+
big cargo ship passing on the shore
|
800 |
+
back view of man and woman walking on unpaved road
|
VBench/prompts/all_dimension.txt
ADDED
@@ -0,0 +1,946 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
In a still frame, a stop sign
|
2 |
+
a toilet, frozen in time
|
3 |
+
a laptop, frozen in time
|
4 |
+
A tranquil tableau of alley
|
5 |
+
A tranquil tableau of bar
|
6 |
+
A tranquil tableau of barn
|
7 |
+
A tranquil tableau of bathroom
|
8 |
+
A tranquil tableau of bedroom
|
9 |
+
A tranquil tableau of cliff
|
10 |
+
In a still frame, courtyard
|
11 |
+
In a still frame, gas station
|
12 |
+
A tranquil tableau of house
|
13 |
+
indoor gymnasium, frozen in time
|
14 |
+
A tranquil tableau of indoor library
|
15 |
+
A tranquil tableau of kitchen
|
16 |
+
A tranquil tableau of palace
|
17 |
+
In a still frame, parking lot
|
18 |
+
In a still frame, phone booth
|
19 |
+
A tranquil tableau of restaurant
|
20 |
+
A tranquil tableau of tower
|
21 |
+
A tranquil tableau of a bowl
|
22 |
+
A tranquil tableau of an apple
|
23 |
+
A tranquil tableau of a bench
|
24 |
+
A tranquil tableau of a bed
|
25 |
+
A tranquil tableau of a chair
|
26 |
+
A tranquil tableau of a cup
|
27 |
+
A tranquil tableau of a dining table
|
28 |
+
In a still frame, a pear
|
29 |
+
A tranquil tableau of a bunch of grapes
|
30 |
+
A tranquil tableau of a bowl on the kitchen counter
|
31 |
+
A tranquil tableau of a beautiful, handcrafted ceramic bowl
|
32 |
+
A tranquil tableau of an antique bowl
|
33 |
+
A tranquil tableau of an exquisite mahogany dining table
|
34 |
+
A tranquil tableau of a wooden bench in the park
|
35 |
+
A tranquil tableau of a beautiful wrought-iron bench surrounded by blooming flowers
|
36 |
+
In a still frame, a park bench with a view of the lake
|
37 |
+
A tranquil tableau of a vintage rocking chair was placed on the porch
|
38 |
+
A tranquil tableau of the jail cell was small and dimly lit, with cold, steel bars
|
39 |
+
A tranquil tableau of the phone booth was tucked away in a quiet alley
|
40 |
+
a dilapidated phone booth stood as a relic of a bygone era on the sidewalk, frozen in time
|
41 |
+
A tranquil tableau of the old red barn stood weathered and iconic against the backdrop of the countryside
|
42 |
+
A tranquil tableau of a picturesque barn was painted a warm shade of red and nestled in a picturesque meadow
|
43 |
+
In a still frame, within the desolate desert, an oasis unfolded, characterized by the stoic presence of palm trees and a motionless, glassy pool of water
|
44 |
+
In a still frame, the Parthenon's majestic Doric columns stand in serene solitude atop the Acropolis, framed by the tranquil Athenian landscape
|
45 |
+
In a still frame, the Temple of Hephaestus, with its timeless Doric grace, stands stoically against the backdrop of a quiet Athens
|
46 |
+
In a still frame, the ornate Victorian streetlamp stands solemnly, adorned with intricate ironwork and stained glass panels
|
47 |
+
A tranquil tableau of the Stonehenge presented itself as an enigmatic puzzle, each colossal stone meticulously placed against the backdrop of tranquility
|
48 |
+
In a still frame, in the vast desert, an oasis nestled among dunes, featuring tall palm trees and an air of serenity
|
49 |
+
static view on a desert scene with an oasis, palm trees, and a clear, calm pool of water
|
50 |
+
A tranquil tableau of an ornate Victorian streetlamp standing on a cobblestone street corner, illuminating the empty night
|
51 |
+
A tranquil tableau of a tranquil lakeside cabin nestled among tall pines, its reflection mirrored perfectly in the calm water
|
52 |
+
In a still frame, a vintage gas lantern, adorned with intricate details, gracing a historic cobblestone square
|
53 |
+
In a still frame, a tranquil Japanese tea ceremony room, with tatami mats, a delicate tea set, and a bonsai tree in the corner
|
54 |
+
A tranquil tableau of the Parthenon stands resolute in its classical elegance, a timeless symbol of Athens' cultural legacy
|
55 |
+
A tranquil tableau of in the heart of Plaka, the neoclassical architecture of the old city harmonizes with the ancient ruins
|
56 |
+
A tranquil tableau of in the desolate beauty of the American Southwest, Chaco Canyon's ancient ruins whispered tales of an enigmatic civilization that once thrived amidst the arid landscapes
|
57 |
+
A tranquil tableau of at the edge of the Arabian Desert, the ancient city of Petra beckoned with its enigmatic rock-carved façades
|
58 |
+
In a still frame, amidst the cobblestone streets, an Art Nouveau lamppost stood tall
|
59 |
+
A tranquil tableau of in the quaint village square, a traditional wrought-iron streetlamp featured delicate filigree patterns and amber-hued glass panels
|
60 |
+
A tranquil tableau of the lampposts were adorned with Art Deco motifs, their geometric shapes and frosted glass creating a sense of vintage glamour
|
61 |
+
In a still frame, in the picturesque square, a Gothic-style lamppost adorned with intricate stone carvings added a touch of medieval charm to the setting
|
62 |
+
In a still frame, in the heart of the old city, a row of ornate lantern-style streetlamps bathed the narrow alleyway in a warm, welcoming light
|
63 |
+
A tranquil tableau of in the heart of the Utah desert, a massive sandstone arch spanned the horizon
|
64 |
+
A tranquil tableau of in the Arizona desert, a massive stone bridge arched across a rugged canyon
|
65 |
+
A tranquil tableau of in the corner of the minimalist tea room, a bonsai tree added a touch of nature's beauty to the otherwise simple and elegant space
|
66 |
+
In a still frame, amidst the hushed ambiance of the traditional tea room, a meticulously arranged tea set awaited, with porcelain cups, a bamboo whisk
|
67 |
+
In a still frame, nestled in the Zen garden, a rustic teahouse featured tatami seating and a traditional charcoal brazier
|
68 |
+
A tranquil tableau of a country estate's library featured elegant wooden shelves
|
69 |
+
A tranquil tableau of beneath the shade of a solitary oak tree, an old wooden park bench sat patiently
|
70 |
+
A tranquil tableau of beside a tranquil pond, a weeping willow tree draped its branches gracefully over the water's surface, creating a serene tableau of reflection and calm
|
71 |
+
A tranquil tableau of in the Zen garden, a perfectly raked gravel path led to a serene rock garden
|
72 |
+
In a still frame, a tranquil pond was fringed by weeping cherry trees, their blossoms drifting lazily onto the glassy surface
|
73 |
+
In a still frame, within the historic library's reading room, rows of antique leather chairs and mahogany tables offered a serene haven for literary contemplation
|
74 |
+
A tranquil tableau of a peaceful orchid garden showcased a variety of delicate blooms
|
75 |
+
A tranquil tableau of in the serene courtyard, a centuries-old stone well stood as a symbol of a bygone era, its mossy stones bearing witness to the passage of time
|
76 |
+
a bird and a cat
|
77 |
+
a cat and a dog
|
78 |
+
a dog and a horse
|
79 |
+
a horse and a sheep
|
80 |
+
a sheep and a cow
|
81 |
+
a cow and an elephant
|
82 |
+
an elephant and a bear
|
83 |
+
a bear and a zebra
|
84 |
+
a zebra and a giraffe
|
85 |
+
a giraffe and a bird
|
86 |
+
a chair and a couch
|
87 |
+
a couch and a potted plant
|
88 |
+
a potted plant and a tv
|
89 |
+
a tv and a laptop
|
90 |
+
a laptop and a remote
|
91 |
+
a remote and a keyboard
|
92 |
+
a keyboard and a cell phone
|
93 |
+
a cell phone and a book
|
94 |
+
a book and a clock
|
95 |
+
a clock and a backpack
|
96 |
+
a backpack and an umbrella
|
97 |
+
an umbrella and a handbag
|
98 |
+
a handbag and a tie
|
99 |
+
a tie and a suitcase
|
100 |
+
a suitcase and a vase
|
101 |
+
a vase and scissors
|
102 |
+
scissors and a teddy bear
|
103 |
+
a teddy bear and a frisbee
|
104 |
+
a frisbee and skis
|
105 |
+
skis and a snowboard
|
106 |
+
a snowboard and a sports ball
|
107 |
+
a sports ball and a kite
|
108 |
+
a kite and a baseball bat
|
109 |
+
a baseball bat and a baseball glove
|
110 |
+
a baseball glove and a skateboard
|
111 |
+
a skateboard and a surfboard
|
112 |
+
a surfboard and a tennis racket
|
113 |
+
a tennis racket and a bottle
|
114 |
+
a bottle and a chair
|
115 |
+
an airplane and a train
|
116 |
+
a train and a boat
|
117 |
+
a boat and an airplane
|
118 |
+
a bicycle and a car
|
119 |
+
a car and a motorcycle
|
120 |
+
a motorcycle and a bus
|
121 |
+
a bus and a traffic light
|
122 |
+
a traffic light and a fire hydrant
|
123 |
+
a fire hydrant and a stop sign
|
124 |
+
a stop sign and a parking meter
|
125 |
+
a parking meter and a truck
|
126 |
+
a truck and a bicycle
|
127 |
+
a toilet and a hair drier
|
128 |
+
a hair drier and a toothbrush
|
129 |
+
a toothbrush and a sink
|
130 |
+
a sink and a toilet
|
131 |
+
a wine glass and a chair
|
132 |
+
a cup and a couch
|
133 |
+
a fork and a potted plant
|
134 |
+
a knife and a tv
|
135 |
+
a spoon and a laptop
|
136 |
+
a bowl and a remote
|
137 |
+
a banana and a keyboard
|
138 |
+
an apple and a cell phone
|
139 |
+
a sandwich and a book
|
140 |
+
an orange and a clock
|
141 |
+
broccoli and a backpack
|
142 |
+
a carrot and an umbrella
|
143 |
+
a hot dog and a handbag
|
144 |
+
a pizza and a tie
|
145 |
+
a donut and a suitcase
|
146 |
+
a cake and a vase
|
147 |
+
an oven and scissors
|
148 |
+
a toaster and a teddy bear
|
149 |
+
a microwave and a frisbee
|
150 |
+
a refrigerator and skis
|
151 |
+
a bicycle and an airplane
|
152 |
+
a car and a train
|
153 |
+
a motorcycle and a boat
|
154 |
+
a person and a toilet
|
155 |
+
a person and a hair drier
|
156 |
+
a person and a toothbrush
|
157 |
+
a person and a sink
|
158 |
+
A person is riding a bike
|
159 |
+
A person is marching
|
160 |
+
A person is roller skating
|
161 |
+
A person is tasting beer
|
162 |
+
A person is clapping
|
163 |
+
A person is drawing
|
164 |
+
A person is petting animal (not cat)
|
165 |
+
A person is eating watermelon
|
166 |
+
A person is playing harp
|
167 |
+
A person is wrestling
|
168 |
+
A person is riding scooter
|
169 |
+
A person is sweeping floor
|
170 |
+
A person is skateboarding
|
171 |
+
A person is dunking basketball
|
172 |
+
A person is playing flute
|
173 |
+
A person is stretching leg
|
174 |
+
A person is tying tie
|
175 |
+
A person is skydiving
|
176 |
+
A person is shooting goal (soccer)
|
177 |
+
A person is playing piano
|
178 |
+
A person is finger snapping
|
179 |
+
A person is canoeing or kayaking
|
180 |
+
A person is laughing
|
181 |
+
A person is digging
|
182 |
+
A person is clay pottery making
|
183 |
+
A person is shooting basketball
|
184 |
+
A person is bending back
|
185 |
+
A person is shaking hands
|
186 |
+
A person is bandaging
|
187 |
+
A person is push up
|
188 |
+
A person is catching or throwing frisbee
|
189 |
+
A person is playing trumpet
|
190 |
+
A person is flying kite
|
191 |
+
A person is filling eyebrows
|
192 |
+
A person is shuffling cards
|
193 |
+
A person is folding clothes
|
194 |
+
A person is smoking
|
195 |
+
A person is tai chi
|
196 |
+
A person is squat
|
197 |
+
A person is playing controller
|
198 |
+
A person is throwing axe
|
199 |
+
A person is giving or receiving award
|
200 |
+
A person is air drumming
|
201 |
+
A person is taking a shower
|
202 |
+
A person is planting trees
|
203 |
+
A person is sharpening knives
|
204 |
+
A person is robot dancing
|
205 |
+
A person is rock climbing
|
206 |
+
A person is hula hooping
|
207 |
+
A person is writing
|
208 |
+
A person is bungee jumping
|
209 |
+
A person is pushing cart
|
210 |
+
A person is cleaning windows
|
211 |
+
A person is cutting watermelon
|
212 |
+
A person is cheerleading
|
213 |
+
A person is washing hands
|
214 |
+
A person is ironing
|
215 |
+
A person is cutting nails
|
216 |
+
A person is hugging
|
217 |
+
A person is trimming or shaving beard
|
218 |
+
A person is jogging
|
219 |
+
A person is making bed
|
220 |
+
A person is washing dishes
|
221 |
+
A person is grooming dog
|
222 |
+
A person is doing laundry
|
223 |
+
A person is knitting
|
224 |
+
A person is reading book
|
225 |
+
A person is baby waking up
|
226 |
+
A person is massaging legs
|
227 |
+
A person is brushing teeth
|
228 |
+
A person is crawling baby
|
229 |
+
A person is motorcycling
|
230 |
+
A person is driving car
|
231 |
+
A person is sticking tongue out
|
232 |
+
A person is shaking head
|
233 |
+
A person is sword fighting
|
234 |
+
A person is doing aerobics
|
235 |
+
A person is strumming guitar
|
236 |
+
A person is riding or walking with horse
|
237 |
+
A person is archery
|
238 |
+
A person is catching or throwing baseball
|
239 |
+
A person is playing chess
|
240 |
+
A person is rock scissors paper
|
241 |
+
A person is using computer
|
242 |
+
A person is arranging flowers
|
243 |
+
A person is bending metal
|
244 |
+
A person is ice skating
|
245 |
+
A person is climbing a rope
|
246 |
+
A person is crying
|
247 |
+
A person is dancing ballet
|
248 |
+
A person is getting a haircut
|
249 |
+
A person is running on treadmill
|
250 |
+
A person is kissing
|
251 |
+
A person is counting money
|
252 |
+
A person is barbequing
|
253 |
+
A person is peeling apples
|
254 |
+
A person is milking cow
|
255 |
+
A person is shining shoes
|
256 |
+
A person is making snowman
|
257 |
+
A person is sailing
|
258 |
+
a person swimming in ocean
|
259 |
+
a person giving a presentation to a room full of colleagues
|
260 |
+
a person washing the dishes
|
261 |
+
a person eating a burger
|
262 |
+
a person walking in the snowstorm
|
263 |
+
a person drinking coffee in a cafe
|
264 |
+
a person playing guitar
|
265 |
+
a bicycle leaning against a tree
|
266 |
+
a bicycle gliding through a snowy field
|
267 |
+
a bicycle slowing down to stop
|
268 |
+
a bicycle accelerating to gain speed
|
269 |
+
a car stuck in traffic during rush hour
|
270 |
+
a car turning a corner
|
271 |
+
a car slowing down to stop
|
272 |
+
a car accelerating to gain speed
|
273 |
+
a motorcycle cruising along a coastal highway
|
274 |
+
a motorcycle turning a corner
|
275 |
+
a motorcycle slowing down to stop
|
276 |
+
a motorcycle gliding through a snowy field
|
277 |
+
a motorcycle accelerating to gain speed
|
278 |
+
an airplane soaring through a clear blue sky
|
279 |
+
an airplane taking off
|
280 |
+
an airplane landing smoothly on a runway
|
281 |
+
an airplane accelerating to gain speed
|
282 |
+
a bus turning a corner
|
283 |
+
a bus stuck in traffic during rush hour
|
284 |
+
a bus accelerating to gain speed
|
285 |
+
a train speeding down the tracks
|
286 |
+
a train crossing over a tall bridge
|
287 |
+
a train accelerating to gain speed
|
288 |
+
a truck turning a corner
|
289 |
+
a truck anchored in a tranquil bay
|
290 |
+
a truck stuck in traffic during rush hour
|
291 |
+
a truck slowing down to stop
|
292 |
+
a truck accelerating to gain speed
|
293 |
+
a boat sailing smoothly on a calm lake
|
294 |
+
a boat slowing down to stop
|
295 |
+
a boat accelerating to gain speed
|
296 |
+
a bird soaring gracefully in the sky
|
297 |
+
a bird building a nest from twigs and leaves
|
298 |
+
a bird flying over a snowy forest
|
299 |
+
a cat grooming itself meticulously with its tongue
|
300 |
+
a cat playing in park
|
301 |
+
a cat drinking water
|
302 |
+
a cat running happily
|
303 |
+
a dog enjoying a peaceful walk
|
304 |
+
a dog playing in park
|
305 |
+
a dog drinking water
|
306 |
+
a dog running happily
|
307 |
+
a horse bending down to drink water from a river
|
308 |
+
a horse galloping across an open field
|
309 |
+
a horse taking a peaceful walk
|
310 |
+
a horse running to join a herd of its kind
|
311 |
+
a sheep bending down to drink water from a river
|
312 |
+
a sheep taking a peaceful walk
|
313 |
+
a sheep running to join a herd of its kind
|
314 |
+
a cow bending down to drink water from a river
|
315 |
+
a cow chewing cud while resting in a tranquil barn
|
316 |
+
a cow running to join a herd of its kind
|
317 |
+
an elephant spraying itself with water using its trunk to cool down
|
318 |
+
an elephant taking a peaceful walk
|
319 |
+
an elephant running to join a herd of its kind
|
320 |
+
a bear catching a salmon in its powerful jaws
|
321 |
+
a bear sniffing the air for scents of food
|
322 |
+
a bear climbing a tree
|
323 |
+
a bear hunting for prey
|
324 |
+
a zebra bending down to drink water from a river
|
325 |
+
a zebra running to join a herd of its kind
|
326 |
+
a zebra taking a peaceful walk
|
327 |
+
a giraffe bending down to drink water from a river
|
328 |
+
a giraffe taking a peaceful walk
|
329 |
+
a giraffe running to join a herd of its kind
|
330 |
+
a person
|
331 |
+
a bicycle
|
332 |
+
a car
|
333 |
+
a motorcycle
|
334 |
+
an airplane
|
335 |
+
a bus
|
336 |
+
a train
|
337 |
+
a truck
|
338 |
+
a boat
|
339 |
+
a traffic light
|
340 |
+
a fire hydrant
|
341 |
+
a stop sign
|
342 |
+
a parking meter
|
343 |
+
a bench
|
344 |
+
a bird
|
345 |
+
a cat
|
346 |
+
a dog
|
347 |
+
a horse
|
348 |
+
a sheep
|
349 |
+
a cow
|
350 |
+
an elephant
|
351 |
+
a bear
|
352 |
+
a zebra
|
353 |
+
a giraffe
|
354 |
+
a backpack
|
355 |
+
an umbrella
|
356 |
+
a handbag
|
357 |
+
a tie
|
358 |
+
a suitcase
|
359 |
+
a frisbee
|
360 |
+
skis
|
361 |
+
a snowboard
|
362 |
+
a sports ball
|
363 |
+
a kite
|
364 |
+
a baseball bat
|
365 |
+
a baseball glove
|
366 |
+
a skateboard
|
367 |
+
a surfboard
|
368 |
+
a tennis racket
|
369 |
+
a bottle
|
370 |
+
a wine glass
|
371 |
+
a cup
|
372 |
+
a fork
|
373 |
+
a knife
|
374 |
+
a spoon
|
375 |
+
a bowl
|
376 |
+
a banana
|
377 |
+
an apple
|
378 |
+
a sandwich
|
379 |
+
an orange
|
380 |
+
broccoli
|
381 |
+
a carrot
|
382 |
+
a hot dog
|
383 |
+
a pizza
|
384 |
+
a donut
|
385 |
+
a cake
|
386 |
+
a chair
|
387 |
+
a couch
|
388 |
+
a potted plant
|
389 |
+
a bed
|
390 |
+
a dining table
|
391 |
+
a toilet
|
392 |
+
a tv
|
393 |
+
a laptop
|
394 |
+
a remote
|
395 |
+
a keyboard
|
396 |
+
a cell phone
|
397 |
+
a microwave
|
398 |
+
an oven
|
399 |
+
a toaster
|
400 |
+
a sink
|
401 |
+
a refrigerator
|
402 |
+
a book
|
403 |
+
a clock
|
404 |
+
a vase
|
405 |
+
scissors
|
406 |
+
a teddy bear
|
407 |
+
a hair drier
|
408 |
+
a toothbrush
|
409 |
+
a red bicycle
|
410 |
+
a green bicycle
|
411 |
+
a blue bicycle
|
412 |
+
a yellow bicycle
|
413 |
+
an orange bicycle
|
414 |
+
a purple bicycle
|
415 |
+
a pink bicycle
|
416 |
+
a black bicycle
|
417 |
+
a white bicycle
|
418 |
+
a red car
|
419 |
+
a green car
|
420 |
+
a blue car
|
421 |
+
a yellow car
|
422 |
+
an orange car
|
423 |
+
a purple car
|
424 |
+
a pink car
|
425 |
+
a black car
|
426 |
+
a white car
|
427 |
+
a red bird
|
428 |
+
a green bird
|
429 |
+
a blue bird
|
430 |
+
a yellow bird
|
431 |
+
an orange bird
|
432 |
+
a purple bird
|
433 |
+
a pink bird
|
434 |
+
a black bird
|
435 |
+
a white bird
|
436 |
+
a black cat
|
437 |
+
a white cat
|
438 |
+
an orange cat
|
439 |
+
a yellow cat
|
440 |
+
a red umbrella
|
441 |
+
a green umbrella
|
442 |
+
a blue umbrella
|
443 |
+
a yellow umbrella
|
444 |
+
an orange umbrella
|
445 |
+
a purple umbrella
|
446 |
+
a pink umbrella
|
447 |
+
a black umbrella
|
448 |
+
a white umbrella
|
449 |
+
a red suitcase
|
450 |
+
a green suitcase
|
451 |
+
a blue suitcase
|
452 |
+
a yellow suitcase
|
453 |
+
an orange suitcase
|
454 |
+
a purple suitcase
|
455 |
+
a pink suitcase
|
456 |
+
a black suitcase
|
457 |
+
a white suitcase
|
458 |
+
a red bowl
|
459 |
+
a green bowl
|
460 |
+
a blue bowl
|
461 |
+
a yellow bowl
|
462 |
+
an orange bowl
|
463 |
+
a purple bowl
|
464 |
+
a pink bowl
|
465 |
+
a black bowl
|
466 |
+
a white bowl
|
467 |
+
a red chair
|
468 |
+
a green chair
|
469 |
+
a blue chair
|
470 |
+
a yellow chair
|
471 |
+
an orange chair
|
472 |
+
a purple chair
|
473 |
+
a pink chair
|
474 |
+
a black chair
|
475 |
+
a white chair
|
476 |
+
a red clock
|
477 |
+
a green clock
|
478 |
+
a blue clock
|
479 |
+
a yellow clock
|
480 |
+
an orange clock
|
481 |
+
a purple clock
|
482 |
+
a pink clock
|
483 |
+
a black clock
|
484 |
+
a white clock
|
485 |
+
a red vase
|
486 |
+
a green vase
|
487 |
+
a blue vase
|
488 |
+
a yellow vase
|
489 |
+
an orange vase
|
490 |
+
a purple vase
|
491 |
+
a pink vase
|
492 |
+
a black vase
|
493 |
+
a white vase
|
494 |
+
A beautiful coastal beach in spring, waves lapping on sand, Van Gogh style
|
495 |
+
A beautiful coastal beach in spring, waves lapping on sand, oil painting
|
496 |
+
A beautiful coastal beach in spring, waves lapping on sand by Hokusai, in the style of Ukiyo
|
497 |
+
A beautiful coastal beach in spring, waves lapping on sand, black and white
|
498 |
+
A beautiful coastal beach in spring, waves lapping on sand, pixel art
|
499 |
+
A beautiful coastal beach in spring, waves lapping on sand, in cyberpunk style
|
500 |
+
A beautiful coastal beach in spring, waves lapping on sand, animated style
|
501 |
+
A beautiful coastal beach in spring, waves lapping on sand, watercolor painting
|
502 |
+
A beautiful coastal beach in spring, waves lapping on sand, surrealism style
|
503 |
+
The bund Shanghai, Van Gogh style
|
504 |
+
The bund Shanghai, oil painting
|
505 |
+
The bund Shanghai by Hokusai, in the style of Ukiyo
|
506 |
+
The bund Shanghai, black and white
|
507 |
+
The bund Shanghai, pixel art
|
508 |
+
The bund Shanghai, in cyberpunk style
|
509 |
+
The bund Shanghai, animated style
|
510 |
+
The bund Shanghai, watercolor painting
|
511 |
+
The bund Shanghai, surrealism style
|
512 |
+
a shark is swimming in the ocean, Van Gogh style
|
513 |
+
a shark is swimming in the ocean, oil painting
|
514 |
+
a shark is swimming in the ocean by Hokusai, in the style of Ukiyo
|
515 |
+
a shark is swimming in the ocean, black and white
|
516 |
+
a shark is swimming in the ocean, pixel art
|
517 |
+
a shark is swimming in the ocean, in cyberpunk style
|
518 |
+
a shark is swimming in the ocean, animated style
|
519 |
+
a shark is swimming in the ocean, watercolor painting
|
520 |
+
a shark is swimming in the ocean, surrealism style
|
521 |
+
A panda drinking coffee in a cafe in Paris, Van Gogh style
|
522 |
+
A panda drinking coffee in a cafe in Paris, oil painting
|
523 |
+
A panda drinking coffee in a cafe in Paris by Hokusai, in the style of Ukiyo
|
524 |
+
A panda drinking coffee in a cafe in Paris, black and white
|
525 |
+
A panda drinking coffee in a cafe in Paris, pixel art
|
526 |
+
A panda drinking coffee in a cafe in Paris, in cyberpunk style
|
527 |
+
A panda drinking coffee in a cafe in Paris, animated style
|
528 |
+
A panda drinking coffee in a cafe in Paris, watercolor painting
|
529 |
+
A panda drinking coffee in a cafe in Paris, surrealism style
|
530 |
+
A cute happy Corgi playing in park, sunset, Van Gogh style
|
531 |
+
A cute happy Corgi playing in park, sunset, oil painting
|
532 |
+
A cute happy Corgi playing in park, sunset by Hokusai, in the style of Ukiyo
|
533 |
+
A cute happy Corgi playing in park, sunset, black and white
|
534 |
+
A cute happy Corgi playing in park, sunset, pixel art
|
535 |
+
A cute happy Corgi playing in park, sunset, in cyberpunk style
|
536 |
+
A cute happy Corgi playing in park, sunset, animated style
|
537 |
+
A cute happy Corgi playing in park, sunset, watercolor painting
|
538 |
+
A cute happy Corgi playing in park, sunset, surrealism style
|
539 |
+
Gwen Stacy reading a book, Van Gogh style
|
540 |
+
Gwen Stacy reading a book, oil painting
|
541 |
+
Gwen Stacy reading a book by Hokusai, in the style of Ukiyo
|
542 |
+
Gwen Stacy reading a book, black and white
|
543 |
+
Gwen Stacy reading a book, pixel art
|
544 |
+
Gwen Stacy reading a book, in cyberpunk style
|
545 |
+
Gwen Stacy reading a book, animated style
|
546 |
+
Gwen Stacy reading a book, watercolor painting
|
547 |
+
Gwen Stacy reading a book, surrealism style
|
548 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, Van Gogh style
|
549 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, oil painting
|
550 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background by Hokusai, in the style of Ukiyo
|
551 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, black and white
|
552 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, pixel art
|
553 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, in cyberpunk style
|
554 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, animated style
|
555 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, watercolor painting
|
556 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, surrealism style
|
557 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, Van Gogh style
|
558 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, oil painting
|
559 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas by Hokusai, in the style of Ukiyo
|
560 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, black and white
|
561 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, pixel art
|
562 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, in cyberpunk style
|
563 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, animated style
|
564 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, watercolor painting
|
565 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, surrealism style
|
566 |
+
An astronaut flying in space, Van Gogh style
|
567 |
+
An astronaut flying in space, oil painting
|
568 |
+
An astronaut flying in space by Hokusai, in the style of Ukiyo
|
569 |
+
An astronaut flying in space, black and white
|
570 |
+
An astronaut flying in space, pixel art
|
571 |
+
An astronaut flying in space, in cyberpunk style
|
572 |
+
An astronaut flying in space, animated style
|
573 |
+
An astronaut flying in space, watercolor painting
|
574 |
+
An astronaut flying in space, surrealism style
|
575 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, Van Gogh style
|
576 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, oil painting
|
577 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks by Hokusai, in the style of Ukiyo
|
578 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, black and white
|
579 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, pixel art
|
580 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, in cyberpunk style
|
581 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, animated style
|
582 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, watercolor painting
|
583 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, surrealism style
|
584 |
+
A beautiful coastal beach in spring, waves lapping on sand, in super slow motion
|
585 |
+
A beautiful coastal beach in spring, waves lapping on sand, zoom in
|
586 |
+
A beautiful coastal beach in spring, waves lapping on sand, zoom out
|
587 |
+
A beautiful coastal beach in spring, waves lapping on sand, pan left
|
588 |
+
A beautiful coastal beach in spring, waves lapping on sand, pan right
|
589 |
+
A beautiful coastal beach in spring, waves lapping on sand, tilt up
|
590 |
+
A beautiful coastal beach in spring, waves lapping on sand, tilt down
|
591 |
+
A beautiful coastal beach in spring, waves lapping on sand, with an intense shaking effect
|
592 |
+
A beautiful coastal beach in spring, waves lapping on sand, featuring a steady and smooth perspective
|
593 |
+
A beautiful coastal beach in spring, waves lapping on sand, racking focus
|
594 |
+
The bund Shanghai, in super slow motion
|
595 |
+
The bund Shanghai, zoom in
|
596 |
+
The bund Shanghai, zoom out
|
597 |
+
The bund Shanghai, pan left
|
598 |
+
The bund Shanghai, pan right
|
599 |
+
The bund Shanghai, tilt up
|
600 |
+
The bund Shanghai, tilt down
|
601 |
+
The bund Shanghai, with an intense shaking effect
|
602 |
+
The bund Shanghai, featuring a steady and smooth perspective
|
603 |
+
The bund Shanghai, racking focus
|
604 |
+
a shark is swimming in the ocean, in super slow motion
|
605 |
+
a shark is swimming in the ocean, zoom in
|
606 |
+
a shark is swimming in the ocean, zoom out
|
607 |
+
a shark is swimming in the ocean, pan left
|
608 |
+
a shark is swimming in the ocean, pan right
|
609 |
+
a shark is swimming in the ocean, tilt up
|
610 |
+
a shark is swimming in the ocean, tilt down
|
611 |
+
a shark is swimming in the ocean, with an intense shaking effect
|
612 |
+
a shark is swimming in the ocean, featuring a steady and smooth perspective
|
613 |
+
a shark is swimming in the ocean, racking focus
|
614 |
+
A panda drinking coffee in a cafe in Paris, in super slow motion
|
615 |
+
A panda drinking coffee in a cafe in Paris, zoom in
|
616 |
+
A panda drinking coffee in a cafe in Paris, zoom out
|
617 |
+
A panda drinking coffee in a cafe in Paris, pan left
|
618 |
+
A panda drinking coffee in a cafe in Paris, pan right
|
619 |
+
A panda drinking coffee in a cafe in Paris, tilt up
|
620 |
+
A panda drinking coffee in a cafe in Paris, tilt down
|
621 |
+
A panda drinking coffee in a cafe in Paris, with an intense shaking effect
|
622 |
+
A panda drinking coffee in a cafe in Paris, featuring a steady and smooth perspective
|
623 |
+
A panda drinking coffee in a cafe in Paris, racking focus
|
624 |
+
A cute happy Corgi playing in park, sunset, in super slow motion
|
625 |
+
A cute happy Corgi playing in park, sunset, zoom in
|
626 |
+
A cute happy Corgi playing in park, sunset, zoom out
|
627 |
+
A cute happy Corgi playing in park, sunset, pan left
|
628 |
+
A cute happy Corgi playing in park, sunset, pan right
|
629 |
+
A cute happy Corgi playing in park, sunset, tilt up
|
630 |
+
A cute happy Corgi playing in park, sunset, tilt down
|
631 |
+
A cute happy Corgi playing in park, sunset, with an intense shaking effect
|
632 |
+
A cute happy Corgi playing in park, sunset, featuring a steady and smooth perspective
|
633 |
+
A cute happy Corgi playing in park, sunset, racking focus
|
634 |
+
Gwen Stacy reading a book, in super slow motion
|
635 |
+
Gwen Stacy reading a book, zoom in
|
636 |
+
Gwen Stacy reading a book, zoom out
|
637 |
+
Gwen Stacy reading a book, pan left
|
638 |
+
Gwen Stacy reading a book, pan right
|
639 |
+
Gwen Stacy reading a book, tilt up
|
640 |
+
Gwen Stacy reading a book, tilt down
|
641 |
+
Gwen Stacy reading a book, with an intense shaking effect
|
642 |
+
Gwen Stacy reading a book, featuring a steady and smooth perspective
|
643 |
+
Gwen Stacy reading a book, racking focus
|
644 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, in super slow motion
|
645 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, zoom in
|
646 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, zoom out
|
647 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, pan left
|
648 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, pan right
|
649 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, tilt up
|
650 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, tilt down
|
651 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, with an intense shaking effect
|
652 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, featuring a steady and smooth perspective
|
653 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, racking focus
|
654 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, in super slow motion
|
655 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, zoom in
|
656 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, zoom out
|
657 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, pan left
|
658 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, pan right
|
659 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, tilt up
|
660 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, tilt down
|
661 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, with an intense shaking effect
|
662 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, featuring a steady and smooth perspective
|
663 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, racking focus
|
664 |
+
An astronaut flying in space, in super slow motion
|
665 |
+
An astronaut flying in space, zoom in
|
666 |
+
An astronaut flying in space, zoom out
|
667 |
+
An astronaut flying in space, pan left
|
668 |
+
An astronaut flying in space, pan right
|
669 |
+
An astronaut flying in space, tilt up
|
670 |
+
An astronaut flying in space, tilt down
|
671 |
+
An astronaut flying in space, with an intense shaking effect
|
672 |
+
An astronaut flying in space, featuring a steady and smooth perspective
|
673 |
+
An astronaut flying in space, racking focus
|
674 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, in super slow motion
|
675 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, zoom in
|
676 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, zoom out
|
677 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, pan left
|
678 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, pan right
|
679 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, tilt up
|
680 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, tilt down
|
681 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, with an intense shaking effect
|
682 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, featuring a steady and smooth perspective
|
683 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, racking focus
|
684 |
+
Close up of grapes on a rotating table.
|
685 |
+
Turtle swimming in ocean.
|
686 |
+
A storm trooper vacuuming the beach.
|
687 |
+
A panda standing on a surfboard in the ocean in sunset.
|
688 |
+
An astronaut feeding ducks on a sunny afternoon, reflection from the water.
|
689 |
+
Two pandas discussing an academic paper.
|
690 |
+
Sunset time lapse at the beach with moving clouds and colors in the sky.
|
691 |
+
A fat rabbit wearing a purple robe walking through a fantasy landscape.
|
692 |
+
A koala bear playing piano in the forest.
|
693 |
+
An astronaut flying in space.
|
694 |
+
Fireworks.
|
695 |
+
An animated painting of fluffy white clouds moving in sky.
|
696 |
+
Flying through fantasy landscapes.
|
697 |
+
A bigfoot walking in the snowstorm.
|
698 |
+
A squirrel eating a burger.
|
699 |
+
A cat wearing sunglasses and working as a lifeguard at a pool.
|
700 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks.
|
701 |
+
Splash of turquoise water in extreme slow motion, alpha channel included.
|
702 |
+
an ice cream is melting on the table.
|
703 |
+
a drone flying over a snowy forest.
|
704 |
+
a shark is swimming in the ocean.
|
705 |
+
Aerial panoramic video from a drone of a fantasy land.
|
706 |
+
a teddy bear is swimming in the ocean.
|
707 |
+
time lapse of sunrise on mars.
|
708 |
+
golden fish swimming in the ocean.
|
709 |
+
An artist brush painting on a canvas close up.
|
710 |
+
A drone view of celebration with Christmas tree and fireworks, starry sky - background.
|
711 |
+
happy dog wearing a yellow turtleneck, studio, portrait, facing camera, dark background
|
712 |
+
Origami dancers in white paper, 3D render, on white background, studio shot, dancing modern dance.
|
713 |
+
Campfire at night in a snowy forest with starry sky in the background.
|
714 |
+
a fantasy landscape
|
715 |
+
A 3D model of a 1800s victorian house.
|
716 |
+
this is how I do makeup in the morning.
|
717 |
+
A raccoon that looks like a turtle, digital art.
|
718 |
+
Robot dancing in Times Square.
|
719 |
+
Busy freeway at night.
|
720 |
+
Balloon full of water exploding in extreme slow motion.
|
721 |
+
An astronaut is riding a horse in the space in a photorealistic style.
|
722 |
+
Macro slo-mo. Slow motion cropped closeup of roasted coffee beans falling into an empty bowl.
|
723 |
+
Sewing machine, old sewing machine working.
|
724 |
+
Motion colour drop in water, ink swirling in water, colourful ink in water, abstraction fancy dream cloud of ink.
|
725 |
+
Few big purple plums rotating on the turntable. water drops appear on the skin during rotation. isolated on the white background. close-up. macro.
|
726 |
+
Vampire makeup face of beautiful girl, red contact lenses.
|
727 |
+
Ashtray full of butts on table, smoke flowing on black background, close-up
|
728 |
+
Pacific coast, carmel by the sea ocean and waves.
|
729 |
+
A teddy bear is playing drum kit in NYC Times Square.
|
730 |
+
A corgi is playing drum kit.
|
731 |
+
An Iron man is playing the electronic guitar, high electronic guitar.
|
732 |
+
A raccoon is playing the electronic guitar.
|
733 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background by Vincent van Gogh
|
734 |
+
A corgi's head depicted as an explosion of a nebula
|
735 |
+
A fantasy landscape
|
736 |
+
A future where humans have achieved teleportation technology
|
737 |
+
A jellyfish floating through the ocean, with bioluminescent tentacles
|
738 |
+
A Mars rover moving on Mars
|
739 |
+
A panda drinking coffee in a cafe in Paris
|
740 |
+
A space shuttle launching into orbit, with flames and smoke billowing out from the engines
|
741 |
+
A steam train moving on a mountainside
|
742 |
+
A super cool giant robot in Cyberpunk Beijing
|
743 |
+
A tropical beach at sunrise, with palm trees and crystal-clear water in the foreground
|
744 |
+
Cinematic shot of Van Gogh's selfie, Van Gogh style
|
745 |
+
Gwen Stacy reading a book
|
746 |
+
Iron Man flying in the sky
|
747 |
+
The bund Shanghai, oil painting
|
748 |
+
Yoda playing guitar on the stage
|
749 |
+
A beautiful coastal beach in spring, waves lapping on sand by Hokusai, in the style of Ukiyo
|
750 |
+
A beautiful coastal beach in spring, waves lapping on sand by Vincent van Gogh
|
751 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background
|
752 |
+
A car moving slowly on an empty street, rainy evening
|
753 |
+
A cat eating food out of a bowl
|
754 |
+
A cat wearing sunglasses at a pool
|
755 |
+
A confused panda in calculus class
|
756 |
+
A cute fluffy panda eating Chinese food in a restaurant
|
757 |
+
A cute happy Corgi playing in park, sunset
|
758 |
+
A cute raccoon playing guitar in a boat on the ocean
|
759 |
+
A happy fuzzy panda playing guitar nearby a campfire, snow mountain in the background
|
760 |
+
A lightning striking atop of eiffel tower, dark clouds in the sky
|
761 |
+
A modern art museum, with colorful paintings
|
762 |
+
A panda cooking in the kitchen
|
763 |
+
A panda playing on a swing set
|
764 |
+
A polar bear is playing guitar
|
765 |
+
A raccoon dressed in suit playing the trumpet, stage background
|
766 |
+
A robot DJ is playing the turntable, in heavy raining futuristic tokyo rooftop cyberpunk night, sci-fi, fantasy
|
767 |
+
A shark swimming in clear Caribbean ocean
|
768 |
+
A super robot protecting city
|
769 |
+
A teddy bear washing the dishes
|
770 |
+
An epic tornado attacking above a glowing city at night, the tornado is made of smoke
|
771 |
+
An oil painting of a couple in formal evening wear going home get caught in a heavy downpour with umbrellas
|
772 |
+
Clown fish swimming through the coral reef
|
773 |
+
Hyper-realistic spaceship landing on Mars
|
774 |
+
The bund Shanghai, vibrant color
|
775 |
+
Vincent van Gogh is painting in the room
|
776 |
+
Yellow flowers swing in the wind
|
777 |
+
alley
|
778 |
+
amusement park
|
779 |
+
aquarium
|
780 |
+
arch
|
781 |
+
art gallery
|
782 |
+
bathroom
|
783 |
+
bakery shop
|
784 |
+
ballroom
|
785 |
+
bar
|
786 |
+
barn
|
787 |
+
basement
|
788 |
+
beach
|
789 |
+
bedroom
|
790 |
+
bridge
|
791 |
+
botanical garden
|
792 |
+
cafeteria
|
793 |
+
campsite
|
794 |
+
campus
|
795 |
+
carrousel
|
796 |
+
castle
|
797 |
+
cemetery
|
798 |
+
classroom
|
799 |
+
cliff
|
800 |
+
crosswalk
|
801 |
+
construction site
|
802 |
+
corridor
|
803 |
+
courtyard
|
804 |
+
desert
|
805 |
+
downtown
|
806 |
+
driveway
|
807 |
+
farm
|
808 |
+
food court
|
809 |
+
football field
|
810 |
+
forest road
|
811 |
+
fountain
|
812 |
+
gas station
|
813 |
+
glacier
|
814 |
+
golf course
|
815 |
+
indoor gymnasium
|
816 |
+
harbor
|
817 |
+
highway
|
818 |
+
hospital
|
819 |
+
house
|
820 |
+
iceberg
|
821 |
+
industrial area
|
822 |
+
jail cell
|
823 |
+
junkyard
|
824 |
+
kitchen
|
825 |
+
indoor library
|
826 |
+
lighthouse
|
827 |
+
laboratory
|
828 |
+
mansion
|
829 |
+
marsh
|
830 |
+
mountain
|
831 |
+
indoor movie theater
|
832 |
+
indoor museum
|
833 |
+
music studio
|
834 |
+
nursery
|
835 |
+
ocean
|
836 |
+
office
|
837 |
+
palace
|
838 |
+
parking lot
|
839 |
+
pharmacy
|
840 |
+
phone booth
|
841 |
+
raceway
|
842 |
+
restaurant
|
843 |
+
river
|
844 |
+
science museum
|
845 |
+
shower
|
846 |
+
ski slope
|
847 |
+
sky
|
848 |
+
skyscraper
|
849 |
+
baseball stadium
|
850 |
+
staircase
|
851 |
+
street
|
852 |
+
supermarket
|
853 |
+
indoor swimming pool
|
854 |
+
tower
|
855 |
+
outdoor track
|
856 |
+
train railway
|
857 |
+
train station platform
|
858 |
+
underwater coral reef
|
859 |
+
valley
|
860 |
+
volcano
|
861 |
+
waterfall
|
862 |
+
windmill
|
863 |
+
a bicycle on the left of a car, front view
|
864 |
+
a car on the right of a motorcycle, front view
|
865 |
+
a motorcycle on the left of a bus, front view
|
866 |
+
a bus on the right of a traffic light, front view
|
867 |
+
a traffic light on the left of a fire hydrant, front view
|
868 |
+
a fire hydrant on the right of a stop sign, front view
|
869 |
+
a stop sign on the left of a parking meter, front view
|
870 |
+
a parking meter on the right of a bench, front view
|
871 |
+
a bench on the left of a truck, front view
|
872 |
+
a truck on the right of a bicycle, front view
|
873 |
+
a bird on the left of a cat, front view
|
874 |
+
a cat on the right of a dog, front view
|
875 |
+
a dog on the left of a horse, front view
|
876 |
+
a horse on the right of a sheep, front view
|
877 |
+
a sheep on the left of a cow, front view
|
878 |
+
a cow on the right of an elephant, front view
|
879 |
+
an elephant on the left of a bear, front view
|
880 |
+
a bear on the right of a zebra, front view
|
881 |
+
a zebra on the left of a giraffe, front view
|
882 |
+
a giraffe on the right of a bird, front view
|
883 |
+
a bottle on the left of a wine glass, front view
|
884 |
+
a wine glass on the right of a cup, front view
|
885 |
+
a cup on the left of a fork, front view
|
886 |
+
a fork on the right of a knife, front view
|
887 |
+
a knife on the left of a spoon, front view
|
888 |
+
a spoon on the right of a bowl, front view
|
889 |
+
a bowl on the left of a bottle, front view
|
890 |
+
a potted plant on the left of a remote, front view
|
891 |
+
a remote on the right of a clock, front view
|
892 |
+
a clock on the left of a vase, front view
|
893 |
+
a vase on the right of scissors, front view
|
894 |
+
scissors on the left of a teddy bear, front view
|
895 |
+
a teddy bear on the right of a potted plant, front view
|
896 |
+
a frisbee on the left of a sports ball, front view
|
897 |
+
a sports ball on the right of a baseball bat, front view
|
898 |
+
a baseball bat on the left of a baseball glove, front view
|
899 |
+
a baseball glove on the right of a tennis racket, front view
|
900 |
+
a tennis racket on the left of a frisbee, front view
|
901 |
+
a toilet on the left of a hair drier, front view
|
902 |
+
a hair drier on the right of a toothbrush, front view
|
903 |
+
a toothbrush on the left of a sink, front view
|
904 |
+
a sink on the right of a toilet, front view
|
905 |
+
a chair on the left of a couch, front view
|
906 |
+
a couch on the right of a bed, front view
|
907 |
+
a bed on the left of a tv, front view
|
908 |
+
a tv on the right of a dining table, front view
|
909 |
+
a dining table on the left of a chair, front view
|
910 |
+
an airplane on the left of a train, front view
|
911 |
+
a train on the right of a boat, front view
|
912 |
+
a boat on the left of an airplane, front view
|
913 |
+
an oven on the top of a toaster, front view
|
914 |
+
an oven on the bottom of a toaster, front view
|
915 |
+
a toaster on the top of a microwave, front view
|
916 |
+
a toaster on the bottom of a microwave, front view
|
917 |
+
a microwave on the top of an oven, front view
|
918 |
+
a microwave on the bottom of an oven, front view
|
919 |
+
a banana on the top of an apple, front view
|
920 |
+
a banana on the bottom of an apple, front view
|
921 |
+
an apple on the top of a sandwich, front view
|
922 |
+
an apple on the bottom of a sandwich, front view
|
923 |
+
a sandwich on the top of an orange, front view
|
924 |
+
a sandwich on the bottom of an orange, front view
|
925 |
+
an orange on the top of a carrot, front view
|
926 |
+
an orange on the bottom of a carrot, front view
|
927 |
+
a carrot on the top of a hot dog, front view
|
928 |
+
a carrot on the bottom of a hot dog, front view
|
929 |
+
a hot dog on the top of a pizza, front view
|
930 |
+
a hot dog on the bottom of a pizza, front view
|
931 |
+
a pizza on the top of a donut, front view
|
932 |
+
a pizza on the bottom of a donut, front view
|
933 |
+
a donut on the top of broccoli, front view
|
934 |
+
a donut on the bottom of broccoli, front view
|
935 |
+
broccoli on the top of a banana, front view
|
936 |
+
broccoli on the bottom of a banana, front view
|
937 |
+
skis on the top of a snowboard, front view
|
938 |
+
skis on the bottom of a snowboard, front view
|
939 |
+
a snowboard on the top of a kite, front view
|
940 |
+
a snowboard on the bottom of a kite, front view
|
941 |
+
a kite on the top of a skateboard, front view
|
942 |
+
a kite on the bottom of a skateboard, front view
|
943 |
+
a skateboard on the top of a surfboard, front view
|
944 |
+
a skateboard on the bottom of a surfboard, front view
|
945 |
+
a surfboard on the top of skis, front view
|
946 |
+
a surfboard on the bottom of skis, front view
|
VBench/prompts/metadata/appearance_style.json
ADDED
@@ -0,0 +1,362 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
[
|
2 |
+
{
|
3 |
+
"prompt_en": "A beautiful coastal beach in spring, waves lapping on sand, Van Gogh style",
|
4 |
+
"style_en": "Van Gogh style"
|
5 |
+
},
|
6 |
+
{
|
7 |
+
"prompt_en": "A beautiful coastal beach in spring, waves lapping on sand, oil painting",
|
8 |
+
"style_en": "oil painting"
|
9 |
+
},
|
10 |
+
{
|
11 |
+
"prompt_en": "A beautiful coastal beach in spring, waves lapping on sand by Hokusai, in the style of Ukiyo",
|
12 |
+
"style_en": "by Hokusai, in the style of Ukiyo"
|
13 |
+
},
|
14 |
+
{
|
15 |
+
"prompt_en": "A beautiful coastal beach in spring, waves lapping on sand, black and white",
|
16 |
+
"style_en": "black and white"
|
17 |
+
},
|
18 |
+
{
|
19 |
+
"prompt_en": "A beautiful coastal beach in spring, waves lapping on sand, pixel art",
|
20 |
+
"style_en": "pixel art"
|
21 |
+
},
|
22 |
+
{
|
23 |
+
"prompt_en": "A beautiful coastal beach in spring, waves lapping on sand, in cyberpunk style",
|
24 |
+
"style_en": "in cyberpunk style"
|
25 |
+
},
|
26 |
+
{
|
27 |
+
"prompt_en": "A beautiful coastal beach in spring, waves lapping on sand, animated style",
|
28 |
+
"style_en": "animated style"
|
29 |
+
},
|
30 |
+
{
|
31 |
+
"prompt_en": "A beautiful coastal beach in spring, waves lapping on sand, watercolor painting",
|
32 |
+
"style_en": "watercolor painting"
|
33 |
+
},
|
34 |
+
{
|
35 |
+
"prompt_en": "A beautiful coastal beach in spring, waves lapping on sand, surrealism style",
|
36 |
+
"style_en": "surrealism style"
|
37 |
+
},
|
38 |
+
{
|
39 |
+
"prompt_en": "The bund Shanghai, Van Gogh style",
|
40 |
+
"style_en": "Van Gogh style"
|
41 |
+
},
|
42 |
+
{
|
43 |
+
"prompt_en": "The bund Shanghai, oil painting",
|
44 |
+
"style_en": "oil painting"
|
45 |
+
},
|
46 |
+
{
|
47 |
+
"prompt_en": "The bund Shanghai by Hokusai, in the style of Ukiyo",
|
48 |
+
"style_en": "by Hokusai, in the style of Ukiyo"
|
49 |
+
},
|
50 |
+
{
|
51 |
+
"prompt_en": "The bund Shanghai, black and white",
|
52 |
+
"style_en": "black and white"
|
53 |
+
},
|
54 |
+
{
|
55 |
+
"prompt_en": "The bund Shanghai, pixel art",
|
56 |
+
"style_en": "pixel art"
|
57 |
+
},
|
58 |
+
{
|
59 |
+
"prompt_en": "The bund Shanghai, in cyberpunk style",
|
60 |
+
"style_en": "in cyberpunk style"
|
61 |
+
},
|
62 |
+
{
|
63 |
+
"prompt_en": "The bund Shanghai, animated style",
|
64 |
+
"style_en": "animated style"
|
65 |
+
},
|
66 |
+
{
|
67 |
+
"prompt_en": "The bund Shanghai, watercolor painting",
|
68 |
+
"style_en": "watercolor painting"
|
69 |
+
},
|
70 |
+
{
|
71 |
+
"prompt_en": "The bund Shanghai, surrealism style",
|
72 |
+
"style_en": "surrealism style"
|
73 |
+
},
|
74 |
+
{
|
75 |
+
"prompt_en": "a shark is swimming in the ocean, Van Gogh style",
|
76 |
+
"style_en": "Van Gogh style"
|
77 |
+
},
|
78 |
+
{
|
79 |
+
"prompt_en": "a shark is swimming in the ocean, oil painting",
|
80 |
+
"style_en": "oil painting"
|
81 |
+
},
|
82 |
+
{
|
83 |
+
"prompt_en": "a shark is swimming in the ocean by Hokusai, in the style of Ukiyo",
|
84 |
+
"style_en": "by Hokusai, in the style of Ukiyo"
|
85 |
+
},
|
86 |
+
{
|
87 |
+
"prompt_en": "a shark is swimming in the ocean, black and white",
|
88 |
+
"style_en": "black and white"
|
89 |
+
},
|
90 |
+
{
|
91 |
+
"prompt_en": "a shark is swimming in the ocean, pixel art",
|
92 |
+
"style_en": "pixel art"
|
93 |
+
},
|
94 |
+
{
|
95 |
+
"prompt_en": "a shark is swimming in the ocean, in cyberpunk style",
|
96 |
+
"style_en": "in cyberpunk style"
|
97 |
+
},
|
98 |
+
{
|
99 |
+
"prompt_en": "a shark is swimming in the ocean, animated style",
|
100 |
+
"style_en": "animated style"
|
101 |
+
},
|
102 |
+
{
|
103 |
+
"prompt_en": "a shark is swimming in the ocean, watercolor painting",
|
104 |
+
"style_en": "watercolor painting"
|
105 |
+
},
|
106 |
+
{
|
107 |
+
"prompt_en": "a shark is swimming in the ocean, surrealism style",
|
108 |
+
"style_en": "surrealism style"
|
109 |
+
},
|
110 |
+
{
|
111 |
+
"prompt_en": "A panda drinking coffee in a cafe in Paris, Van Gogh style",
|
112 |
+
"style_en": "Van Gogh style"
|
113 |
+
},
|
114 |
+
{
|
115 |
+
"prompt_en": "A panda drinking coffee in a cafe in Paris, oil painting",
|
116 |
+
"style_en": "oil painting"
|
117 |
+
},
|
118 |
+
{
|
119 |
+
"prompt_en": "A panda drinking coffee in a cafe in Paris by Hokusai, in the style of Ukiyo",
|
120 |
+
"style_en": "by Hokusai, in the style of Ukiyo"
|
121 |
+
},
|
122 |
+
{
|
123 |
+
"prompt_en": "A panda drinking coffee in a cafe in Paris, black and white",
|
124 |
+
"style_en": "black and white"
|
125 |
+
},
|
126 |
+
{
|
127 |
+
"prompt_en": "A panda drinking coffee in a cafe in Paris, pixel art",
|
128 |
+
"style_en": "pixel art"
|
129 |
+
},
|
130 |
+
{
|
131 |
+
"prompt_en": "A panda drinking coffee in a cafe in Paris, in cyberpunk style",
|
132 |
+
"style_en": "in cyberpunk style"
|
133 |
+
},
|
134 |
+
{
|
135 |
+
"prompt_en": "A panda drinking coffee in a cafe in Paris, animated style",
|
136 |
+
"style_en": "animated style"
|
137 |
+
},
|
138 |
+
{
|
139 |
+
"prompt_en": "A panda drinking coffee in a cafe in Paris, watercolor painting",
|
140 |
+
"style_en": "watercolor painting"
|
141 |
+
},
|
142 |
+
{
|
143 |
+
"prompt_en": "A panda drinking coffee in a cafe in Paris, surrealism style",
|
144 |
+
"style_en": "surrealism style"
|
145 |
+
},
|
146 |
+
{
|
147 |
+
"prompt_en": "A cute happy Corgi playing in park, sunset, Van Gogh style",
|
148 |
+
"style_en": "Van Gogh style"
|
149 |
+
},
|
150 |
+
{
|
151 |
+
"prompt_en": "A cute happy Corgi playing in park, sunset, oil painting",
|
152 |
+
"style_en": "oil painting"
|
153 |
+
},
|
154 |
+
{
|
155 |
+
"prompt_en": "A cute happy Corgi playing in park, sunset by Hokusai, in the style of Ukiyo",
|
156 |
+
"style_en": "by Hokusai, in the style of Ukiyo"
|
157 |
+
},
|
158 |
+
{
|
159 |
+
"prompt_en": "A cute happy Corgi playing in park, sunset, black and white",
|
160 |
+
"style_en": "black and white"
|
161 |
+
},
|
162 |
+
{
|
163 |
+
"prompt_en": "A cute happy Corgi playing in park, sunset, pixel art",
|
164 |
+
"style_en": "pixel art"
|
165 |
+
},
|
166 |
+
{
|
167 |
+
"prompt_en": "A cute happy Corgi playing in park, sunset, in cyberpunk style",
|
168 |
+
"style_en": "in cyberpunk style"
|
169 |
+
},
|
170 |
+
{
|
171 |
+
"prompt_en": "A cute happy Corgi playing in park, sunset, animated style",
|
172 |
+
"style_en": "animated style"
|
173 |
+
},
|
174 |
+
{
|
175 |
+
"prompt_en": "A cute happy Corgi playing in park, sunset, watercolor painting",
|
176 |
+
"style_en": "watercolor painting"
|
177 |
+
},
|
178 |
+
{
|
179 |
+
"prompt_en": "A cute happy Corgi playing in park, sunset, surrealism style",
|
180 |
+
"style_en": "surrealism style"
|
181 |
+
},
|
182 |
+
{
|
183 |
+
"prompt_en": "Gwen Stacy reading a book, Van Gogh style",
|
184 |
+
"style_en": "Van Gogh style"
|
185 |
+
},
|
186 |
+
{
|
187 |
+
"prompt_en": "Gwen Stacy reading a book, oil painting",
|
188 |
+
"style_en": "oil painting"
|
189 |
+
},
|
190 |
+
{
|
191 |
+
"prompt_en": "Gwen Stacy reading a book by Hokusai, in the style of Ukiyo",
|
192 |
+
"style_en": "by Hokusai, in the style of Ukiyo"
|
193 |
+
},
|
194 |
+
{
|
195 |
+
"prompt_en": "Gwen Stacy reading a book, black and white",
|
196 |
+
"style_en": "black and white"
|
197 |
+
},
|
198 |
+
{
|
199 |
+
"prompt_en": "Gwen Stacy reading a book, pixel art",
|
200 |
+
"style_en": "pixel art"
|
201 |
+
},
|
202 |
+
{
|
203 |
+
"prompt_en": "Gwen Stacy reading a book, in cyberpunk style",
|
204 |
+
"style_en": "in cyberpunk style"
|
205 |
+
},
|
206 |
+
{
|
207 |
+
"prompt_en": "Gwen Stacy reading a book, animated style",
|
208 |
+
"style_en": "animated style"
|
209 |
+
},
|
210 |
+
{
|
211 |
+
"prompt_en": "Gwen Stacy reading a book, watercolor painting",
|
212 |
+
"style_en": "watercolor painting"
|
213 |
+
},
|
214 |
+
{
|
215 |
+
"prompt_en": "Gwen Stacy reading a book, surrealism style",
|
216 |
+
"style_en": "surrealism style"
|
217 |
+
},
|
218 |
+
{
|
219 |
+
"prompt_en": "A boat sailing leisurely along the Seine River with the Eiffel Tower in background, Van Gogh style",
|
220 |
+
"style_en": "Van Gogh style"
|
221 |
+
},
|
222 |
+
{
|
223 |
+
"prompt_en": "A boat sailing leisurely along the Seine River with the Eiffel Tower in background, oil painting",
|
224 |
+
"style_en": "oil painting"
|
225 |
+
},
|
226 |
+
{
|
227 |
+
"prompt_en": "A boat sailing leisurely along the Seine River with the Eiffel Tower in background by Hokusai, in the style of Ukiyo",
|
228 |
+
"style_en": "by Hokusai, in the style of Ukiyo"
|
229 |
+
},
|
230 |
+
{
|
231 |
+
"prompt_en": "A boat sailing leisurely along the Seine River with the Eiffel Tower in background, black and white",
|
232 |
+
"style_en": "black and white"
|
233 |
+
},
|
234 |
+
{
|
235 |
+
"prompt_en": "A boat sailing leisurely along the Seine River with the Eiffel Tower in background, pixel art",
|
236 |
+
"style_en": "pixel art"
|
237 |
+
},
|
238 |
+
{
|
239 |
+
"prompt_en": "A boat sailing leisurely along the Seine River with the Eiffel Tower in background, in cyberpunk style",
|
240 |
+
"style_en": "in cyberpunk style"
|
241 |
+
},
|
242 |
+
{
|
243 |
+
"prompt_en": "A boat sailing leisurely along the Seine River with the Eiffel Tower in background, animated style",
|
244 |
+
"style_en": "animated style"
|
245 |
+
},
|
246 |
+
{
|
247 |
+
"prompt_en": "A boat sailing leisurely along the Seine River with the Eiffel Tower in background, watercolor painting",
|
248 |
+
"style_en": "watercolor painting"
|
249 |
+
},
|
250 |
+
{
|
251 |
+
"prompt_en": "A boat sailing leisurely along the Seine River with the Eiffel Tower in background, surrealism style",
|
252 |
+
"style_en": "surrealism style"
|
253 |
+
},
|
254 |
+
{
|
255 |
+
"prompt_en": "A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, Van Gogh style",
|
256 |
+
"style_en": "Van Gogh style"
|
257 |
+
},
|
258 |
+
{
|
259 |
+
"prompt_en": "A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, oil painting",
|
260 |
+
"style_en": "oil painting"
|
261 |
+
},
|
262 |
+
{
|
263 |
+
"prompt_en": "A couple in formal evening wear going home get caught in a heavy downpour with umbrellas by Hokusai, in the style of Ukiyo",
|
264 |
+
"style_en": "by Hokusai, in the style of Ukiyo"
|
265 |
+
},
|
266 |
+
{
|
267 |
+
"prompt_en": "A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, black and white",
|
268 |
+
"style_en": "black and white"
|
269 |
+
},
|
270 |
+
{
|
271 |
+
"prompt_en": "A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, pixel art",
|
272 |
+
"style_en": "pixel art"
|
273 |
+
},
|
274 |
+
{
|
275 |
+
"prompt_en": "A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, in cyberpunk style",
|
276 |
+
"style_en": "in cyberpunk style"
|
277 |
+
},
|
278 |
+
{
|
279 |
+
"prompt_en": "A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, animated style",
|
280 |
+
"style_en": "animated style"
|
281 |
+
},
|
282 |
+
{
|
283 |
+
"prompt_en": "A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, watercolor painting",
|
284 |
+
"style_en": "watercolor painting"
|
285 |
+
},
|
286 |
+
{
|
287 |
+
"prompt_en": "A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, surrealism style",
|
288 |
+
"style_en": "surrealism style"
|
289 |
+
},
|
290 |
+
{
|
291 |
+
"prompt_en": "An astronaut flying in space, Van Gogh style",
|
292 |
+
"style_en": "Van Gogh style"
|
293 |
+
},
|
294 |
+
{
|
295 |
+
"prompt_en": "An astronaut flying in space, oil painting",
|
296 |
+
"style_en": "oil painting"
|
297 |
+
},
|
298 |
+
{
|
299 |
+
"prompt_en": "An astronaut flying in space by Hokusai, in the style of Ukiyo",
|
300 |
+
"style_en": "by Hokusai, in the style of Ukiyo"
|
301 |
+
},
|
302 |
+
{
|
303 |
+
"prompt_en": "An astronaut flying in space, black and white",
|
304 |
+
"style_en": "black and white"
|
305 |
+
},
|
306 |
+
{
|
307 |
+
"prompt_en": "An astronaut flying in space, pixel art",
|
308 |
+
"style_en": "pixel art"
|
309 |
+
},
|
310 |
+
{
|
311 |
+
"prompt_en": "An astronaut flying in space, in cyberpunk style",
|
312 |
+
"style_en": "in cyberpunk style"
|
313 |
+
},
|
314 |
+
{
|
315 |
+
"prompt_en": "An astronaut flying in space, animated style",
|
316 |
+
"style_en": "animated style"
|
317 |
+
},
|
318 |
+
{
|
319 |
+
"prompt_en": "An astronaut flying in space, watercolor painting",
|
320 |
+
"style_en": "watercolor painting"
|
321 |
+
},
|
322 |
+
{
|
323 |
+
"prompt_en": "An astronaut flying in space, surrealism style",
|
324 |
+
"style_en": "surrealism style"
|
325 |
+
},
|
326 |
+
{
|
327 |
+
"prompt_en": "Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, Van Gogh style",
|
328 |
+
"style_en": "Van Gogh style"
|
329 |
+
},
|
330 |
+
{
|
331 |
+
"prompt_en": "Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, oil painting",
|
332 |
+
"style_en": "oil painting"
|
333 |
+
},
|
334 |
+
{
|
335 |
+
"prompt_en": "Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks by Hokusai, in the style of Ukiyo",
|
336 |
+
"style_en": "by Hokusai, in the style of Ukiyo"
|
337 |
+
},
|
338 |
+
{
|
339 |
+
"prompt_en": "Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, black and white",
|
340 |
+
"style_en": "black and white"
|
341 |
+
},
|
342 |
+
{
|
343 |
+
"prompt_en": "Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, pixel art",
|
344 |
+
"style_en": "pixel art"
|
345 |
+
},
|
346 |
+
{
|
347 |
+
"prompt_en": "Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, in cyberpunk style",
|
348 |
+
"style_en": "in cyberpunk style"
|
349 |
+
},
|
350 |
+
{
|
351 |
+
"prompt_en": "Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, animated style",
|
352 |
+
"style_en": "animated style"
|
353 |
+
},
|
354 |
+
{
|
355 |
+
"prompt_en": "Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, watercolor painting",
|
356 |
+
"style_en": "watercolor painting"
|
357 |
+
},
|
358 |
+
{
|
359 |
+
"prompt_en": "Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, surrealism style",
|
360 |
+
"style_en": "surrealism style"
|
361 |
+
}
|
362 |
+
]
|
VBench/prompts/metadata/color.json
ADDED
@@ -0,0 +1,342 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
[
|
2 |
+
{
|
3 |
+
"prompt_en": "a red bicycle",
|
4 |
+
"color_en": "red"
|
5 |
+
},
|
6 |
+
{
|
7 |
+
"prompt_en": "a green bicycle",
|
8 |
+
"color_en": "green"
|
9 |
+
},
|
10 |
+
{
|
11 |
+
"prompt_en": "a blue bicycle",
|
12 |
+
"color_en": "blue"
|
13 |
+
},
|
14 |
+
{
|
15 |
+
"prompt_en": "a yellow bicycle",
|
16 |
+
"color_en": "yellow"
|
17 |
+
},
|
18 |
+
{
|
19 |
+
"prompt_en": "an orange bicycle",
|
20 |
+
"color_en": "orange"
|
21 |
+
},
|
22 |
+
{
|
23 |
+
"prompt_en": "a purple bicycle",
|
24 |
+
"color_en": "purple"
|
25 |
+
},
|
26 |
+
{
|
27 |
+
"prompt_en": "a pink bicycle",
|
28 |
+
"color_en": "pink"
|
29 |
+
},
|
30 |
+
{
|
31 |
+
"prompt_en": "a black bicycle",
|
32 |
+
"color_en": "black"
|
33 |
+
},
|
34 |
+
{
|
35 |
+
"prompt_en": "a white bicycle",
|
36 |
+
"color_en": "white"
|
37 |
+
},
|
38 |
+
{
|
39 |
+
"prompt_en": "a red car",
|
40 |
+
"color_en": "red"
|
41 |
+
},
|
42 |
+
{
|
43 |
+
"prompt_en": "a green car",
|
44 |
+
"color_en": "green"
|
45 |
+
},
|
46 |
+
{
|
47 |
+
"prompt_en": "a blue car",
|
48 |
+
"color_en": "blue"
|
49 |
+
},
|
50 |
+
{
|
51 |
+
"prompt_en": "a yellow car",
|
52 |
+
"color_en": "yellow"
|
53 |
+
},
|
54 |
+
{
|
55 |
+
"prompt_en": "an orange car",
|
56 |
+
"color_en": "orange"
|
57 |
+
},
|
58 |
+
{
|
59 |
+
"prompt_en": "a purple car",
|
60 |
+
"color_en": "purple"
|
61 |
+
},
|
62 |
+
{
|
63 |
+
"prompt_en": "a pink car",
|
64 |
+
"color_en": "pink"
|
65 |
+
},
|
66 |
+
{
|
67 |
+
"prompt_en": "a black car",
|
68 |
+
"color_en": "black"
|
69 |
+
},
|
70 |
+
{
|
71 |
+
"prompt_en": "a white car",
|
72 |
+
"color_en": "white"
|
73 |
+
},
|
74 |
+
{
|
75 |
+
"prompt_en": "a red bird",
|
76 |
+
"color_en": "red"
|
77 |
+
},
|
78 |
+
{
|
79 |
+
"prompt_en": "a green bird",
|
80 |
+
"color_en": "green"
|
81 |
+
},
|
82 |
+
{
|
83 |
+
"prompt_en": "a blue bird",
|
84 |
+
"color_en": "blue"
|
85 |
+
},
|
86 |
+
{
|
87 |
+
"prompt_en": "a yellow bird",
|
88 |
+
"color_en": "yellow"
|
89 |
+
},
|
90 |
+
{
|
91 |
+
"prompt_en": "an orange bird",
|
92 |
+
"color_en": "orange"
|
93 |
+
},
|
94 |
+
{
|
95 |
+
"prompt_en": "a purple bird",
|
96 |
+
"color_en": "purple"
|
97 |
+
},
|
98 |
+
{
|
99 |
+
"prompt_en": "a pink bird",
|
100 |
+
"color_en": "pink"
|
101 |
+
},
|
102 |
+
{
|
103 |
+
"prompt_en": "a black bird",
|
104 |
+
"color_en": "black"
|
105 |
+
},
|
106 |
+
{
|
107 |
+
"prompt_en": "a white bird",
|
108 |
+
"color_en": "white"
|
109 |
+
},
|
110 |
+
{
|
111 |
+
"prompt_en": "a black cat",
|
112 |
+
"color_en": "black"
|
113 |
+
},
|
114 |
+
{
|
115 |
+
"prompt_en": "a white cat",
|
116 |
+
"color_en": "white"
|
117 |
+
},
|
118 |
+
{
|
119 |
+
"prompt_en": "an orange cat",
|
120 |
+
"color_en": "orange"
|
121 |
+
},
|
122 |
+
{
|
123 |
+
"prompt_en": "a yellow cat",
|
124 |
+
"color_en": "yellow"
|
125 |
+
},
|
126 |
+
{
|
127 |
+
"prompt_en": "a red umbrella",
|
128 |
+
"color_en": "red"
|
129 |
+
},
|
130 |
+
{
|
131 |
+
"prompt_en": "a green umbrella",
|
132 |
+
"color_en": "green"
|
133 |
+
},
|
134 |
+
{
|
135 |
+
"prompt_en": "a blue umbrella",
|
136 |
+
"color_en": "blue"
|
137 |
+
},
|
138 |
+
{
|
139 |
+
"prompt_en": "a yellow umbrella",
|
140 |
+
"color_en": "yellow"
|
141 |
+
},
|
142 |
+
{
|
143 |
+
"prompt_en": "an orange umbrella",
|
144 |
+
"color_en": "orange"
|
145 |
+
},
|
146 |
+
{
|
147 |
+
"prompt_en": "a purple umbrella",
|
148 |
+
"color_en": "purple"
|
149 |
+
},
|
150 |
+
{
|
151 |
+
"prompt_en": "a pink umbrella",
|
152 |
+
"color_en": "pink"
|
153 |
+
},
|
154 |
+
{
|
155 |
+
"prompt_en": "a black umbrella",
|
156 |
+
"color_en": "black"
|
157 |
+
},
|
158 |
+
{
|
159 |
+
"prompt_en": "a white umbrella",
|
160 |
+
"color_en": "white"
|
161 |
+
},
|
162 |
+
{
|
163 |
+
"prompt_en": "a red suitcase",
|
164 |
+
"color_en": "red"
|
165 |
+
},
|
166 |
+
{
|
167 |
+
"prompt_en": "a green suitcase",
|
168 |
+
"color_en": "green"
|
169 |
+
},
|
170 |
+
{
|
171 |
+
"prompt_en": "a blue suitcase",
|
172 |
+
"color_en": "blue"
|
173 |
+
},
|
174 |
+
{
|
175 |
+
"prompt_en": "a yellow suitcase",
|
176 |
+
"color_en": "yellow"
|
177 |
+
},
|
178 |
+
{
|
179 |
+
"prompt_en": "an orange suitcase",
|
180 |
+
"color_en": "orange"
|
181 |
+
},
|
182 |
+
{
|
183 |
+
"prompt_en": "a purple suitcase",
|
184 |
+
"color_en": "purple"
|
185 |
+
},
|
186 |
+
{
|
187 |
+
"prompt_en": "a pink suitcase",
|
188 |
+
"color_en": "pink"
|
189 |
+
},
|
190 |
+
{
|
191 |
+
"prompt_en": "a black suitcase",
|
192 |
+
"color_en": "black"
|
193 |
+
},
|
194 |
+
{
|
195 |
+
"prompt_en": "a white suitcase",
|
196 |
+
"color_en": "white"
|
197 |
+
},
|
198 |
+
{
|
199 |
+
"prompt_en": "a red bowl",
|
200 |
+
"color_en": "red"
|
201 |
+
},
|
202 |
+
{
|
203 |
+
"prompt_en": "a green bowl",
|
204 |
+
"color_en": "green"
|
205 |
+
},
|
206 |
+
{
|
207 |
+
"prompt_en": "a blue bowl",
|
208 |
+
"color_en": "blue"
|
209 |
+
},
|
210 |
+
{
|
211 |
+
"prompt_en": "a yellow bowl",
|
212 |
+
"color_en": "yellow"
|
213 |
+
},
|
214 |
+
{
|
215 |
+
"prompt_en": "an orange bowl",
|
216 |
+
"color_en": "orange"
|
217 |
+
},
|
218 |
+
{
|
219 |
+
"prompt_en": "a purple bowl",
|
220 |
+
"color_en": "purple"
|
221 |
+
},
|
222 |
+
{
|
223 |
+
"prompt_en": "a pink bowl",
|
224 |
+
"color_en": "pink"
|
225 |
+
},
|
226 |
+
{
|
227 |
+
"prompt_en": "a black bowl",
|
228 |
+
"color_en": "black"
|
229 |
+
},
|
230 |
+
{
|
231 |
+
"prompt_en": "a white bowl",
|
232 |
+
"color_en": "white"
|
233 |
+
},
|
234 |
+
{
|
235 |
+
"prompt_en": "a red chair",
|
236 |
+
"color_en": "red"
|
237 |
+
},
|
238 |
+
{
|
239 |
+
"prompt_en": "a green chair",
|
240 |
+
"color_en": "green"
|
241 |
+
},
|
242 |
+
{
|
243 |
+
"prompt_en": "a blue chair",
|
244 |
+
"color_en": "blue"
|
245 |
+
},
|
246 |
+
{
|
247 |
+
"prompt_en": "a yellow chair",
|
248 |
+
"color_en": "yellow"
|
249 |
+
},
|
250 |
+
{
|
251 |
+
"prompt_en": "an orange chair",
|
252 |
+
"color_en": "orange"
|
253 |
+
},
|
254 |
+
{
|
255 |
+
"prompt_en": "a purple chair",
|
256 |
+
"color_en": "purple"
|
257 |
+
},
|
258 |
+
{
|
259 |
+
"prompt_en": "a pink chair",
|
260 |
+
"color_en": "pink"
|
261 |
+
},
|
262 |
+
{
|
263 |
+
"prompt_en": "a black chair",
|
264 |
+
"color_en": "black"
|
265 |
+
},
|
266 |
+
{
|
267 |
+
"prompt_en": "a white chair",
|
268 |
+
"color_en": "white"
|
269 |
+
},
|
270 |
+
{
|
271 |
+
"prompt_en": "a red clock",
|
272 |
+
"color_en": "red"
|
273 |
+
},
|
274 |
+
{
|
275 |
+
"prompt_en": "a green clock",
|
276 |
+
"color_en": "green"
|
277 |
+
},
|
278 |
+
{
|
279 |
+
"prompt_en": "a blue clock",
|
280 |
+
"color_en": "blue"
|
281 |
+
},
|
282 |
+
{
|
283 |
+
"prompt_en": "a yellow clock",
|
284 |
+
"color_en": "yellow"
|
285 |
+
},
|
286 |
+
{
|
287 |
+
"prompt_en": "an orange clock",
|
288 |
+
"color_en": "orange"
|
289 |
+
},
|
290 |
+
{
|
291 |
+
"prompt_en": "a purple clock",
|
292 |
+
"color_en": "purple"
|
293 |
+
},
|
294 |
+
{
|
295 |
+
"prompt_en": "a pink clock",
|
296 |
+
"color_en": "pink"
|
297 |
+
},
|
298 |
+
{
|
299 |
+
"prompt_en": "a black clock",
|
300 |
+
"color_en": "black"
|
301 |
+
},
|
302 |
+
{
|
303 |
+
"prompt_en": "a white clock",
|
304 |
+
"color_en": "white"
|
305 |
+
},
|
306 |
+
{
|
307 |
+
"prompt_en": "a red vase",
|
308 |
+
"color_en": "red"
|
309 |
+
},
|
310 |
+
{
|
311 |
+
"prompt_en": "a green vase",
|
312 |
+
"color_en": "green"
|
313 |
+
},
|
314 |
+
{
|
315 |
+
"prompt_en": "a blue vase",
|
316 |
+
"color_en": "blue"
|
317 |
+
},
|
318 |
+
{
|
319 |
+
"prompt_en": "a yellow vase",
|
320 |
+
"color_en": "yellow"
|
321 |
+
},
|
322 |
+
{
|
323 |
+
"prompt_en": "an orange vase",
|
324 |
+
"color_en": "orange"
|
325 |
+
},
|
326 |
+
{
|
327 |
+
"prompt_en": "a purple vase",
|
328 |
+
"color_en": "purple"
|
329 |
+
},
|
330 |
+
{
|
331 |
+
"prompt_en": "a pink vase",
|
332 |
+
"color_en": "pink"
|
333 |
+
},
|
334 |
+
{
|
335 |
+
"prompt_en": "a black vase",
|
336 |
+
"color_en": "black"
|
337 |
+
},
|
338 |
+
{
|
339 |
+
"prompt_en": "a white vase",
|
340 |
+
"color_en": "white"
|
341 |
+
}
|
342 |
+
]
|
VBench/prompts/metadata/multiple_objects.json
ADDED
@@ -0,0 +1,330 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
[
|
2 |
+
{
|
3 |
+
"prompt_en": "a bird and a cat",
|
4 |
+
"object_en": "bird and cat"
|
5 |
+
},
|
6 |
+
{
|
7 |
+
"prompt_en": "a cat and a dog",
|
8 |
+
"object_en": "cat and dog"
|
9 |
+
},
|
10 |
+
{
|
11 |
+
"prompt_en": "a dog and a horse",
|
12 |
+
"object_en": "dog and horse"
|
13 |
+
},
|
14 |
+
{
|
15 |
+
"prompt_en": "a horse and a sheep",
|
16 |
+
"object_en": "horse and sheep"
|
17 |
+
},
|
18 |
+
{
|
19 |
+
"prompt_en": "a sheep and a cow",
|
20 |
+
"object_en": "sheep and cow"
|
21 |
+
},
|
22 |
+
{
|
23 |
+
"prompt_en": "a cow and an elephant",
|
24 |
+
"object_en": "cow and elephant"
|
25 |
+
},
|
26 |
+
{
|
27 |
+
"prompt_en": "an elephant and a bear",
|
28 |
+
"object_en": "elephant and bear"
|
29 |
+
},
|
30 |
+
{
|
31 |
+
"prompt_en": "a bear and a zebra",
|
32 |
+
"object_en": "bear and zebra"
|
33 |
+
},
|
34 |
+
{
|
35 |
+
"prompt_en": "a zebra and a giraffe",
|
36 |
+
"object_en": "zebra and giraffe"
|
37 |
+
},
|
38 |
+
{
|
39 |
+
"prompt_en": "a giraffe and a bird",
|
40 |
+
"object_en": "giraffe and bird"
|
41 |
+
},
|
42 |
+
{
|
43 |
+
"prompt_en": "a chair and a couch",
|
44 |
+
"object_en": "chair and couch"
|
45 |
+
},
|
46 |
+
{
|
47 |
+
"prompt_en": "a couch and a potted plant",
|
48 |
+
"object_en": "couch and potted plant"
|
49 |
+
},
|
50 |
+
{
|
51 |
+
"prompt_en": "a potted plant and a tv",
|
52 |
+
"object_en": "potted plant and tv"
|
53 |
+
},
|
54 |
+
{
|
55 |
+
"prompt_en": "a tv and a laptop",
|
56 |
+
"object_en": "tv and laptop"
|
57 |
+
},
|
58 |
+
{
|
59 |
+
"prompt_en": "a laptop and a remote",
|
60 |
+
"object_en": "laptop and remote"
|
61 |
+
},
|
62 |
+
{
|
63 |
+
"prompt_en": "a remote and a keyboard",
|
64 |
+
"object_en": "remote and keyboard"
|
65 |
+
},
|
66 |
+
{
|
67 |
+
"prompt_en": "a keyboard and a cell phone",
|
68 |
+
"object_en": "keyboard and cell phone"
|
69 |
+
},
|
70 |
+
{
|
71 |
+
"prompt_en": "a cell phone and a book",
|
72 |
+
"object_en": "cell phone and book"
|
73 |
+
},
|
74 |
+
{
|
75 |
+
"prompt_en": "a book and a clock",
|
76 |
+
"object_en": "book and clock"
|
77 |
+
},
|
78 |
+
{
|
79 |
+
"prompt_en": "a clock and a backpack",
|
80 |
+
"object_en": "clock and backpack"
|
81 |
+
},
|
82 |
+
{
|
83 |
+
"prompt_en": "a backpack and an umbrella",
|
84 |
+
"object_en": "backpack and umbrella"
|
85 |
+
},
|
86 |
+
{
|
87 |
+
"prompt_en": "an umbrella and a handbag",
|
88 |
+
"object_en": "umbrella and handbag"
|
89 |
+
},
|
90 |
+
{
|
91 |
+
"prompt_en": "a handbag and a tie",
|
92 |
+
"object_en": "handbag and tie"
|
93 |
+
},
|
94 |
+
{
|
95 |
+
"prompt_en": "a tie and a suitcase",
|
96 |
+
"object_en": "tie and suitcase"
|
97 |
+
},
|
98 |
+
{
|
99 |
+
"prompt_en": "a suitcase and a vase",
|
100 |
+
"object_en": "suitcase and vase"
|
101 |
+
},
|
102 |
+
{
|
103 |
+
"prompt_en": "a vase and scissors",
|
104 |
+
"object_en": "vase and scissors"
|
105 |
+
},
|
106 |
+
{
|
107 |
+
"prompt_en": "scissors and a teddy bear",
|
108 |
+
"object_en": "scissors and teddy bear"
|
109 |
+
},
|
110 |
+
{
|
111 |
+
"prompt_en": "a teddy bear and a frisbee",
|
112 |
+
"object_en": "teddy bear and frisbee"
|
113 |
+
},
|
114 |
+
{
|
115 |
+
"prompt_en": "a frisbee and skis",
|
116 |
+
"object_en": "frisbee and skis"
|
117 |
+
},
|
118 |
+
{
|
119 |
+
"prompt_en": "skis and a snowboard",
|
120 |
+
"object_en": "skis and snowboard"
|
121 |
+
},
|
122 |
+
{
|
123 |
+
"prompt_en": "a snowboard and a sports ball",
|
124 |
+
"object_en": "snowboard and sports ball"
|
125 |
+
},
|
126 |
+
{
|
127 |
+
"prompt_en": "a sports ball and a kite",
|
128 |
+
"object_en": "sports ball and kite"
|
129 |
+
},
|
130 |
+
{
|
131 |
+
"prompt_en": "a kite and a baseball bat",
|
132 |
+
"object_en": "kite and baseball bat"
|
133 |
+
},
|
134 |
+
{
|
135 |
+
"prompt_en": "a baseball bat and a baseball glove",
|
136 |
+
"object_en": "baseball bat and baseball glove"
|
137 |
+
},
|
138 |
+
{
|
139 |
+
"prompt_en": "a baseball glove and a skateboard",
|
140 |
+
"object_en": "baseball glove and skateboard"
|
141 |
+
},
|
142 |
+
{
|
143 |
+
"prompt_en": "a skateboard and a surfboard",
|
144 |
+
"object_en": "skateboard and surfboard"
|
145 |
+
},
|
146 |
+
{
|
147 |
+
"prompt_en": "a surfboard and a tennis racket",
|
148 |
+
"object_en": "surfboard and tennis racket"
|
149 |
+
},
|
150 |
+
{
|
151 |
+
"prompt_en": "a tennis racket and a bottle",
|
152 |
+
"object_en": "tennis racket and bottle"
|
153 |
+
},
|
154 |
+
{
|
155 |
+
"prompt_en": "a bottle and a chair",
|
156 |
+
"object_en": "bottle and chair"
|
157 |
+
},
|
158 |
+
{
|
159 |
+
"prompt_en": "an airplane and a train",
|
160 |
+
"object_en": "airplane and train"
|
161 |
+
},
|
162 |
+
{
|
163 |
+
"prompt_en": "a train and a boat",
|
164 |
+
"object_en": "train and boat"
|
165 |
+
},
|
166 |
+
{
|
167 |
+
"prompt_en": "a boat and an airplane",
|
168 |
+
"object_en": "boat and airplane"
|
169 |
+
},
|
170 |
+
{
|
171 |
+
"prompt_en": "a bicycle and a car",
|
172 |
+
"object_en": "bicycle and car"
|
173 |
+
},
|
174 |
+
{
|
175 |
+
"prompt_en": "a car and a motorcycle",
|
176 |
+
"object_en": "car and motorcycle"
|
177 |
+
},
|
178 |
+
{
|
179 |
+
"prompt_en": "a motorcycle and a bus",
|
180 |
+
"object_en": "motorcycle and bus"
|
181 |
+
},
|
182 |
+
{
|
183 |
+
"prompt_en": "a bus and a traffic light",
|
184 |
+
"object_en": "bus and traffic light"
|
185 |
+
},
|
186 |
+
{
|
187 |
+
"prompt_en": "a traffic light and a fire hydrant",
|
188 |
+
"object_en": "traffic light and fire hydrant"
|
189 |
+
},
|
190 |
+
{
|
191 |
+
"prompt_en": "a fire hydrant and a stop sign",
|
192 |
+
"object_en": "fire hydrant and stop sign"
|
193 |
+
},
|
194 |
+
{
|
195 |
+
"prompt_en": "a stop sign and a parking meter",
|
196 |
+
"object_en": "stop sign and parking meter"
|
197 |
+
},
|
198 |
+
{
|
199 |
+
"prompt_en": "a parking meter and a truck",
|
200 |
+
"object_en": "parking meter and truck"
|
201 |
+
},
|
202 |
+
{
|
203 |
+
"prompt_en": "a truck and a bicycle",
|
204 |
+
"object_en": "truck and bicycle"
|
205 |
+
},
|
206 |
+
{
|
207 |
+
"prompt_en": "a toilet and a hair drier",
|
208 |
+
"object_en": "toilet and hair drier"
|
209 |
+
},
|
210 |
+
{
|
211 |
+
"prompt_en": "a hair drier and a toothbrush",
|
212 |
+
"object_en": "hair drier and toothbrush"
|
213 |
+
},
|
214 |
+
{
|
215 |
+
"prompt_en": "a toothbrush and a sink",
|
216 |
+
"object_en": "toothbrush and sink"
|
217 |
+
},
|
218 |
+
{
|
219 |
+
"prompt_en": "a sink and a toilet",
|
220 |
+
"object_en": "sink and toilet"
|
221 |
+
},
|
222 |
+
{
|
223 |
+
"prompt_en": "a wine glass and a chair",
|
224 |
+
"object_en": "wine glass and chair"
|
225 |
+
},
|
226 |
+
{
|
227 |
+
"prompt_en": "a cup and a couch",
|
228 |
+
"object_en": "cup and couch"
|
229 |
+
},
|
230 |
+
{
|
231 |
+
"prompt_en": "a fork and a potted plant",
|
232 |
+
"object_en": "fork and potted plant"
|
233 |
+
},
|
234 |
+
{
|
235 |
+
"prompt_en": "a knife and a tv",
|
236 |
+
"object_en": "knife and tv"
|
237 |
+
},
|
238 |
+
{
|
239 |
+
"prompt_en": "a spoon and a laptop",
|
240 |
+
"object_en": "spoon and laptop"
|
241 |
+
},
|
242 |
+
{
|
243 |
+
"prompt_en": "a bowl and a remote",
|
244 |
+
"object_en": "bowl and remote"
|
245 |
+
},
|
246 |
+
{
|
247 |
+
"prompt_en": "a banana and a keyboard",
|
248 |
+
"object_en": "banana and keyboard"
|
249 |
+
},
|
250 |
+
{
|
251 |
+
"prompt_en": "an apple and a cell phone",
|
252 |
+
"object_en": "apple and cell phone"
|
253 |
+
},
|
254 |
+
{
|
255 |
+
"prompt_en": "a sandwich and a book",
|
256 |
+
"object_en": "sandwich and book"
|
257 |
+
},
|
258 |
+
{
|
259 |
+
"prompt_en": "an orange and a clock",
|
260 |
+
"object_en": "orange and clock"
|
261 |
+
},
|
262 |
+
{
|
263 |
+
"prompt_en": "broccoli and a backpack",
|
264 |
+
"object_en": "broccoli and backpack"
|
265 |
+
},
|
266 |
+
{
|
267 |
+
"prompt_en": "a carrot and an umbrella",
|
268 |
+
"object_en": "carrot and umbrella"
|
269 |
+
},
|
270 |
+
{
|
271 |
+
"prompt_en": "a hot dog and a handbag",
|
272 |
+
"object_en": "hot dog and handbag"
|
273 |
+
},
|
274 |
+
{
|
275 |
+
"prompt_en": "a pizza and a tie",
|
276 |
+
"object_en": "pizza and tie"
|
277 |
+
},
|
278 |
+
{
|
279 |
+
"prompt_en": "a donut and a suitcase",
|
280 |
+
"object_en": "donut and suitcase"
|
281 |
+
},
|
282 |
+
{
|
283 |
+
"prompt_en": "a cake and a vase",
|
284 |
+
"object_en": "cake and vase"
|
285 |
+
},
|
286 |
+
{
|
287 |
+
"prompt_en": "an oven and scissors",
|
288 |
+
"object_en": "oven and scissors"
|
289 |
+
},
|
290 |
+
{
|
291 |
+
"prompt_en": "a toaster and a teddy bear",
|
292 |
+
"object_en": "toaster and teddy bear"
|
293 |
+
},
|
294 |
+
{
|
295 |
+
"prompt_en": "a microwave and a frisbee",
|
296 |
+
"object_en": "microwave and frisbee"
|
297 |
+
},
|
298 |
+
{
|
299 |
+
"prompt_en": "a refrigerator and skis",
|
300 |
+
"object_en": "refrigerator and skis"
|
301 |
+
},
|
302 |
+
{
|
303 |
+
"prompt_en": "a bicycle and an airplane",
|
304 |
+
"object_en": "bicycle and airplane"
|
305 |
+
},
|
306 |
+
{
|
307 |
+
"prompt_en": "a car and a train",
|
308 |
+
"object_en": "car and train"
|
309 |
+
},
|
310 |
+
{
|
311 |
+
"prompt_en": "a motorcycle and a boat",
|
312 |
+
"object_en": "motorcycle and boat"
|
313 |
+
},
|
314 |
+
{
|
315 |
+
"prompt_en": "a person and a toilet",
|
316 |
+
"object_en": "person and toilet"
|
317 |
+
},
|
318 |
+
{
|
319 |
+
"prompt_en": "a person and a hair drier",
|
320 |
+
"object_en": "person and hair drier"
|
321 |
+
},
|
322 |
+
{
|
323 |
+
"prompt_en": "a person and a toothbrush",
|
324 |
+
"object_en": "person and toothbrush"
|
325 |
+
},
|
326 |
+
{
|
327 |
+
"prompt_en": "a person and a sink",
|
328 |
+
"object_en": "person and sink"
|
329 |
+
}
|
330 |
+
]
|
VBench/prompts/metadata/object_class.json
ADDED
@@ -0,0 +1,318 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
[
|
2 |
+
{
|
3 |
+
"prompt_en": "a person",
|
4 |
+
"object_en": "person"
|
5 |
+
},
|
6 |
+
{
|
7 |
+
"prompt_en": "a bicycle",
|
8 |
+
"object_en": "bicycle"
|
9 |
+
},
|
10 |
+
{
|
11 |
+
"prompt_en": "a car",
|
12 |
+
"object_en": "car"
|
13 |
+
},
|
14 |
+
{
|
15 |
+
"prompt_en": "a motorcycle",
|
16 |
+
"object_en": "motorcycle"
|
17 |
+
},
|
18 |
+
{
|
19 |
+
"prompt_en": "an airplane",
|
20 |
+
"object_en": "airplane"
|
21 |
+
},
|
22 |
+
{
|
23 |
+
"prompt_en": "a bus",
|
24 |
+
"object_en": "bus"
|
25 |
+
},
|
26 |
+
{
|
27 |
+
"prompt_en": "a train",
|
28 |
+
"object_en": "train"
|
29 |
+
},
|
30 |
+
{
|
31 |
+
"prompt_en": "a truck",
|
32 |
+
"object_en": "truck"
|
33 |
+
},
|
34 |
+
{
|
35 |
+
"prompt_en": "a boat",
|
36 |
+
"object_en": "boat"
|
37 |
+
},
|
38 |
+
{
|
39 |
+
"prompt_en": "a traffic light",
|
40 |
+
"object_en": "traffic light"
|
41 |
+
},
|
42 |
+
{
|
43 |
+
"prompt_en": "a fire hydrant",
|
44 |
+
"object_en": "fire hydrant"
|
45 |
+
},
|
46 |
+
{
|
47 |
+
"prompt_en": "a stop sign",
|
48 |
+
"object_en": "stop sign"
|
49 |
+
},
|
50 |
+
{
|
51 |
+
"prompt_en": "a parking meter",
|
52 |
+
"object_en": "parking meter"
|
53 |
+
},
|
54 |
+
{
|
55 |
+
"prompt_en": "a bench",
|
56 |
+
"object_en": "bench"
|
57 |
+
},
|
58 |
+
{
|
59 |
+
"prompt_en": "a bird",
|
60 |
+
"object_en": "bird"
|
61 |
+
},
|
62 |
+
{
|
63 |
+
"prompt_en": "a cat",
|
64 |
+
"object_en": "cat"
|
65 |
+
},
|
66 |
+
{
|
67 |
+
"prompt_en": "a dog",
|
68 |
+
"object_en": "dog"
|
69 |
+
},
|
70 |
+
{
|
71 |
+
"prompt_en": "a horse",
|
72 |
+
"object_en": "horse"
|
73 |
+
},
|
74 |
+
{
|
75 |
+
"prompt_en": "a sheep",
|
76 |
+
"object_en": "sheep"
|
77 |
+
},
|
78 |
+
{
|
79 |
+
"prompt_en": "a cow",
|
80 |
+
"object_en": "cow"
|
81 |
+
},
|
82 |
+
{
|
83 |
+
"prompt_en": "an elephant",
|
84 |
+
"object_en": "elephant"
|
85 |
+
},
|
86 |
+
{
|
87 |
+
"prompt_en": "a bear",
|
88 |
+
"object_en": "bear"
|
89 |
+
},
|
90 |
+
{
|
91 |
+
"prompt_en": "a zebra",
|
92 |
+
"object_en": "zebra"
|
93 |
+
},
|
94 |
+
{
|
95 |
+
"prompt_en": "a giraffe",
|
96 |
+
"object_en": "giraffe"
|
97 |
+
},
|
98 |
+
{
|
99 |
+
"prompt_en": "a backpack",
|
100 |
+
"object_en": "backpack"
|
101 |
+
},
|
102 |
+
{
|
103 |
+
"prompt_en": "an umbrella",
|
104 |
+
"object_en": "umbrella"
|
105 |
+
},
|
106 |
+
{
|
107 |
+
"prompt_en": "a handbag",
|
108 |
+
"object_en": "handbag"
|
109 |
+
},
|
110 |
+
{
|
111 |
+
"prompt_en": "a tie",
|
112 |
+
"object_en": "tie"
|
113 |
+
},
|
114 |
+
{
|
115 |
+
"prompt_en": "a suitcase",
|
116 |
+
"object_en": "suitcase"
|
117 |
+
},
|
118 |
+
{
|
119 |
+
"prompt_en": "a frisbee",
|
120 |
+
"object_en": "frisbee"
|
121 |
+
},
|
122 |
+
{
|
123 |
+
"prompt_en": "skis",
|
124 |
+
"object_en": "skis"
|
125 |
+
},
|
126 |
+
{
|
127 |
+
"prompt_en": "a snowboard",
|
128 |
+
"object_en": "snowboard"
|
129 |
+
},
|
130 |
+
{
|
131 |
+
"prompt_en": "a sports ball",
|
132 |
+
"object_en": "sports ball"
|
133 |
+
},
|
134 |
+
{
|
135 |
+
"prompt_en": "a kite",
|
136 |
+
"object_en": "kite"
|
137 |
+
},
|
138 |
+
{
|
139 |
+
"prompt_en": "a baseball bat",
|
140 |
+
"object_en": "baseball bat"
|
141 |
+
},
|
142 |
+
{
|
143 |
+
"prompt_en": "a baseball glove",
|
144 |
+
"object_en": "baseball glove"
|
145 |
+
},
|
146 |
+
{
|
147 |
+
"prompt_en": "a skateboard",
|
148 |
+
"object_en": "skateboard"
|
149 |
+
},
|
150 |
+
{
|
151 |
+
"prompt_en": "a surfboard",
|
152 |
+
"object_en": "surfboard"
|
153 |
+
},
|
154 |
+
{
|
155 |
+
"prompt_en": "a tennis racket",
|
156 |
+
"object_en": "tennis racket"
|
157 |
+
},
|
158 |
+
{
|
159 |
+
"prompt_en": "a bottle",
|
160 |
+
"object_en": "bottle"
|
161 |
+
},
|
162 |
+
{
|
163 |
+
"prompt_en": "a wine glass",
|
164 |
+
"object_en": "wine glass"
|
165 |
+
},
|
166 |
+
{
|
167 |
+
"prompt_en": "a cup",
|
168 |
+
"object_en": "cup"
|
169 |
+
},
|
170 |
+
{
|
171 |
+
"prompt_en": "a fork",
|
172 |
+
"object_en": "fork"
|
173 |
+
},
|
174 |
+
{
|
175 |
+
"prompt_en": "a knife",
|
176 |
+
"object_en": "knife"
|
177 |
+
},
|
178 |
+
{
|
179 |
+
"prompt_en": "a spoon",
|
180 |
+
"object_en": "spoon"
|
181 |
+
},
|
182 |
+
{
|
183 |
+
"prompt_en": "a bowl",
|
184 |
+
"object_en": "bowl"
|
185 |
+
},
|
186 |
+
{
|
187 |
+
"prompt_en": "a banana",
|
188 |
+
"object_en": "banana"
|
189 |
+
},
|
190 |
+
{
|
191 |
+
"prompt_en": "an apple",
|
192 |
+
"object_en": "apple"
|
193 |
+
},
|
194 |
+
{
|
195 |
+
"prompt_en": "a sandwich",
|
196 |
+
"object_en": "sandwich"
|
197 |
+
},
|
198 |
+
{
|
199 |
+
"prompt_en": "an orange",
|
200 |
+
"object_en": "orange"
|
201 |
+
},
|
202 |
+
{
|
203 |
+
"prompt_en": "broccoli",
|
204 |
+
"object_en": "broccoli"
|
205 |
+
},
|
206 |
+
{
|
207 |
+
"prompt_en": "a carrot",
|
208 |
+
"object_en": "carrot"
|
209 |
+
},
|
210 |
+
{
|
211 |
+
"prompt_en": "a hot dog",
|
212 |
+
"object_en": "hot dog"
|
213 |
+
},
|
214 |
+
{
|
215 |
+
"prompt_en": "a pizza",
|
216 |
+
"object_en": "pizza"
|
217 |
+
},
|
218 |
+
{
|
219 |
+
"prompt_en": "a donut",
|
220 |
+
"object_en": "donut"
|
221 |
+
},
|
222 |
+
{
|
223 |
+
"prompt_en": "a cake",
|
224 |
+
"object_en": "cake"
|
225 |
+
},
|
226 |
+
{
|
227 |
+
"prompt_en": "a chair",
|
228 |
+
"object_en": "chair"
|
229 |
+
},
|
230 |
+
{
|
231 |
+
"prompt_en": "a couch",
|
232 |
+
"object_en": "couch"
|
233 |
+
},
|
234 |
+
{
|
235 |
+
"prompt_en": "a potted plant",
|
236 |
+
"object_en": "potted plant"
|
237 |
+
},
|
238 |
+
{
|
239 |
+
"prompt_en": "a bed",
|
240 |
+
"object_en": "bed"
|
241 |
+
},
|
242 |
+
{
|
243 |
+
"prompt_en": "a dining table",
|
244 |
+
"object_en": "dining table"
|
245 |
+
},
|
246 |
+
{
|
247 |
+
"prompt_en": "a toilet",
|
248 |
+
"object_en": "toilet"
|
249 |
+
},
|
250 |
+
{
|
251 |
+
"prompt_en": "a tv",
|
252 |
+
"object_en": "tv"
|
253 |
+
},
|
254 |
+
{
|
255 |
+
"prompt_en": "a laptop",
|
256 |
+
"object_en": "laptop"
|
257 |
+
},
|
258 |
+
{
|
259 |
+
"prompt_en": "a remote",
|
260 |
+
"object_en": "remote"
|
261 |
+
},
|
262 |
+
{
|
263 |
+
"prompt_en": "a keyboard",
|
264 |
+
"object_en": "keyboard"
|
265 |
+
},
|
266 |
+
{
|
267 |
+
"prompt_en": "a cell phone",
|
268 |
+
"object_en": "cell phone"
|
269 |
+
},
|
270 |
+
{
|
271 |
+
"prompt_en": "a microwave",
|
272 |
+
"object_en": "microwave"
|
273 |
+
},
|
274 |
+
{
|
275 |
+
"prompt_en": "an oven",
|
276 |
+
"object_en": "oven"
|
277 |
+
},
|
278 |
+
{
|
279 |
+
"prompt_en": "a toaster",
|
280 |
+
"object_en": "toaster"
|
281 |
+
},
|
282 |
+
{
|
283 |
+
"prompt_en": "a sink",
|
284 |
+
"object_en": "sink"
|
285 |
+
},
|
286 |
+
{
|
287 |
+
"prompt_en": "a refrigerator",
|
288 |
+
"object_en": "refrigerator"
|
289 |
+
},
|
290 |
+
{
|
291 |
+
"prompt_en": "a book",
|
292 |
+
"object_en": "book"
|
293 |
+
},
|
294 |
+
{
|
295 |
+
"prompt_en": "a clock",
|
296 |
+
"object_en": "clock"
|
297 |
+
},
|
298 |
+
{
|
299 |
+
"prompt_en": "a vase",
|
300 |
+
"object_en": "vase"
|
301 |
+
},
|
302 |
+
{
|
303 |
+
"prompt_en": "scissors",
|
304 |
+
"object_en": "scissors"
|
305 |
+
},
|
306 |
+
{
|
307 |
+
"prompt_en": "a teddy bear",
|
308 |
+
"object_en": "teddy bear"
|
309 |
+
},
|
310 |
+
{
|
311 |
+
"prompt_en": "a hair drier",
|
312 |
+
"object_en": "hair drier"
|
313 |
+
},
|
314 |
+
{
|
315 |
+
"prompt_en": "a toothbrush",
|
316 |
+
"object_en": "toothbrush"
|
317 |
+
}
|
318 |
+
]
|
VBench/prompts/metadata/spatial_relationship.json
ADDED
@@ -0,0 +1,506 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
[
|
2 |
+
{
|
3 |
+
"prompt_en": "a bicycle on the left of a car, front view",
|
4 |
+
"object_a_en": "bicycle",
|
5 |
+
"object_b_en": "car",
|
6 |
+
"relationship_en": "on the left of"
|
7 |
+
},
|
8 |
+
{
|
9 |
+
"prompt_en": "a car on the right of a motorcycle, front view",
|
10 |
+
"object_a_en": "car",
|
11 |
+
"object_b_en": "motorcycle",
|
12 |
+
"relationship_en": "on the right of"
|
13 |
+
},
|
14 |
+
{
|
15 |
+
"prompt_en": "a motorcycle on the left of a bus, front view",
|
16 |
+
"object_a_en": "motorcycle",
|
17 |
+
"object_b_en": "bus",
|
18 |
+
"relationship_en": "on the left of"
|
19 |
+
},
|
20 |
+
{
|
21 |
+
"prompt_en": "a bus on the right of a traffic light, front view",
|
22 |
+
"object_a_en": "bus",
|
23 |
+
"object_b_en": "traffic light",
|
24 |
+
"relationship_en": "on the right of"
|
25 |
+
},
|
26 |
+
{
|
27 |
+
"prompt_en": "a traffic light on the left of a fire hydrant, front view",
|
28 |
+
"object_a_en": "traffic light",
|
29 |
+
"object_b_en": "fire hydrant",
|
30 |
+
"relationship_en": "on the left of"
|
31 |
+
},
|
32 |
+
{
|
33 |
+
"prompt_en": "a fire hydrant on the right of a stop sign, front view",
|
34 |
+
"object_a_en": "fire hydrant",
|
35 |
+
"object_b_en": "stop sign",
|
36 |
+
"relationship_en": "on the right of"
|
37 |
+
},
|
38 |
+
{
|
39 |
+
"prompt_en": "a stop sign on the left of a parking meter, front view",
|
40 |
+
"object_a_en": "stop sign",
|
41 |
+
"object_b_en": "parking meter",
|
42 |
+
"relationship_en": "on the left of"
|
43 |
+
},
|
44 |
+
{
|
45 |
+
"prompt_en": "a parking meter on the right of a bench, front view",
|
46 |
+
"object_a_en": "parking meter",
|
47 |
+
"object_b_en": "bench",
|
48 |
+
"relationship_en": "on the right of"
|
49 |
+
},
|
50 |
+
{
|
51 |
+
"prompt_en": "a bench on the left of a truck, front view",
|
52 |
+
"object_a_en": "bench",
|
53 |
+
"object_b_en": "truck",
|
54 |
+
"relationship_en": "on the left of"
|
55 |
+
},
|
56 |
+
{
|
57 |
+
"prompt_en": "a truck on the right of a bicycle, front view",
|
58 |
+
"object_a_en": "truck",
|
59 |
+
"object_b_en": "bicycle",
|
60 |
+
"relationship_en": "on the right of"
|
61 |
+
},
|
62 |
+
{
|
63 |
+
"prompt_en": "a bird on the left of a cat, front view",
|
64 |
+
"object_a_en": "bird",
|
65 |
+
"object_b_en": "cat",
|
66 |
+
"relationship_en": "on the left of"
|
67 |
+
},
|
68 |
+
{
|
69 |
+
"prompt_en": "a cat on the right of a dog, front view",
|
70 |
+
"object_a_en": "cat",
|
71 |
+
"object_b_en": "dog",
|
72 |
+
"relationship_en": "on the right of"
|
73 |
+
},
|
74 |
+
{
|
75 |
+
"prompt_en": "a dog on the left of a horse, front view",
|
76 |
+
"object_a_en": "dog",
|
77 |
+
"object_b_en": "horse",
|
78 |
+
"relationship_en": "on the left of"
|
79 |
+
},
|
80 |
+
{
|
81 |
+
"prompt_en": "a horse on the right of a sheep, front view",
|
82 |
+
"object_a_en": "horse",
|
83 |
+
"object_b_en": "sheep",
|
84 |
+
"relationship_en": "on the right of"
|
85 |
+
},
|
86 |
+
{
|
87 |
+
"prompt_en": "a sheep on the left of a cow, front view",
|
88 |
+
"object_a_en": "sheep",
|
89 |
+
"object_b_en": "cow",
|
90 |
+
"relationship_en": "on the left of"
|
91 |
+
},
|
92 |
+
{
|
93 |
+
"prompt_en": "a cow on the right of an elephant, front view",
|
94 |
+
"object_a_en": "cow",
|
95 |
+
"object_b_en": "elephant",
|
96 |
+
"relationship_en": "on the right of"
|
97 |
+
},
|
98 |
+
{
|
99 |
+
"prompt_en": "an elephant on the left of a bear, front view",
|
100 |
+
"object_a_en": "elephant",
|
101 |
+
"object_b_en": "bear",
|
102 |
+
"relationship_en": "on the left of"
|
103 |
+
},
|
104 |
+
{
|
105 |
+
"prompt_en": "a bear on the right of a zebra, front view",
|
106 |
+
"object_a_en": "bear",
|
107 |
+
"object_b_en": "zebra",
|
108 |
+
"relationship_en": "on the right of"
|
109 |
+
},
|
110 |
+
{
|
111 |
+
"prompt_en": "a zebra on the left of a giraffe, front view",
|
112 |
+
"object_a_en": "zebra",
|
113 |
+
"object_b_en": "giraffe",
|
114 |
+
"relationship_en": "on the left of"
|
115 |
+
},
|
116 |
+
{
|
117 |
+
"prompt_en": "a giraffe on the right of a bird, front view",
|
118 |
+
"object_a_en": "giraffe",
|
119 |
+
"object_b_en": "bird",
|
120 |
+
"relationship_en": "on the right of"
|
121 |
+
},
|
122 |
+
{
|
123 |
+
"prompt_en": "a bottle on the left of a wine glass, front view",
|
124 |
+
"object_a_en": "bottle",
|
125 |
+
"object_b_en": "wine glass",
|
126 |
+
"relationship_en": "on the left of"
|
127 |
+
},
|
128 |
+
{
|
129 |
+
"prompt_en": "a wine glass on the right of a cup, front view",
|
130 |
+
"object_a_en": "wine glass",
|
131 |
+
"object_b_en": "cup",
|
132 |
+
"relationship_en": "on the right of"
|
133 |
+
},
|
134 |
+
{
|
135 |
+
"prompt_en": "a cup on the left of a fork, front view",
|
136 |
+
"object_a_en": "cup",
|
137 |
+
"object_b_en": "fork",
|
138 |
+
"relationship_en": "on the left of"
|
139 |
+
},
|
140 |
+
{
|
141 |
+
"prompt_en": "a fork on the right of a knife, front view",
|
142 |
+
"object_a_en": "fork",
|
143 |
+
"object_b_en": "knife",
|
144 |
+
"relationship_en": "on the right of"
|
145 |
+
},
|
146 |
+
{
|
147 |
+
"prompt_en": "a knife on the left of a spoon, front view",
|
148 |
+
"object_a_en": "knife",
|
149 |
+
"object_b_en": "spoon",
|
150 |
+
"relationship_en": "on the left of"
|
151 |
+
},
|
152 |
+
{
|
153 |
+
"prompt_en": "a spoon on the right of a bowl, front view",
|
154 |
+
"object_a_en": "spoon",
|
155 |
+
"object_b_en": "bowl",
|
156 |
+
"relationship_en": "on the right of"
|
157 |
+
},
|
158 |
+
{
|
159 |
+
"prompt_en": "a bowl on the left of a bottle, front view",
|
160 |
+
"object_a_en": "bowl",
|
161 |
+
"object_b_en": "bottle",
|
162 |
+
"relationship_en": "on the left of"
|
163 |
+
},
|
164 |
+
{
|
165 |
+
"prompt_en": "a potted plant on the left of a remote, front view",
|
166 |
+
"object_a_en": "potted plant",
|
167 |
+
"object_b_en": "remote",
|
168 |
+
"relationship_en": "on the left of"
|
169 |
+
},
|
170 |
+
{
|
171 |
+
"prompt_en": "a remote on the right of a clock, front view",
|
172 |
+
"object_a_en": "remote",
|
173 |
+
"object_b_en": "clock",
|
174 |
+
"relationship_en": "on the right of"
|
175 |
+
},
|
176 |
+
{
|
177 |
+
"prompt_en": "a clock on the left of a vase, front view",
|
178 |
+
"object_a_en": "clock",
|
179 |
+
"object_b_en": "vase",
|
180 |
+
"relationship_en": "on the left of"
|
181 |
+
},
|
182 |
+
{
|
183 |
+
"prompt_en": "a vase on the right of scissors, front view",
|
184 |
+
"object_a_en": "vase",
|
185 |
+
"object_b_en": "scissors",
|
186 |
+
"relationship_en": "on the right of"
|
187 |
+
},
|
188 |
+
{
|
189 |
+
"prompt_en": "scissors on the left of a teddy bear, front view",
|
190 |
+
"object_a_en": "scissors",
|
191 |
+
"object_b_en": "teddy bear",
|
192 |
+
"relationship_en": "on the left of"
|
193 |
+
},
|
194 |
+
{
|
195 |
+
"prompt_en": "a teddy bear on the right of a potted plant, front view",
|
196 |
+
"object_a_en": "teddy bear",
|
197 |
+
"object_b_en": "potted plant",
|
198 |
+
"relationship_en": "on the right of"
|
199 |
+
},
|
200 |
+
{
|
201 |
+
"prompt_en": "a frisbee on the left of a sports ball, front view",
|
202 |
+
"object_a_en": "frisbee",
|
203 |
+
"object_b_en": "sports ball",
|
204 |
+
"relationship_en": "on the left of"
|
205 |
+
},
|
206 |
+
{
|
207 |
+
"prompt_en": "a sports ball on the right of a baseball bat, front view",
|
208 |
+
"object_a_en": "sports ball",
|
209 |
+
"object_b_en": "baseball bat",
|
210 |
+
"relationship_en": "on the right of"
|
211 |
+
},
|
212 |
+
{
|
213 |
+
"prompt_en": "a baseball bat on the left of a baseball glove, front view",
|
214 |
+
"object_a_en": "baseball bat",
|
215 |
+
"object_b_en": "baseball glove",
|
216 |
+
"relationship_en": "on the left of"
|
217 |
+
},
|
218 |
+
{
|
219 |
+
"prompt_en": "a baseball glove on the right of a tennis racket, front view",
|
220 |
+
"object_a_en": "baseball glove",
|
221 |
+
"object_b_en": "tennis racket",
|
222 |
+
"relationship_en": "on the right of"
|
223 |
+
},
|
224 |
+
{
|
225 |
+
"prompt_en": "a tennis racket on the left of a frisbee, front view",
|
226 |
+
"object_a_en": "tennis racket",
|
227 |
+
"object_b_en": "frisbee",
|
228 |
+
"relationship_en": "on the left of"
|
229 |
+
},
|
230 |
+
{
|
231 |
+
"prompt_en": "a toilet on the left of a hair drier, front view",
|
232 |
+
"object_a_en": "toilet",
|
233 |
+
"object_b_en": "hair drier",
|
234 |
+
"relationship_en": "on the left of"
|
235 |
+
},
|
236 |
+
{
|
237 |
+
"prompt_en": "a hair drier on the right of a toothbrush, front view",
|
238 |
+
"object_a_en": "hair drier",
|
239 |
+
"object_b_en": "toothbrush",
|
240 |
+
"relationship_en": "on the right of"
|
241 |
+
},
|
242 |
+
{
|
243 |
+
"prompt_en": "a toothbrush on the left of a sink, front view",
|
244 |
+
"object_a_en": "toothbrush",
|
245 |
+
"object_b_en": "sink",
|
246 |
+
"relationship_en": "on the left of"
|
247 |
+
},
|
248 |
+
{
|
249 |
+
"prompt_en": "a sink on the right of a toilet, front view",
|
250 |
+
"object_a_en": "sink",
|
251 |
+
"object_b_en": "toilet",
|
252 |
+
"relationship_en": "on the right of"
|
253 |
+
},
|
254 |
+
{
|
255 |
+
"prompt_en": "a chair on the left of a couch, front view",
|
256 |
+
"object_a_en": "chair",
|
257 |
+
"object_b_en": "couch",
|
258 |
+
"relationship_en": "on the left of"
|
259 |
+
},
|
260 |
+
{
|
261 |
+
"prompt_en": "a couch on the right of a bed, front view",
|
262 |
+
"object_a_en": "couch",
|
263 |
+
"object_b_en": "bed",
|
264 |
+
"relationship_en": "on the right of"
|
265 |
+
},
|
266 |
+
{
|
267 |
+
"prompt_en": "a bed on the left of a tv, front view",
|
268 |
+
"object_a_en": "bed",
|
269 |
+
"object_b_en": "tv",
|
270 |
+
"relationship_en": "on the left of"
|
271 |
+
},
|
272 |
+
{
|
273 |
+
"prompt_en": "a tv on the right of a dining table, front view",
|
274 |
+
"object_a_en": "tv",
|
275 |
+
"object_b_en": "dining table",
|
276 |
+
"relationship_en": "on the right of"
|
277 |
+
},
|
278 |
+
{
|
279 |
+
"prompt_en": "a dining table on the left of a chair, front view",
|
280 |
+
"object_a_en": "dining table",
|
281 |
+
"object_b_en": "chair",
|
282 |
+
"relationship_en": "on the left of"
|
283 |
+
},
|
284 |
+
{
|
285 |
+
"prompt_en": "an airplane on the left of a train, front view",
|
286 |
+
"object_a_en": "airplane",
|
287 |
+
"object_b_en": "train",
|
288 |
+
"relationship_en": "on the left of"
|
289 |
+
},
|
290 |
+
{
|
291 |
+
"prompt_en": "a train on the right of a boat, front view",
|
292 |
+
"object_a_en": "train",
|
293 |
+
"object_b_en": "boat",
|
294 |
+
"relationship_en": "on the right of"
|
295 |
+
},
|
296 |
+
{
|
297 |
+
"prompt_en": "a boat on the left of an airplane, front view",
|
298 |
+
"object_a_en": "boat",
|
299 |
+
"object_b_en": "airplane",
|
300 |
+
"relationship_en": "on the left of"
|
301 |
+
},
|
302 |
+
{
|
303 |
+
"prompt_en": "an oven on the top of a toaster, front view",
|
304 |
+
"object_a_en": "oven",
|
305 |
+
"object_b_en": "toaster",
|
306 |
+
"relationship_en": "on the top of"
|
307 |
+
},
|
308 |
+
{
|
309 |
+
"prompt_en": "an oven on the bottom of a toaster, front view",
|
310 |
+
"object_a_en": "oven",
|
311 |
+
"object_b_en": "toaster",
|
312 |
+
"relationship_en": "on the bottom of"
|
313 |
+
},
|
314 |
+
{
|
315 |
+
"prompt_en": "a toaster on the top of a microwave, front view",
|
316 |
+
"object_a_en": "toaster",
|
317 |
+
"object_b_en": "microwave",
|
318 |
+
"relationship_en": "on the top of"
|
319 |
+
},
|
320 |
+
{
|
321 |
+
"prompt_en": "a toaster on the bottom of a microwave, front view",
|
322 |
+
"object_a_en": "toaster",
|
323 |
+
"object_b_en": "microwave",
|
324 |
+
"relationship_en": "on the bottom of"
|
325 |
+
},
|
326 |
+
{
|
327 |
+
"prompt_en": "a microwave on the top of an oven, front view",
|
328 |
+
"object_a_en": "microwave",
|
329 |
+
"object_b_en": "oven",
|
330 |
+
"relationship_en": "on the top of"
|
331 |
+
},
|
332 |
+
{
|
333 |
+
"prompt_en": "a microwave on the bottom of an oven, front view",
|
334 |
+
"object_a_en": "microwave",
|
335 |
+
"object_b_en": "oven",
|
336 |
+
"relationship_en": "on the bottom of"
|
337 |
+
},
|
338 |
+
{
|
339 |
+
"prompt_en": "a banana on the top of an apple, front view",
|
340 |
+
"object_a_en": "banana",
|
341 |
+
"object_b_en": "apple",
|
342 |
+
"relationship_en": "on the top of"
|
343 |
+
},
|
344 |
+
{
|
345 |
+
"prompt_en": "a banana on the bottom of an apple, front view",
|
346 |
+
"object_a_en": "banana",
|
347 |
+
"object_b_en": "apple",
|
348 |
+
"relationship_en": "on the bottom of"
|
349 |
+
},
|
350 |
+
{
|
351 |
+
"prompt_en": "an apple on the top of a sandwich, front view",
|
352 |
+
"object_a_en": "apple",
|
353 |
+
"object_b_en": "sandwich",
|
354 |
+
"relationship_en": "on the top of"
|
355 |
+
},
|
356 |
+
{
|
357 |
+
"prompt_en": "an apple on the bottom of a sandwich, front view",
|
358 |
+
"object_a_en": "apple",
|
359 |
+
"object_b_en": "sandwich",
|
360 |
+
"relationship_en": "on the bottom of"
|
361 |
+
},
|
362 |
+
{
|
363 |
+
"prompt_en": "a sandwich on the top of an orange, front view",
|
364 |
+
"object_a_en": "sandwich",
|
365 |
+
"object_b_en": "orange",
|
366 |
+
"relationship_en": "on the top of"
|
367 |
+
},
|
368 |
+
{
|
369 |
+
"prompt_en": "a sandwich on the bottom of an orange, front view",
|
370 |
+
"object_a_en": "sandwich",
|
371 |
+
"object_b_en": "orange",
|
372 |
+
"relationship_en": "on the bottom of"
|
373 |
+
},
|
374 |
+
{
|
375 |
+
"prompt_en": "an orange on the top of a carrot, front view",
|
376 |
+
"object_a_en": "orange",
|
377 |
+
"object_b_en": "carrot",
|
378 |
+
"relationship_en": "on the top of"
|
379 |
+
},
|
380 |
+
{
|
381 |
+
"prompt_en": "an orange on the bottom of a carrot, front view",
|
382 |
+
"object_a_en": "orange",
|
383 |
+
"object_b_en": "carrot",
|
384 |
+
"relationship_en": "on the bottom of"
|
385 |
+
},
|
386 |
+
{
|
387 |
+
"prompt_en": "a carrot on the top of a hot dog, front view",
|
388 |
+
"object_a_en": "carrot",
|
389 |
+
"object_b_en": "hot dog",
|
390 |
+
"relationship_en": "on the top of"
|
391 |
+
},
|
392 |
+
{
|
393 |
+
"prompt_en": "a carrot on the bottom of a hot dog, front view",
|
394 |
+
"object_a_en": "carrot",
|
395 |
+
"object_b_en": "hot dog",
|
396 |
+
"relationship_en": "on the bottom of"
|
397 |
+
},
|
398 |
+
{
|
399 |
+
"prompt_en": "a hot dog on the top of a pizza, front view",
|
400 |
+
"object_a_en": "hot dog",
|
401 |
+
"object_b_en": "pizza",
|
402 |
+
"relationship_en": "on the top of"
|
403 |
+
},
|
404 |
+
{
|
405 |
+
"prompt_en": "a hot dog on the bottom of a pizza, front view",
|
406 |
+
"object_a_en": "hot dog",
|
407 |
+
"object_b_en": "pizza",
|
408 |
+
"relationship_en": "on the bottom of"
|
409 |
+
},
|
410 |
+
{
|
411 |
+
"prompt_en": "a pizza on the top of a donut, front view",
|
412 |
+
"object_a_en": "pizza",
|
413 |
+
"object_b_en": "donut",
|
414 |
+
"relationship_en": "on the top of"
|
415 |
+
},
|
416 |
+
{
|
417 |
+
"prompt_en": "a pizza on the bottom of a donut, front view",
|
418 |
+
"object_a_en": "pizza",
|
419 |
+
"object_b_en": "donut",
|
420 |
+
"relationship_en": "on the bottom of"
|
421 |
+
},
|
422 |
+
{
|
423 |
+
"prompt_en": "a donut on the top of broccoli, front view",
|
424 |
+
"object_a_en": "donut",
|
425 |
+
"object_b_en": "broccoli",
|
426 |
+
"relationship_en": "on the top of"
|
427 |
+
},
|
428 |
+
{
|
429 |
+
"prompt_en": "a donut on the bottom of broccoli, front view",
|
430 |
+
"object_a_en": "donut",
|
431 |
+
"object_b_en": "broccoli",
|
432 |
+
"relationship_en": "on the bottom of"
|
433 |
+
},
|
434 |
+
{
|
435 |
+
"prompt_en": "broccoli on the top of a banana, front view",
|
436 |
+
"object_a_en": "broccoli",
|
437 |
+
"object_b_en": "banana",
|
438 |
+
"relationship_en": "on the top of"
|
439 |
+
},
|
440 |
+
{
|
441 |
+
"prompt_en": "broccoli on the bottom of a banana, front view",
|
442 |
+
"object_a_en": "broccoli",
|
443 |
+
"object_b_en": "banana",
|
444 |
+
"relationship_en": "on the bottom of"
|
445 |
+
},
|
446 |
+
{
|
447 |
+
"prompt_en": "skis on the top of a snowboard, front view",
|
448 |
+
"object_a_en": "skis",
|
449 |
+
"object_b_en": "snowboard",
|
450 |
+
"relationship_en": "on the top of"
|
451 |
+
},
|
452 |
+
{
|
453 |
+
"prompt_en": "skis on the bottom of a snowboard, front view",
|
454 |
+
"object_a_en": "skis",
|
455 |
+
"object_b_en": "snowboard",
|
456 |
+
"relationship_en": "on the bottom of"
|
457 |
+
},
|
458 |
+
{
|
459 |
+
"prompt_en": "a snowboard on the top of a kite, front view",
|
460 |
+
"object_a_en": "snowboard",
|
461 |
+
"object_b_en": "kite",
|
462 |
+
"relationship_en": "on the top of"
|
463 |
+
},
|
464 |
+
{
|
465 |
+
"prompt_en": "a snowboard on the bottom of a kite, front view",
|
466 |
+
"object_a_en": "snowboard",
|
467 |
+
"object_b_en": "kite",
|
468 |
+
"relationship_en": "on the bottom of"
|
469 |
+
},
|
470 |
+
{
|
471 |
+
"prompt_en": "a kite on the top of a skateboard, front view",
|
472 |
+
"object_a_en": "kite",
|
473 |
+
"object_b_en": "skateboard",
|
474 |
+
"relationship_en": "on the top of"
|
475 |
+
},
|
476 |
+
{
|
477 |
+
"prompt_en": "a kite on the bottom of a skateboard, front view",
|
478 |
+
"object_a_en": "kite",
|
479 |
+
"object_b_en": "skateboard",
|
480 |
+
"relationship_en": "on the bottom of"
|
481 |
+
},
|
482 |
+
{
|
483 |
+
"prompt_en": "a skateboard on the top of a surfboard, front view",
|
484 |
+
"object_a_en": "skateboard",
|
485 |
+
"object_b_en": "surfboard",
|
486 |
+
"relationship_en": "on the top of"
|
487 |
+
},
|
488 |
+
{
|
489 |
+
"prompt_en": "a skateboard on the bottom of a surfboard, front view",
|
490 |
+
"object_a_en": "skateboard",
|
491 |
+
"object_b_en": "surfboard",
|
492 |
+
"relationship_en": "on the bottom of"
|
493 |
+
},
|
494 |
+
{
|
495 |
+
"prompt_en": "a surfboard on the top of skis, front view",
|
496 |
+
"object_a_en": "surfboard",
|
497 |
+
"object_b_en": "skis",
|
498 |
+
"relationship_en": "on the top of"
|
499 |
+
},
|
500 |
+
{
|
501 |
+
"prompt_en": "a surfboard on the bottom of skis, front view",
|
502 |
+
"object_a_en": "surfboard",
|
503 |
+
"object_b_en": "skis",
|
504 |
+
"relationship_en": "on the bottom of"
|
505 |
+
}
|
506 |
+
]
|
VBench/prompts/prompts_per_category/animal.txt
ADDED
@@ -0,0 +1,100 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
a black dog wearing halloween costume
|
2 |
+
spider making a web
|
3 |
+
bat eating fruits while hanging
|
4 |
+
a snake crawling on a wooden flooring
|
5 |
+
a close up video of a dragonfly
|
6 |
+
macro shot of ladybug on green leaf plant
|
7 |
+
chameleon eating ant
|
8 |
+
a bee feeding on nectars
|
9 |
+
bird nests on a tree captured with moving camera
|
10 |
+
a squirrel eating nuts
|
11 |
+
close up video of snail
|
12 |
+
top view of a hermit crab crawling on a wooden surface
|
13 |
+
cat licking another cat
|
14 |
+
red dragonfly perched on green leaf
|
15 |
+
close up view of a brown caterpillar crawling on green leaf
|
16 |
+
ants eating dead spider
|
17 |
+
an eagle on a tree branch
|
18 |
+
a frog eating an ant
|
19 |
+
white rabbit near the fence
|
20 |
+
a gorilla eating a carrot
|
21 |
+
close up of wolf
|
22 |
+
a meerkat looking around
|
23 |
+
a hyena in a zoo
|
24 |
+
lemur eating grass leaves
|
25 |
+
an owl being trained by a man
|
26 |
+
a lizard on a bamboo
|
27 |
+
brown chicken hunting for its food
|
28 |
+
video of parrots perched on bird stand
|
29 |
+
underwater footage of an octopus in a coral reef
|
30 |
+
a cute pomeranian dog playing with a soccer ball
|
31 |
+
white fox on rock
|
32 |
+
close up footage of a horse figurine
|
33 |
+
giraffe feeding on a tree in a savannah
|
34 |
+
curious cat sitting and looking around
|
35 |
+
hummingbird hawk moth flying near pink flowers
|
36 |
+
close up of a scorpion on a rock
|
37 |
+
close up on fish in net
|
38 |
+
koala eating leaves from a branch
|
39 |
+
a pod of dolphins swirling in the sea catching forage fish
|
40 |
+
low angle view of a hawk perched on a tree branch
|
41 |
+
a lion standing on wild grass
|
42 |
+
deer grazing in the field
|
43 |
+
elephant herd in a savanna
|
44 |
+
close up on lobster under water
|
45 |
+
hedgehog crossing road in forest
|
46 |
+
a sheep eating yellow flowers from behind a wire fence
|
47 |
+
twin sisters and a turtle
|
48 |
+
a pig wallowing in mud
|
49 |
+
flock of goose eating on the lake water
|
50 |
+
cow in a field irritated with flies
|
51 |
+
a close up shot of a fly
|
52 |
+
cheetah lying on the grass
|
53 |
+
close up of a lemur
|
54 |
+
close up shot of a kangaroo itching in the sand
|
55 |
+
a tortoise covered with algae
|
56 |
+
turkey in cage
|
57 |
+
a great blue heron bird in the lakeside
|
58 |
+
crab with shell in aquarium
|
59 |
+
a seagull walking on shore
|
60 |
+
an american crocodile
|
61 |
+
a tiger walking inside a cage
|
62 |
+
alligator in the nature
|
63 |
+
a raccoon climbing a tree
|
64 |
+
wild rabbit in a green meadow
|
65 |
+
group of ring tailed lemurs
|
66 |
+
a clouded leopard on a tree branch
|
67 |
+
duck grooming its feathers
|
68 |
+
an african penguin walking on a beach
|
69 |
+
a video of a peacock
|
70 |
+
close up shot of a wild bear
|
71 |
+
baby rhino plays with mom
|
72 |
+
porcupine climbs tree branches
|
73 |
+
close up of a natterjack toad on a rock
|
74 |
+
a sleeping orangutan
|
75 |
+
mother whale swimming with babies
|
76 |
+
a bear wearing red jersey
|
77 |
+
pink jellyfish swimming underwater in a blue sea
|
78 |
+
beautiful clown fish swimming
|
79 |
+
animation of disposable objects shaped as a whale
|
80 |
+
paper cut out of a pair of hands a whale and a heart
|
81 |
+
vertical video of camel roaming in the field during daytime
|
82 |
+
a still video of mosquito biting human
|
83 |
+
a curious sloth hanging from a tree branch
|
84 |
+
a plastic flamingo bird stumbles from the wind
|
85 |
+
a wolf in its natural habitat
|
86 |
+
a monkey sitting in the stone and scratching his head
|
87 |
+
bat hanging upside down
|
88 |
+
a red panda eating leaves
|
89 |
+
snake on ground
|
90 |
+
a harbour seal swimming near the shore
|
91 |
+
shark swimming in the sea
|
92 |
+
otter on branch while eating
|
93 |
+
goat standing over a rock
|
94 |
+
a troop of monkey on top of a mountain
|
95 |
+
a zebra eating grass on the field
|
96 |
+
a colorful butterfly perching on a bud
|
97 |
+
a snail crawling on a leaf
|
98 |
+
zookeeper showering a baby elephant
|
99 |
+
a beetle emerging from the sand
|
100 |
+
a nine banded armadillo searching for food
|
VBench/prompts/prompts_per_category/architecture.txt
ADDED
@@ -0,0 +1,100 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
an apartment building with balcony
|
2 |
+
asian garden and medieval castle
|
3 |
+
illuminated tower in berlin
|
4 |
+
a wooden house overseeing the lake
|
5 |
+
a crowd of people in a plaza in front of a government building
|
6 |
+
a church interior
|
7 |
+
jewish friends posing with hanukkah menorah in a cabin house
|
8 |
+
a destroyed building after a missile attack in ukraine
|
9 |
+
abandoned building in the woods
|
10 |
+
drone video of an abandoned school building in pripyat ukraine
|
11 |
+
elegant university building
|
12 |
+
architecture and designs of buildings in central london
|
13 |
+
a pancake tower with chocolate syrup and strawberries on top
|
14 |
+
an ancient white building
|
15 |
+
friends hanging out at a coffee house
|
16 |
+
house front door with christmas decorations
|
17 |
+
city night dark building
|
18 |
+
a bird house hanging on a tree branch
|
19 |
+
sacred sculpture in a temple
|
20 |
+
high angle shot of a clock tower
|
21 |
+
modern wooden house interior
|
22 |
+
the interior of an abandoned building
|
23 |
+
opera house overlooking sea
|
24 |
+
a concrete structure near the green trees
|
25 |
+
dome like building in scotland
|
26 |
+
low angle shot of a building
|
27 |
+
tower on hill
|
28 |
+
a miniature house
|
29 |
+
eiffel tower from the seine river
|
30 |
+
low angle footage of an apartment building
|
31 |
+
island with pier and antique building
|
32 |
+
asian historic architecture
|
33 |
+
drone footage of a beautiful mansion
|
34 |
+
mosque in the middle east
|
35 |
+
building a tent and hammock in the forest camping site
|
36 |
+
top view of a high rise building
|
37 |
+
house covered in snow
|
38 |
+
skyscraper at night
|
39 |
+
house in village
|
40 |
+
a casino with people outside the building
|
41 |
+
silhouette of a building
|
42 |
+
a woman climbing a tree house
|
43 |
+
drone view of house near lake during golden hour
|
44 |
+
an under construction concrete house
|
45 |
+
a watch tower by the sea
|
46 |
+
exterior view of arabic style building
|
47 |
+
video of a hotel building
|
48 |
+
red paper lantern decorations hanging outside a building
|
49 |
+
house on seashore
|
50 |
+
aerial footage of the palace of culture and science building in warsaw poland
|
51 |
+
aerial video of stuttgart tv tower in germany
|
52 |
+
aerial view of the highway and building in a city
|
53 |
+
drone shot of a skyscraper san francisco california usa
|
54 |
+
waterfall and house
|
55 |
+
view of the sky through a building
|
56 |
+
drone footage of a house on top of the mountain
|
57 |
+
abandoned house in the nature
|
58 |
+
clouds hovering over a mansion
|
59 |
+
light house on the ocean
|
60 |
+
buddhist temple at sunrise
|
61 |
+
people walking by a graveyard near a mosque at sunset
|
62 |
+
view of lifeguard tower on the beach
|
63 |
+
scenic view of a house in the mountains
|
64 |
+
the landscape in front of a government building
|
65 |
+
aerial footage of a building and its surrounding landscape in winter
|
66 |
+
time lapse of a cloudy sky behind a transmission tower
|
67 |
+
blue ocean near the brown castle
|
68 |
+
fog over temple
|
69 |
+
house in countryside top view
|
70 |
+
building under construction
|
71 |
+
turkish flag waving on old tower
|
72 |
+
the georgian building
|
73 |
+
close up shot of a steel structure
|
74 |
+
the atrium and interior design of a multi floor building
|
75 |
+
city view reflected on a glass building
|
76 |
+
aerial view of a luxurious house with pool
|
77 |
+
an unpaved road leading to the house
|
78 |
+
drone footage of a lookout tower in mountain landscape
|
79 |
+
wind turbines on hill behind building
|
80 |
+
time lapse footage of the sun light in front of a small house porch
|
81 |
+
a building built with lots of stairways
|
82 |
+
overcast over house on seashore
|
83 |
+
the view of the sydney opera house from the other side of the harbor
|
84 |
+
candle on a jar and a house figurine on a surface
|
85 |
+
video of a farm and house
|
86 |
+
a dilapidated building made of bricks
|
87 |
+
a view of a unique building from a moving vehicle
|
88 |
+
aerial footage of a tall building in cambodia
|
89 |
+
push in shot of a huge house
|
90 |
+
a beach house built over a seawall protected from the sea waves
|
91 |
+
exotic house surrounded by trees
|
92 |
+
drone video of a house surrounded by tropical vegetation
|
93 |
+
drone footage of a building beside a pond
|
94 |
+
observation tower on hill in forest
|
95 |
+
a tree house in the woods
|
96 |
+
a video of vessel structure during daytime
|
97 |
+
fire in front of illuminated building at night
|
98 |
+
a footage of a wooden house on a wheat field
|
99 |
+
tilt shot of a solar panel below a light tower
|
100 |
+
water tower on the desert
|
VBench/prompts/prompts_per_category/food.txt
ADDED
@@ -0,0 +1,100 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
freshly baked finger looking cookies
|
2 |
+
video of fake blood in wine glass
|
3 |
+
halloween food art
|
4 |
+
a person slicing a vegetable
|
5 |
+
a serving of pumpkin dish in a plate
|
6 |
+
close up view of green leafy vegetable
|
7 |
+
a birthday cake in the plate
|
8 |
+
video of a slice papaya fruit
|
9 |
+
a muffin with a burning candle and a love sign by a ceramic mug
|
10 |
+
a jack o lantern designed cookie
|
11 |
+
baked bread with chocolate
|
12 |
+
a broccoli soup on wooden table
|
13 |
+
a freshly brewed coffee on a pink mug
|
14 |
+
grabbing sourdough neapolitan style pizza slices
|
15 |
+
person cooking mushrooms in frying pan
|
16 |
+
rice grains placed on a reusable cloth bag
|
17 |
+
slices of kiwi fruit
|
18 |
+
grilling a steak on a pan grill
|
19 |
+
close up of bread popping out of a toaster
|
20 |
+
man eating noodle
|
21 |
+
preparing a cocktail drink
|
22 |
+
close up pasta with bacon on plate
|
23 |
+
milk and cinnamon rolls
|
24 |
+
boy getting a dumpling using chopsticks
|
25 |
+
a mother preparing food with her kids
|
26 |
+
man using his phone while eating
|
27 |
+
fresh salmon salad on a plate
|
28 |
+
cutting cucumbers into long thin slices as ingredient for sushi roll
|
29 |
+
a steaming cup of tea by the window
|
30 |
+
a glass filled with beer
|
31 |
+
a kid eating popcorn while watching tv
|
32 |
+
close up shot of fried fish on the plate
|
33 |
+
a man eating a donut
|
34 |
+
person making a vegetarian dish
|
35 |
+
spreading cheese on bagel
|
36 |
+
close up view of a man drinking red wine
|
37 |
+
a couple having breakfast in a restaurant
|
38 |
+
a student eating her sandwich
|
39 |
+
girl peeling a banana
|
40 |
+
red rice in a small bowl
|
41 |
+
pancake with blueberry on the top
|
42 |
+
green apple fruit on white wooden table
|
43 |
+
a man eating a taco by the bar
|
44 |
+
making of a burrito
|
45 |
+
squeezing lemon into salad
|
46 |
+
a chef cutting sushi rolls
|
47 |
+
video of a delicious dessert
|
48 |
+
deep frying a crab on a wok in high fire
|
49 |
+
close up video of a orange juice
|
50 |
+
video of a cooked chicken breast
|
51 |
+
woman holding a pineapple
|
52 |
+
a woman eating a bar of chocolate
|
53 |
+
decorating christmas cookie
|
54 |
+
squeezing a slice of fruit
|
55 |
+
tuna sashimi on a plate
|
56 |
+
a strawberry fruit mixed in an alcoholic drink
|
57 |
+
preparing hot dogs in a grill
|
58 |
+
a woman cutting a tomato
|
59 |
+
an orange fruit cut in half
|
60 |
+
a coconut fruit with drinking straw
|
61 |
+
woman holding a dragon fruit
|
62 |
+
a woman pouring hot beverage on a cup
|
63 |
+
waffles with whipped cream and fruit
|
64 |
+
focus shot of an insect at the bottom of a fruit
|
65 |
+
preparing a healthy broccoli dish
|
66 |
+
man eating snack at picnic
|
67 |
+
close up video of a grilled shrimp skewer
|
68 |
+
a woman mixing a smoothie drinks
|
69 |
+
close up video of woman having a bite of jelly
|
70 |
+
businessman drinking whiskey at the bar counter of a hotel lounge
|
71 |
+
cutting an onion with a knife over a wooden chopping board
|
72 |
+
fresh lemonade in bottles
|
73 |
+
grilling a meat on a charcoal grill
|
74 |
+
people enjoying asian cuisine
|
75 |
+
close up footage of a hot dish on a clay pot
|
76 |
+
pork ribs dish
|
77 |
+
waffle with strawberry and syrup for breakfast
|
78 |
+
tofu dish with rose garnish
|
79 |
+
uncooked pork meat
|
80 |
+
egg yolk being dumped over gourmet dish
|
81 |
+
tasty brunch dish close up
|
82 |
+
little boy pretending to eat the watermelon
|
83 |
+
slicing roasted beef
|
84 |
+
close up of a chef adding teriyaki sauce to a dish
|
85 |
+
flat lay mexican dish
|
86 |
+
a person placing an octopus dish on a marble surface
|
87 |
+
close up of tea leaves brewing in a glass kettle
|
88 |
+
adding fresh herbs to soup dish
|
89 |
+
a scoop of roasted coffee beans
|
90 |
+
fresh dim sum set up on a bamboo steam tray for cooking
|
91 |
+
a girl putting ketchup on food at the kitchen
|
92 |
+
cooking on electric stove
|
93 |
+
a woman with a slice of a pie
|
94 |
+
grapes and wine on a wooden board
|
95 |
+
man taking picture of his food
|
96 |
+
hamburger and fries on restaurant table
|
97 |
+
close up video of japanese food
|
98 |
+
a cracker sandwich with cheese filling for snack
|
99 |
+
barista preparing matcha tea
|
100 |
+
close up of onion rings being deep fried
|
VBench/prompts/prompts_per_category/human.txt
ADDED
@@ -0,0 +1,100 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
people carving a pumpkin
|
2 |
+
people sitting on a sofa
|
3 |
+
a man with a muertos face painting
|
4 |
+
man walking in the dark
|
5 |
+
men in front of their computer editing photos
|
6 |
+
men loading christmas tree on tow truck
|
7 |
+
woman washing the dishes
|
8 |
+
woman adding honey to the cinnamon rolls
|
9 |
+
two women kissing and smiling
|
10 |
+
three women looking at watercolor paintings
|
11 |
+
a family wearing paper bag masks
|
12 |
+
a family posing for the camera
|
13 |
+
a boy covering a rose flower with a dome glass
|
14 |
+
boy sitting on grass petting a dog
|
15 |
+
a girl in her tennis sportswear
|
16 |
+
a girl coloring the cardboard
|
17 |
+
silhouette of the couple during sunset
|
18 |
+
couple dancing with body paint
|
19 |
+
a child playing with water
|
20 |
+
a woman with her child sitting on a couch in the living room
|
21 |
+
a group of friend place doing hand gestures of agreement
|
22 |
+
friends having a group selfie
|
23 |
+
friends talking while on the basketball court
|
24 |
+
group of people protesting
|
25 |
+
a group of campers with a cute dog
|
26 |
+
a group of photographers taking pictures at the north western gardens in llandudno north wales
|
27 |
+
a group of students laughing and talking
|
28 |
+
a group of martial artist warming up
|
29 |
+
a person playing golf
|
30 |
+
a person walking on a wet wooden bridge
|
31 |
+
person doing a leg exercise
|
32 |
+
ice hockey athlete on rink
|
33 |
+
a young athlete training in swimming
|
34 |
+
chess player dusting a chessboard
|
35 |
+
baseball player holding his bat
|
36 |
+
a bearded man putting a vinyl record on a vinyl player
|
37 |
+
an orchestra finishes a performance
|
38 |
+
people applauding the performance of the kids
|
39 |
+
band performance at the recording studio
|
40 |
+
father and his children playing jenga game
|
41 |
+
people playing a board game
|
42 |
+
man playing a video game
|
43 |
+
a man video recording the movie in theater
|
44 |
+
man and a woman eating while watching a movie
|
45 |
+
movie crew talking together
|
46 |
+
a director explaining the movie scene
|
47 |
+
man and woman listening to music on car
|
48 |
+
man playing music
|
49 |
+
couple dancing slow dance with sun glare
|
50 |
+
a ballerina practicing in the dance studio
|
51 |
+
father and son holding hands
|
52 |
+
father and daughter talking together
|
53 |
+
a mother and her kids engaged in a video call
|
54 |
+
mother and daughter reading a book together
|
55 |
+
a mother teaching her daughter playing a violin
|
56 |
+
kid in a halloween costume
|
57 |
+
a happy kid playing the ukulele
|
58 |
+
a chef slicing a cucumber
|
59 |
+
chef wearing his gloves properly
|
60 |
+
brother and sister using hammock
|
61 |
+
girl applying sunblock to her brother
|
62 |
+
a girl pushing the chair while her sister is on the chair
|
63 |
+
colleagues talking in office building
|
64 |
+
fighter practice kicking
|
65 |
+
a woman fighter in her cosplay costume
|
66 |
+
an engineer holding blueprints while talking with her colleague
|
67 |
+
a young woman looking at vr controllers with her friend
|
68 |
+
workmates teasing a colleague in the work
|
69 |
+
a male police officer talking on the radio
|
70 |
+
teacher holding a marker while talking
|
71 |
+
teacher writing on her notebook
|
72 |
+
a young student attending her online classes
|
73 |
+
a student showing his classmates his wand
|
74 |
+
a male vendor selling fruits
|
75 |
+
a shirtless male climber
|
76 |
+
a sound engineer listening to music
|
77 |
+
female talking to a psychiatrist in a therapy session
|
78 |
+
young female activist posing with flag
|
79 |
+
a man in a hoodie and woman with a red bandana talking to each other and smiling
|
80 |
+
a medium close up of women wearing kimonos
|
81 |
+
a male interviewer listening to a person talking
|
82 |
+
a social worker having a conversation with the foster parents
|
83 |
+
a farm worker harvesting onions
|
84 |
+
worker packing street food
|
85 |
+
worker and client at barber shop
|
86 |
+
elderly man lifting kettlebell
|
87 |
+
mom assisting son in riding a bicycle
|
88 |
+
dad watching her daughter eat
|
89 |
+
young guy with vr headset
|
90 |
+
pregnant woman exercising with trainer
|
91 |
+
a fortune teller talking to a client
|
92 |
+
wizard doing a ritual on a woman
|
93 |
+
a footage of an actor on a movie scene
|
94 |
+
a man holding a best actor trophy
|
95 |
+
a singer of a music band
|
96 |
+
a young singer performing on stage
|
97 |
+
young dancer practicing at home
|
98 |
+
seller showing room to a couple
|
99 |
+
cab driver talking to passenger
|
100 |
+
a policeman talking to the car driver
|
VBench/prompts/prompts_per_category/lifestyle.txt
ADDED
@@ -0,0 +1,100 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
kids celebrating halloween at home
|
2 |
+
little boy helping mother in kitchen
|
3 |
+
video of a indoor green plant
|
4 |
+
a girl arranges a christmas garland hanging by the kitchen cabinet
|
5 |
+
candle burning in dark room
|
6 |
+
couple having fun and goofing around the bedroom
|
7 |
+
girls jumping up and down in the bedroom
|
8 |
+
woman and man in pajamas working from home
|
9 |
+
a muslim family sitting and talking in the living room
|
10 |
+
family enjoying snack time while sitting in the living room
|
11 |
+
woman holding an animal puppet and a little girl playing together at the living room
|
12 |
+
kids playing in the indoor tent
|
13 |
+
young people celebrating new year at the office
|
14 |
+
a woman writing on the sticky note in the office
|
15 |
+
a woman exercising at home over a yoga mat
|
16 |
+
girls preparing easter decorations at home
|
17 |
+
dog on floor in room
|
18 |
+
turning on a fluorescent light inside a room
|
19 |
+
colleagues talking to each other near the office windows
|
20 |
+
a woman recording herself while exercising at home
|
21 |
+
music room
|
22 |
+
different kind of tools kept in a utility room
|
23 |
+
sofa beds and other furniture
|
24 |
+
a girl finding her brother reading a book in the bedroom
|
25 |
+
an elegant ceramic plant pot and hanging plant on indoor
|
26 |
+
furniture inside a bedroom
|
27 |
+
interior design of the bar section
|
28 |
+
living room with party decoration
|
29 |
+
firewood burning in dark room
|
30 |
+
a young woman playing the ukulele at home
|
31 |
+
woman painting at home
|
32 |
+
a woman in a locker room
|
33 |
+
video of a bathroom interior
|
34 |
+
the interior design of a jewish synagogue
|
35 |
+
a woman in protective suit disinfecting the kitchen
|
36 |
+
modern minimalist home interior
|
37 |
+
modern interior design of a coffee shop
|
38 |
+
person arranging minimalist furniture
|
39 |
+
aerial shot of interior of the warehouse
|
40 |
+
a room of a manufacturing facility
|
41 |
+
interior of catholic
|
42 |
+
interior design of a restaurant
|
43 |
+
a female model in a changing room looking herself in mirror
|
44 |
+
men walking in the office hallway
|
45 |
+
people sitting in a conference room
|
46 |
+
the interior design of a shopping mall
|
47 |
+
chandeliers in room
|
48 |
+
lucerne railway station interior
|
49 |
+
a female fencer posing in a foggy room
|
50 |
+
a toolbox and a paint roller beside a huge package in a room
|
51 |
+
bedroom in hotel
|
52 |
+
a woman lying in the operating room
|
53 |
+
a chef holding and checking kitchen utensils
|
54 |
+
a couple singing in the shower room together
|
55 |
+
a woman cleaning mess in the living room
|
56 |
+
an empty meeting room with natural light
|
57 |
+
person dancing in a dark room
|
58 |
+
close up on blood in hospital room
|
59 |
+
a couple resting on their home floor
|
60 |
+
a young female staff at courier office
|
61 |
+
a man entering the gym locker room
|
62 |
+
a bored man sitting by the tv at home
|
63 |
+
woman dancing in indoor garden
|
64 |
+
rubble in the interior of an abandoned house
|
65 |
+
indoor farm in a greenhouse
|
66 |
+
man doing handstand in indoor garden
|
67 |
+
an abandoned indoor swimming pool
|
68 |
+
home decorations on top of a cabinet
|
69 |
+
graffiti art on the interior walls of an abandoned mansion
|
70 |
+
indoor wall climbing activity
|
71 |
+
sunlight inside a room
|
72 |
+
teenage girl roller skating at indoor rink
|
73 |
+
home deco with lighted
|
74 |
+
baby in the shower room
|
75 |
+
men enjoying office christmas party
|
76 |
+
a bedroom with a brick wall
|
77 |
+
actors prepping in the dressing room
|
78 |
+
kids playing at an indoor playground
|
79 |
+
a person sanitizing an office space using smoke machine
|
80 |
+
mother and daughter choosing clothes at home
|
81 |
+
a woman sitting by the indoor fire pit
|
82 |
+
man standing on the corner of the room while looking around
|
83 |
+
person assembling furniture
|
84 |
+
a family stacking cardboard boxes in a room
|
85 |
+
family having fun in the dining room
|
86 |
+
person disinfecting a room
|
87 |
+
a woman washing strawberries in the kitchen sink
|
88 |
+
modern office waiting room
|
89 |
+
close up view of a person slicing with a kitchen knife
|
90 |
+
boiling coffee on a stove in the kitchen
|
91 |
+
modern equipment used in a home studio
|
92 |
+
interior of a recording studio
|
93 |
+
people working in a call center office
|
94 |
+
band performing at a home concert
|
95 |
+
a group of people watching a concert in a room
|
96 |
+
people packing their furniture
|
97 |
+
young employees in office holding a certificate
|
98 |
+
a criminal inside a dark room handcuffed in a table
|
99 |
+
couple browsing and looking for furniture in the store
|
100 |
+
workspace at home
|
VBench/prompts/prompts_per_category/plant.txt
ADDED
@@ -0,0 +1,100 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
video of a indoor green plant
|
2 |
+
close up view of a plant
|
3 |
+
close up shot of a burning plant
|
4 |
+
plucking leaves from plant
|
5 |
+
a plant on gold pot with glass lid
|
6 |
+
a branch of a tree and a plant
|
7 |
+
a leafless tree
|
8 |
+
close up shot of fern leaf
|
9 |
+
close up video of strawberry plant
|
10 |
+
plant with blooming flowers
|
11 |
+
close up video of flower petals
|
12 |
+
watering yellow plant
|
13 |
+
beautiful flower decoration
|
14 |
+
cannabis flower in a jar
|
15 |
+
a footage of the tree leaves
|
16 |
+
a red leaf plant
|
17 |
+
close up view of a white christmas tree
|
18 |
+
snow pouring on a tree
|
19 |
+
close up shot of white flowers on the tree
|
20 |
+
leaves in the trees daytime
|
21 |
+
a dead tree lying on a grass field
|
22 |
+
tree branches in a flowing river
|
23 |
+
purple flowers with leaves
|
24 |
+
a coconut tree by the house
|
25 |
+
close up on flower in winter
|
26 |
+
bamboo leaves backlit by the sun
|
27 |
+
close up video of a wet flower
|
28 |
+
a man putting a flower in a box
|
29 |
+
dropping flower petals on a wooden bowl
|
30 |
+
a close up shot of gypsophila flower
|
31 |
+
variety of succulent plants on a garden
|
32 |
+
variety of trees and plants in a botanical garden
|
33 |
+
forest of deciduous trees
|
34 |
+
a stack of dried leaves burning in a forest
|
35 |
+
tall forest trees on a misty morning
|
36 |
+
close up view of dewdrops on a leaf
|
37 |
+
close up view of white petaled flower
|
38 |
+
removing a pineapple leaf
|
39 |
+
a dragonfly perched on a leaf
|
40 |
+
butterfly pollinating flower
|
41 |
+
person visiting and checking a corn plant
|
42 |
+
woman picking beans from a plant
|
43 |
+
woman plucking mint leaves
|
44 |
+
single tree in the middle of farmland
|
45 |
+
a plant on a soil
|
46 |
+
drone footage of a tree on farm field
|
47 |
+
a tractor harvesting lavender flower
|
48 |
+
people putting christmas ornaments on a christmas tree
|
49 |
+
jack o lantern hanging on a tree
|
50 |
+
tree with halloween decoration
|
51 |
+
flower field near the waterfall
|
52 |
+
truck carrying the tree logs
|
53 |
+
raindrops falling on leaves
|
54 |
+
shot of a palm tree swaying with the wind
|
55 |
+
squirrels on a tree branch
|
56 |
+
person holding a flower
|
57 |
+
a fallen tree trunk
|
58 |
+
tree with golden leaves
|
59 |
+
cherry tree
|
60 |
+
wind blows through leaves of the tree in autumn
|
61 |
+
a leaf on a glass
|
62 |
+
the long trunks of tall trees in the forest
|
63 |
+
trees in the forest during sunny day
|
64 |
+
close up video of tree bark
|
65 |
+
reflection of tree branches
|
66 |
+
trunks of many trees in the forest
|
67 |
+
tree leaves providing shades from the sun
|
68 |
+
leaves swaying in the wind
|
69 |
+
low angle shot of baobab tree
|
70 |
+
bare trees in forest
|
71 |
+
a plant surrounded by fallen leaves
|
72 |
+
a couple preparing food and pruning a plant
|
73 |
+
a man cutting a tree bark
|
74 |
+
oranges on a tree branch
|
75 |
+
plant connected on the stones
|
76 |
+
video of a sawmill machine cutting tree log
|
77 |
+
women drying flower petals
|
78 |
+
macro view of an agave plant
|
79 |
+
a video of a person tying a plant on a string
|
80 |
+
green moss in forest nature
|
81 |
+
coconut tree near sea under blue sky
|
82 |
+
the canopy of a coconut tree
|
83 |
+
a man leaning on a tree at the beach
|
84 |
+
a full grown plant on a pot
|
85 |
+
candle wax dripping on flower petals
|
86 |
+
close up of leaves in autumn
|
87 |
+
a woman opening a book with a flower inside
|
88 |
+
a man holding leaves looking at the camera
|
89 |
+
a shadow of a swaying plant
|
90 |
+
a tree and concrete structure under a blue and cloudy sky
|
91 |
+
trimming excess leaves on a potted plant
|
92 |
+
the changing color of the tree leaves during autumn season
|
93 |
+
a gooseberry tree swayed by the wind
|
94 |
+
forest trees and a medieval castle at sunset
|
95 |
+
woman cut down tree
|
96 |
+
an old oak tree in a park across the street from a hotel
|
97 |
+
wild flowers growing in a forest ground
|
98 |
+
a mossy fountain and green plants in a botanical garden
|
99 |
+
mansion with beautiful garden
|
100 |
+
ants on a dragon fruit flower
|
VBench/prompts/prompts_per_category/scenery.txt
ADDED
@@ -0,0 +1,100 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
scenery of desert landscape
|
2 |
+
landscape agriculture farm tractor
|
3 |
+
burning slash piles in the forest
|
4 |
+
graveyard at sunset
|
5 |
+
view of a jack o lantern with pumpkins in a smoky garden
|
6 |
+
sun view through a spider web
|
7 |
+
view of the sea from an abandoned building
|
8 |
+
close up view of a full moon
|
9 |
+
close up view of lighted candles
|
10 |
+
close up view of swaying white flowers and leaves
|
11 |
+
scenery of a relaxing beach
|
12 |
+
selective focus video of grass during sunny day
|
13 |
+
aerial view of brown dry landscape
|
14 |
+
fireworks display in the sky at night
|
15 |
+
a bonfire near river
|
16 |
+
mountain view
|
17 |
+
waterfalls in between mountain
|
18 |
+
a picturesque view of nature
|
19 |
+
exotic view of a riverfront city
|
20 |
+
tall trees in the forest under the clear sky
|
21 |
+
snow on branches in forest
|
22 |
+
stream in the nature
|
23 |
+
an airplane flying above the sea of clouds
|
24 |
+
scenic video of sunset
|
25 |
+
view of houses with bush fence under a blue and cloudy sky
|
26 |
+
scenic view from wooden pathway
|
27 |
+
scenic view of a tropical beach
|
28 |
+
drone footage of waves crashing on beach shore
|
29 |
+
a scenic view of the golden hour at norway
|
30 |
+
time lapse video of foggy mountain forest
|
31 |
+
brown mountain during fall season
|
32 |
+
video of ocean during daytime
|
33 |
+
boat sailing in the ocean
|
34 |
+
top view of yachts
|
35 |
+
beautiful scenery of flowing waterfalls and river
|
36 |
+
wild ducks paddling on the lake surface
|
37 |
+
a relaxing scenery of beach view under cloudy sky
|
38 |
+
natural rock formations on beach under cloudy sky
|
39 |
+
a palm tree against blue sky
|
40 |
+
video of sailboat on a lake during sunset
|
41 |
+
aerial view of snow piles
|
42 |
+
time lapse of a sunset sky in the countryside
|
43 |
+
aerial footage of a statue
|
44 |
+
time lapse video of a farm during sunset
|
45 |
+
clouds formation in the sky at sunset
|
46 |
+
aerial shot of a village
|
47 |
+
drone shot of a beautiful sunrise at the mountains
|
48 |
+
time lapse video of foggy morning during sunrise
|
49 |
+
sun shining between tree leaves at sunrise
|
50 |
+
video of lake during dawn
|
51 |
+
vehicles traveling on roadway under cloudy sky
|
52 |
+
view of golden domed church
|
53 |
+
a monument under the blue sky
|
54 |
+
firecrackers in the sky
|
55 |
+
view of fruit signage in the farm
|
56 |
+
a dark clouds over shadowing the full moon
|
57 |
+
view of the amazon river
|
58 |
+
a big river swamp in a dense forest
|
59 |
+
a blooming cherry blossom tree under a blue sky with white clouds
|
60 |
+
a river waterfall cascading down the plunge basin
|
61 |
+
flooded landscape with palm trees
|
62 |
+
a blurry waterfall background
|
63 |
+
waterfall in the mountains
|
64 |
+
aerial footage of a city at night
|
65 |
+
pond by small waterfall in forest
|
66 |
+
aerial view of farmlands at the bay of lake
|
67 |
+
rice terraces in the countryside
|
68 |
+
a highway built across an agricultural area in the countryside
|
69 |
+
gloomy morning in the countryside
|
70 |
+
drone shot of an abandoned coliseum on a snowy mountain top
|
71 |
+
boat sailing in the middle of ocean
|
72 |
+
drone shot of the grass field
|
73 |
+
natural landscape of mountain and sea with islets developed into a community
|
74 |
+
aerial view of zaporizhia in ukraine
|
75 |
+
aerial footage of a herd
|
76 |
+
an aerial footage of a red sky
|
77 |
+
grass and plants growing in the remains of an abandoned house
|
78 |
+
view from hill on city
|
79 |
+
aerial view on orthodox church
|
80 |
+
aerial view of bay in croatia
|
81 |
+
a footage of a frozen river
|
82 |
+
overlooking view of a city at daylight
|
83 |
+
view outside the cemetery
|
84 |
+
clear sky with moon over meadow
|
85 |
+
clouds over railway
|
86 |
+
aerial footage of moving vehicles on the road at night
|
87 |
+
aerial view of town and park
|
88 |
+
top view of skyscrapers
|
89 |
+
top view of the empire state building in manhattan
|
90 |
+
top view of the central park in new york city
|
91 |
+
sheep running in a grass field
|
92 |
+
clear sky over factory
|
93 |
+
smoke and fire in birds eye view
|
94 |
+
view of a pathway with snow melting on its side
|
95 |
+
ferry under bridge on river near city in malaysia
|
96 |
+
mountain slopes covered in green vegetation
|
97 |
+
panoramic view of a town surrounded by snow covered mountains
|
98 |
+
aerial view of a palace
|
99 |
+
top view of vehicles driving on the intersection
|
100 |
+
a graveyard by a church in a mountain landscape
|
VBench/prompts/prompts_per_category/vehicles.txt
ADDED
@@ -0,0 +1,100 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
a modern railway station in malaysia use for public transportation
|
2 |
+
drone footage of amsterdam metro station
|
3 |
+
train arriving at a station
|
4 |
+
red vehicle driving on field
|
5 |
+
close up view of flashing emergency vehicle lighting
|
6 |
+
vehicle with fertilizer on field
|
7 |
+
a highway built across an agricultural area in the countryside
|
8 |
+
drone footage of motorcycles driving on country road between agricultural fields
|
9 |
+
a road in the woods under fog
|
10 |
+
footage of a car driving through a wheat field
|
11 |
+
vehicle stops for an ambulance passing through city traffic
|
12 |
+
emergency vehicle parked outside the casino
|
13 |
+
zombies attacking a woman and a boy inside a car
|
14 |
+
woman seating inside the car while chewing
|
15 |
+
video of passengers riding a double decker bus during night
|
16 |
+
traffic in london street at night
|
17 |
+
elderly couple checking engine of automobile
|
18 |
+
a green vintage automobile with an open hood parked in a parking area
|
19 |
+
close up of a prototype automobile with exposed engine on the back seat of the car
|
20 |
+
aerial view of road in forest
|
21 |
+
train departing from station
|
22 |
+
aerial view of a train passing by a bridge
|
23 |
+
video of a train tracks
|
24 |
+
video footage of a subway
|
25 |
+
video of blinking traffic lights
|
26 |
+
couple walking out on the subway
|
27 |
+
time lapse of a subway tunnel
|
28 |
+
monitor board inside the subway
|
29 |
+
metro train at night
|
30 |
+
zoom in video of a tram passing by city
|
31 |
+
young man using laptop in the tram
|
32 |
+
man reading a book at bus stop
|
33 |
+
close up shot of a moving taxi
|
34 |
+
night travel in london street on a public bus
|
35 |
+
red bus in a rainy city
|
36 |
+
flow of traffic in the city
|
37 |
+
close up shot of a yellow taxi turning left
|
38 |
+
two women calling for a taxi
|
39 |
+
drone view of an illuminated bridge across a river
|
40 |
+
policeman in police car talking on radio
|
41 |
+
airplane taking off at night
|
42 |
+
view through window in airplane
|
43 |
+
an airplane in the sky
|
44 |
+
helicopter landing on the street
|
45 |
+
a pilot getting out of a helicopter
|
46 |
+
a helicopter flying under blue sky
|
47 |
+
boat sailing in the middle of the ocean
|
48 |
+
girl playing with a toy boat
|
49 |
+
silhouette of a boat on sea during golden hour
|
50 |
+
a boat travelling around the lake
|
51 |
+
road on mountain ridge
|
52 |
+
ship sailing on danube river
|
53 |
+
slow motion video of a ship water trail in the sea
|
54 |
+
drone footage of a wreck ship on shore
|
55 |
+
a white yacht traveling on a river and passing under the bridge
|
56 |
+
female teenagers drinking champagne in the yacht
|
57 |
+
video of yacht sailing in the ocean
|
58 |
+
red combine harvester on road on field
|
59 |
+
a woman sitting on a bicycle while using a mobile phone
|
60 |
+
a woman sitting on a motorcycle looking around
|
61 |
+
three teenagers fixing a bicycle
|
62 |
+
a woman in a halloween costume posing on a motorcycle
|
63 |
+
a parked motorcycle on a foggy roadside
|
64 |
+
cable car near sea shore
|
65 |
+
a truck travelling in the road
|
66 |
+
footage of the road without any traffic
|
67 |
+
a road sign
|
68 |
+
love padlocks on a bridge
|
69 |
+
camera moving at highway construction site
|
70 |
+
vehicles driving on highway
|
71 |
+
a motorbike on highway at timelapse mode
|
72 |
+
point of view of a car driving through a tunnel
|
73 |
+
time lapse of heavy traffic on an avenue
|
74 |
+
ferry boat on city canal
|
75 |
+
black vintage car in museum
|
76 |
+
a zigzag road across a forest
|
77 |
+
people crossing the road
|
78 |
+
video of a kayak boat in a river
|
79 |
+
a person paddling a wooden boat in a lake
|
80 |
+
a car charging in the parking area
|
81 |
+
cars parked on the road
|
82 |
+
footage of the street with people and vehicle passing by in the rain
|
83 |
+
traffic on busy city street
|
84 |
+
a woman getting out of the car to walk with their dog
|
85 |
+
yacht sailing through the ocean
|
86 |
+
people in queue to military ship
|
87 |
+
man wearing motorcycle helmet looking at the camera
|
88 |
+
empty seats in the bus
|
89 |
+
empty boat on the water
|
90 |
+
cargo train traveling on the mountainside
|
91 |
+
cruise ship in harbor
|
92 |
+
counting down at traffic lights
|
93 |
+
pressing the car ignition
|
94 |
+
fire truck driving on the road
|
95 |
+
a footage of a broken bicycle
|
96 |
+
drone footage of an ambulance on the road
|
97 |
+
slow motion footage of a racing car
|
98 |
+
ship sailing on sea against sunset
|
99 |
+
big cargo ship passing on the shore
|
100 |
+
back view of man and woman walking on unpaved road
|
VBench/prompts/prompts_per_dimension/appearance_style.txt
ADDED
@@ -0,0 +1,90 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
A beautiful coastal beach in spring, waves lapping on sand, Van Gogh style
|
2 |
+
A beautiful coastal beach in spring, waves lapping on sand, oil painting
|
3 |
+
A beautiful coastal beach in spring, waves lapping on sand by Hokusai, in the style of Ukiyo
|
4 |
+
A beautiful coastal beach in spring, waves lapping on sand, black and white
|
5 |
+
A beautiful coastal beach in spring, waves lapping on sand, pixel art
|
6 |
+
A beautiful coastal beach in spring, waves lapping on sand, in cyberpunk style
|
7 |
+
A beautiful coastal beach in spring, waves lapping on sand, animated style
|
8 |
+
A beautiful coastal beach in spring, waves lapping on sand, watercolor painting
|
9 |
+
A beautiful coastal beach in spring, waves lapping on sand, surrealism style
|
10 |
+
The bund Shanghai, Van Gogh style
|
11 |
+
The bund Shanghai, oil painting
|
12 |
+
The bund Shanghai by Hokusai, in the style of Ukiyo
|
13 |
+
The bund Shanghai, black and white
|
14 |
+
The bund Shanghai, pixel art
|
15 |
+
The bund Shanghai, in cyberpunk style
|
16 |
+
The bund Shanghai, animated style
|
17 |
+
The bund Shanghai, watercolor painting
|
18 |
+
The bund Shanghai, surrealism style
|
19 |
+
a shark is swimming in the ocean, Van Gogh style
|
20 |
+
a shark is swimming in the ocean, oil painting
|
21 |
+
a shark is swimming in the ocean by Hokusai, in the style of Ukiyo
|
22 |
+
a shark is swimming in the ocean, black and white
|
23 |
+
a shark is swimming in the ocean, pixel art
|
24 |
+
a shark is swimming in the ocean, in cyberpunk style
|
25 |
+
a shark is swimming in the ocean, animated style
|
26 |
+
a shark is swimming in the ocean, watercolor painting
|
27 |
+
a shark is swimming in the ocean, surrealism style
|
28 |
+
A panda drinking coffee in a cafe in Paris, Van Gogh style
|
29 |
+
A panda drinking coffee in a cafe in Paris, oil painting
|
30 |
+
A panda drinking coffee in a cafe in Paris by Hokusai, in the style of Ukiyo
|
31 |
+
A panda drinking coffee in a cafe in Paris, black and white
|
32 |
+
A panda drinking coffee in a cafe in Paris, pixel art
|
33 |
+
A panda drinking coffee in a cafe in Paris, in cyberpunk style
|
34 |
+
A panda drinking coffee in a cafe in Paris, animated style
|
35 |
+
A panda drinking coffee in a cafe in Paris, watercolor painting
|
36 |
+
A panda drinking coffee in a cafe in Paris, surrealism style
|
37 |
+
A cute happy Corgi playing in park, sunset, Van Gogh style
|
38 |
+
A cute happy Corgi playing in park, sunset, oil painting
|
39 |
+
A cute happy Corgi playing in park, sunset by Hokusai, in the style of Ukiyo
|
40 |
+
A cute happy Corgi playing in park, sunset, black and white
|
41 |
+
A cute happy Corgi playing in park, sunset, pixel art
|
42 |
+
A cute happy Corgi playing in park, sunset, in cyberpunk style
|
43 |
+
A cute happy Corgi playing in park, sunset, animated style
|
44 |
+
A cute happy Corgi playing in park, sunset, watercolor painting
|
45 |
+
A cute happy Corgi playing in park, sunset, surrealism style
|
46 |
+
Gwen Stacy reading a book, Van Gogh style
|
47 |
+
Gwen Stacy reading a book, oil painting
|
48 |
+
Gwen Stacy reading a book by Hokusai, in the style of Ukiyo
|
49 |
+
Gwen Stacy reading a book, black and white
|
50 |
+
Gwen Stacy reading a book, pixel art
|
51 |
+
Gwen Stacy reading a book, in cyberpunk style
|
52 |
+
Gwen Stacy reading a book, animated style
|
53 |
+
Gwen Stacy reading a book, watercolor painting
|
54 |
+
Gwen Stacy reading a book, surrealism style
|
55 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, Van Gogh style
|
56 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, oil painting
|
57 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background by Hokusai, in the style of Ukiyo
|
58 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, black and white
|
59 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, pixel art
|
60 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, in cyberpunk style
|
61 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, animated style
|
62 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, watercolor painting
|
63 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background, surrealism style
|
64 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, Van Gogh style
|
65 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, oil painting
|
66 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas by Hokusai, in the style of Ukiyo
|
67 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, black and white
|
68 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, pixel art
|
69 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, in cyberpunk style
|
70 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, animated style
|
71 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, watercolor painting
|
72 |
+
A couple in formal evening wear going home get caught in a heavy downpour with umbrellas, surrealism style
|
73 |
+
An astronaut flying in space, Van Gogh style
|
74 |
+
An astronaut flying in space, oil painting
|
75 |
+
An astronaut flying in space by Hokusai, in the style of Ukiyo
|
76 |
+
An astronaut flying in space, black and white
|
77 |
+
An astronaut flying in space, pixel art
|
78 |
+
An astronaut flying in space, in cyberpunk style
|
79 |
+
An astronaut flying in space, animated style
|
80 |
+
An astronaut flying in space, watercolor painting
|
81 |
+
An astronaut flying in space, surrealism style
|
82 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, Van Gogh style
|
83 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, oil painting
|
84 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks by Hokusai, in the style of Ukiyo
|
85 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, black and white
|
86 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, pixel art
|
87 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, in cyberpunk style
|
88 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, animated style
|
89 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, watercolor painting
|
90 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks, surrealism style
|
VBench/prompts/prompts_per_dimension/color.txt
ADDED
@@ -0,0 +1,85 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
a red bicycle
|
2 |
+
a green bicycle
|
3 |
+
a blue bicycle
|
4 |
+
a yellow bicycle
|
5 |
+
an orange bicycle
|
6 |
+
a purple bicycle
|
7 |
+
a pink bicycle
|
8 |
+
a black bicycle
|
9 |
+
a white bicycle
|
10 |
+
a red car
|
11 |
+
a green car
|
12 |
+
a blue car
|
13 |
+
a yellow car
|
14 |
+
an orange car
|
15 |
+
a purple car
|
16 |
+
a pink car
|
17 |
+
a black car
|
18 |
+
a white car
|
19 |
+
a red bird
|
20 |
+
a green bird
|
21 |
+
a blue bird
|
22 |
+
a yellow bird
|
23 |
+
an orange bird
|
24 |
+
a purple bird
|
25 |
+
a pink bird
|
26 |
+
a black bird
|
27 |
+
a white bird
|
28 |
+
a black cat
|
29 |
+
a white cat
|
30 |
+
an orange cat
|
31 |
+
a yellow cat
|
32 |
+
a red umbrella
|
33 |
+
a green umbrella
|
34 |
+
a blue umbrella
|
35 |
+
a yellow umbrella
|
36 |
+
an orange umbrella
|
37 |
+
a purple umbrella
|
38 |
+
a pink umbrella
|
39 |
+
a black umbrella
|
40 |
+
a white umbrella
|
41 |
+
a red suitcase
|
42 |
+
a green suitcase
|
43 |
+
a blue suitcase
|
44 |
+
a yellow suitcase
|
45 |
+
an orange suitcase
|
46 |
+
a purple suitcase
|
47 |
+
a pink suitcase
|
48 |
+
a black suitcase
|
49 |
+
a white suitcase
|
50 |
+
a red bowl
|
51 |
+
a green bowl
|
52 |
+
a blue bowl
|
53 |
+
a yellow bowl
|
54 |
+
an orange bowl
|
55 |
+
a purple bowl
|
56 |
+
a pink bowl
|
57 |
+
a black bowl
|
58 |
+
a white bowl
|
59 |
+
a red chair
|
60 |
+
a green chair
|
61 |
+
a blue chair
|
62 |
+
a yellow chair
|
63 |
+
an orange chair
|
64 |
+
a purple chair
|
65 |
+
a pink chair
|
66 |
+
a black chair
|
67 |
+
a white chair
|
68 |
+
a red clock
|
69 |
+
a green clock
|
70 |
+
a blue clock
|
71 |
+
a yellow clock
|
72 |
+
an orange clock
|
73 |
+
a purple clock
|
74 |
+
a pink clock
|
75 |
+
a black clock
|
76 |
+
a white clock
|
77 |
+
a red vase
|
78 |
+
a green vase
|
79 |
+
a blue vase
|
80 |
+
a yellow vase
|
81 |
+
an orange vase
|
82 |
+
a purple vase
|
83 |
+
a pink vase
|
84 |
+
a black vase
|
85 |
+
a white vase
|
VBench/prompts/prompts_per_dimension/human_action.txt
ADDED
@@ -0,0 +1,100 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
A person is riding a bike
|
2 |
+
A person is marching
|
3 |
+
A person is roller skating
|
4 |
+
A person is tasting beer
|
5 |
+
A person is clapping
|
6 |
+
A person is drawing
|
7 |
+
A person is petting animal (not cat)
|
8 |
+
A person is eating watermelon
|
9 |
+
A person is playing harp
|
10 |
+
A person is wrestling
|
11 |
+
A person is riding scooter
|
12 |
+
A person is sweeping floor
|
13 |
+
A person is skateboarding
|
14 |
+
A person is dunking basketball
|
15 |
+
A person is playing flute
|
16 |
+
A person is stretching leg
|
17 |
+
A person is tying tie
|
18 |
+
A person is skydiving
|
19 |
+
A person is shooting goal (soccer)
|
20 |
+
A person is playing piano
|
21 |
+
A person is finger snapping
|
22 |
+
A person is canoeing or kayaking
|
23 |
+
A person is laughing
|
24 |
+
A person is digging
|
25 |
+
A person is clay pottery making
|
26 |
+
A person is shooting basketball
|
27 |
+
A person is bending back
|
28 |
+
A person is shaking hands
|
29 |
+
A person is bandaging
|
30 |
+
A person is push up
|
31 |
+
A person is catching or throwing frisbee
|
32 |
+
A person is playing trumpet
|
33 |
+
A person is flying kite
|
34 |
+
A person is filling eyebrows
|
35 |
+
A person is shuffling cards
|
36 |
+
A person is folding clothes
|
37 |
+
A person is smoking
|
38 |
+
A person is tai chi
|
39 |
+
A person is squat
|
40 |
+
A person is playing controller
|
41 |
+
A person is throwing axe
|
42 |
+
A person is giving or receiving award
|
43 |
+
A person is air drumming
|
44 |
+
A person is taking a shower
|
45 |
+
A person is planting trees
|
46 |
+
A person is sharpening knives
|
47 |
+
A person is robot dancing
|
48 |
+
A person is rock climbing
|
49 |
+
A person is hula hooping
|
50 |
+
A person is writing
|
51 |
+
A person is bungee jumping
|
52 |
+
A person is pushing cart
|
53 |
+
A person is cleaning windows
|
54 |
+
A person is cutting watermelon
|
55 |
+
A person is cheerleading
|
56 |
+
A person is washing hands
|
57 |
+
A person is ironing
|
58 |
+
A person is cutting nails
|
59 |
+
A person is hugging
|
60 |
+
A person is trimming or shaving beard
|
61 |
+
A person is jogging
|
62 |
+
A person is making bed
|
63 |
+
A person is washing dishes
|
64 |
+
A person is grooming dog
|
65 |
+
A person is doing laundry
|
66 |
+
A person is knitting
|
67 |
+
A person is reading book
|
68 |
+
A person is baby waking up
|
69 |
+
A person is massaging legs
|
70 |
+
A person is brushing teeth
|
71 |
+
A person is crawling baby
|
72 |
+
A person is motorcycling
|
73 |
+
A person is driving car
|
74 |
+
A person is sticking tongue out
|
75 |
+
A person is shaking head
|
76 |
+
A person is sword fighting
|
77 |
+
A person is doing aerobics
|
78 |
+
A person is strumming guitar
|
79 |
+
A person is riding or walking with horse
|
80 |
+
A person is archery
|
81 |
+
A person is catching or throwing baseball
|
82 |
+
A person is playing chess
|
83 |
+
A person is rock scissors paper
|
84 |
+
A person is using computer
|
85 |
+
A person is arranging flowers
|
86 |
+
A person is bending metal
|
87 |
+
A person is ice skating
|
88 |
+
A person is climbing a rope
|
89 |
+
A person is crying
|
90 |
+
A person is dancing ballet
|
91 |
+
A person is getting a haircut
|
92 |
+
A person is running on treadmill
|
93 |
+
A person is kissing
|
94 |
+
A person is counting money
|
95 |
+
A person is barbequing
|
96 |
+
A person is peeling apples
|
97 |
+
A person is milking cow
|
98 |
+
A person is shining shoes
|
99 |
+
A person is making snowman
|
100 |
+
A person is sailing
|
VBench/prompts/prompts_per_dimension/multiple_objects.txt
ADDED
@@ -0,0 +1,82 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
a bird and a cat
|
2 |
+
a cat and a dog
|
3 |
+
a dog and a horse
|
4 |
+
a horse and a sheep
|
5 |
+
a sheep and a cow
|
6 |
+
a cow and an elephant
|
7 |
+
an elephant and a bear
|
8 |
+
a bear and a zebra
|
9 |
+
a zebra and a giraffe
|
10 |
+
a giraffe and a bird
|
11 |
+
a chair and a couch
|
12 |
+
a couch and a potted plant
|
13 |
+
a potted plant and a tv
|
14 |
+
a tv and a laptop
|
15 |
+
a laptop and a remote
|
16 |
+
a remote and a keyboard
|
17 |
+
a keyboard and a cell phone
|
18 |
+
a cell phone and a book
|
19 |
+
a book and a clock
|
20 |
+
a clock and a backpack
|
21 |
+
a backpack and an umbrella
|
22 |
+
an umbrella and a handbag
|
23 |
+
a handbag and a tie
|
24 |
+
a tie and a suitcase
|
25 |
+
a suitcase and a vase
|
26 |
+
a vase and scissors
|
27 |
+
scissors and a teddy bear
|
28 |
+
a teddy bear and a frisbee
|
29 |
+
a frisbee and skis
|
30 |
+
skis and a snowboard
|
31 |
+
a snowboard and a sports ball
|
32 |
+
a sports ball and a kite
|
33 |
+
a kite and a baseball bat
|
34 |
+
a baseball bat and a baseball glove
|
35 |
+
a baseball glove and a skateboard
|
36 |
+
a skateboard and a surfboard
|
37 |
+
a surfboard and a tennis racket
|
38 |
+
a tennis racket and a bottle
|
39 |
+
a bottle and a chair
|
40 |
+
an airplane and a train
|
41 |
+
a train and a boat
|
42 |
+
a boat and an airplane
|
43 |
+
a bicycle and a car
|
44 |
+
a car and a motorcycle
|
45 |
+
a motorcycle and a bus
|
46 |
+
a bus and a traffic light
|
47 |
+
a traffic light and a fire hydrant
|
48 |
+
a fire hydrant and a stop sign
|
49 |
+
a stop sign and a parking meter
|
50 |
+
a parking meter and a truck
|
51 |
+
a truck and a bicycle
|
52 |
+
a toilet and a hair drier
|
53 |
+
a hair drier and a toothbrush
|
54 |
+
a toothbrush and a sink
|
55 |
+
a sink and a toilet
|
56 |
+
a wine glass and a chair
|
57 |
+
a cup and a couch
|
58 |
+
a fork and a potted plant
|
59 |
+
a knife and a tv
|
60 |
+
a spoon and a laptop
|
61 |
+
a bowl and a remote
|
62 |
+
a banana and a keyboard
|
63 |
+
an apple and a cell phone
|
64 |
+
a sandwich and a book
|
65 |
+
an orange and a clock
|
66 |
+
broccoli and a backpack
|
67 |
+
a carrot and an umbrella
|
68 |
+
a hot dog and a handbag
|
69 |
+
a pizza and a tie
|
70 |
+
a donut and a suitcase
|
71 |
+
a cake and a vase
|
72 |
+
an oven and scissors
|
73 |
+
a toaster and a teddy bear
|
74 |
+
a microwave and a frisbee
|
75 |
+
a refrigerator and skis
|
76 |
+
a bicycle and an airplane
|
77 |
+
a car and a train
|
78 |
+
a motorcycle and a boat
|
79 |
+
a person and a toilet
|
80 |
+
a person and a hair drier
|
81 |
+
a person and a toothbrush
|
82 |
+
a person and a sink
|
VBench/prompts/prompts_per_dimension/object_class.txt
ADDED
@@ -0,0 +1,79 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
a person
|
2 |
+
a bicycle
|
3 |
+
a car
|
4 |
+
a motorcycle
|
5 |
+
an airplane
|
6 |
+
a bus
|
7 |
+
a train
|
8 |
+
a truck
|
9 |
+
a boat
|
10 |
+
a traffic light
|
11 |
+
a fire hydrant
|
12 |
+
a stop sign
|
13 |
+
a parking meter
|
14 |
+
a bench
|
15 |
+
a bird
|
16 |
+
a cat
|
17 |
+
a dog
|
18 |
+
a horse
|
19 |
+
a sheep
|
20 |
+
a cow
|
21 |
+
an elephant
|
22 |
+
a bear
|
23 |
+
a zebra
|
24 |
+
a giraffe
|
25 |
+
a backpack
|
26 |
+
an umbrella
|
27 |
+
a handbag
|
28 |
+
a tie
|
29 |
+
a suitcase
|
30 |
+
a frisbee
|
31 |
+
skis
|
32 |
+
a snowboard
|
33 |
+
a sports ball
|
34 |
+
a kite
|
35 |
+
a baseball bat
|
36 |
+
a baseball glove
|
37 |
+
a skateboard
|
38 |
+
a surfboard
|
39 |
+
a tennis racket
|
40 |
+
a bottle
|
41 |
+
a wine glass
|
42 |
+
a cup
|
43 |
+
a fork
|
44 |
+
a knife
|
45 |
+
a spoon
|
46 |
+
a bowl
|
47 |
+
a banana
|
48 |
+
an apple
|
49 |
+
a sandwich
|
50 |
+
an orange
|
51 |
+
broccoli
|
52 |
+
a carrot
|
53 |
+
a hot dog
|
54 |
+
a pizza
|
55 |
+
a donut
|
56 |
+
a cake
|
57 |
+
a chair
|
58 |
+
a couch
|
59 |
+
a potted plant
|
60 |
+
a bed
|
61 |
+
a dining table
|
62 |
+
a toilet
|
63 |
+
a tv
|
64 |
+
a laptop
|
65 |
+
a remote
|
66 |
+
a keyboard
|
67 |
+
a cell phone
|
68 |
+
a microwave
|
69 |
+
an oven
|
70 |
+
a toaster
|
71 |
+
a sink
|
72 |
+
a refrigerator
|
73 |
+
a book
|
74 |
+
a clock
|
75 |
+
a vase
|
76 |
+
scissors
|
77 |
+
a teddy bear
|
78 |
+
a hair drier
|
79 |
+
a toothbrush
|
VBench/prompts/prompts_per_dimension/overall_consistency.txt
ADDED
@@ -0,0 +1,93 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
Close up of grapes on a rotating table.
|
2 |
+
Turtle swimming in ocean.
|
3 |
+
A storm trooper vacuuming the beach.
|
4 |
+
A panda standing on a surfboard in the ocean in sunset.
|
5 |
+
An astronaut feeding ducks on a sunny afternoon, reflection from the water.
|
6 |
+
Two pandas discussing an academic paper.
|
7 |
+
Sunset time lapse at the beach with moving clouds and colors in the sky.
|
8 |
+
A fat rabbit wearing a purple robe walking through a fantasy landscape.
|
9 |
+
A koala bear playing piano in the forest.
|
10 |
+
An astronaut flying in space.
|
11 |
+
Fireworks.
|
12 |
+
An animated painting of fluffy white clouds moving in sky.
|
13 |
+
Flying through fantasy landscapes.
|
14 |
+
A bigfoot walking in the snowstorm.
|
15 |
+
A squirrel eating a burger.
|
16 |
+
A cat wearing sunglasses and working as a lifeguard at a pool.
|
17 |
+
Snow rocky mountains peaks canyon. snow blanketed rocky mountains surround and shadow deep canyons. the canyons twist and bend through the high elevated mountain peaks.
|
18 |
+
Splash of turquoise water in extreme slow motion, alpha channel included.
|
19 |
+
an ice cream is melting on the table.
|
20 |
+
a drone flying over a snowy forest.
|
21 |
+
a shark is swimming in the ocean.
|
22 |
+
Aerial panoramic video from a drone of a fantasy land.
|
23 |
+
a teddy bear is swimming in the ocean.
|
24 |
+
time lapse of sunrise on mars.
|
25 |
+
golden fish swimming in the ocean.
|
26 |
+
An artist brush painting on a canvas close up.
|
27 |
+
A drone view of celebration with Christmas tree and fireworks, starry sky - background.
|
28 |
+
happy dog wearing a yellow turtleneck, studio, portrait, facing camera, dark background
|
29 |
+
Origami dancers in white paper, 3D render, on white background, studio shot, dancing modern dance.
|
30 |
+
Campfire at night in a snowy forest with starry sky in the background.
|
31 |
+
a fantasy landscape
|
32 |
+
A 3D model of a 1800s victorian house.
|
33 |
+
this is how I do makeup in the morning.
|
34 |
+
A raccoon that looks like a turtle, digital art.
|
35 |
+
Robot dancing in Times Square.
|
36 |
+
Busy freeway at night.
|
37 |
+
Balloon full of water exploding in extreme slow motion.
|
38 |
+
An astronaut is riding a horse in the space in a photorealistic style.
|
39 |
+
Macro slo-mo. Slow motion cropped closeup of roasted coffee beans falling into an empty bowl.
|
40 |
+
Sewing machine, old sewing machine working.
|
41 |
+
Motion colour drop in water, ink swirling in water, colourful ink in water, abstraction fancy dream cloud of ink.
|
42 |
+
Few big purple plums rotating on the turntable. water drops appear on the skin during rotation. isolated on the white background. close-up. macro.
|
43 |
+
Vampire makeup face of beautiful girl, red contact lenses.
|
44 |
+
Ashtray full of butts on table, smoke flowing on black background, close-up
|
45 |
+
Pacific coast, carmel by the sea ocean and waves.
|
46 |
+
A teddy bear is playing drum kit in NYC Times Square.
|
47 |
+
A corgi is playing drum kit.
|
48 |
+
An Iron man is playing the electronic guitar, high electronic guitar.
|
49 |
+
A raccoon is playing the electronic guitar.
|
50 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background by Vincent van Gogh
|
51 |
+
A corgi's head depicted as an explosion of a nebula
|
52 |
+
A fantasy landscape
|
53 |
+
A future where humans have achieved teleportation technology
|
54 |
+
A jellyfish floating through the ocean, with bioluminescent tentacles
|
55 |
+
A Mars rover moving on Mars
|
56 |
+
A panda drinking coffee in a cafe in Paris
|
57 |
+
A space shuttle launching into orbit, with flames and smoke billowing out from the engines
|
58 |
+
A steam train moving on a mountainside
|
59 |
+
A super cool giant robot in Cyberpunk Beijing
|
60 |
+
A tropical beach at sunrise, with palm trees and crystal-clear water in the foreground
|
61 |
+
Cinematic shot of Van Gogh's selfie, Van Gogh style
|
62 |
+
Gwen Stacy reading a book
|
63 |
+
Iron Man flying in the sky
|
64 |
+
The bund Shanghai, oil painting
|
65 |
+
Yoda playing guitar on the stage
|
66 |
+
A beautiful coastal beach in spring, waves lapping on sand by Hokusai, in the style of Ukiyo
|
67 |
+
A beautiful coastal beach in spring, waves lapping on sand by Vincent van Gogh
|
68 |
+
A boat sailing leisurely along the Seine River with the Eiffel Tower in background
|
69 |
+
A car moving slowly on an empty street, rainy evening
|
70 |
+
A cat eating food out of a bowl
|
71 |
+
A cat wearing sunglasses at a pool
|
72 |
+
A confused panda in calculus class
|
73 |
+
A cute fluffy panda eating Chinese food in a restaurant
|
74 |
+
A cute happy Corgi playing in park, sunset
|
75 |
+
A cute raccoon playing guitar in a boat on the ocean
|
76 |
+
A happy fuzzy panda playing guitar nearby a campfire, snow mountain in the background
|
77 |
+
A lightning striking atop of eiffel tower, dark clouds in the sky
|
78 |
+
A modern art museum, with colorful paintings
|
79 |
+
A panda cooking in the kitchen
|
80 |
+
A panda playing on a swing set
|
81 |
+
A polar bear is playing guitar
|
82 |
+
A raccoon dressed in suit playing the trumpet, stage background
|
83 |
+
A robot DJ is playing the turntable, in heavy raining futuristic tokyo rooftop cyberpunk night, sci-fi, fantasy
|
84 |
+
A shark swimming in clear Caribbean ocean
|
85 |
+
A super robot protecting city
|
86 |
+
A teddy bear washing the dishes
|
87 |
+
An epic tornado attacking above a glowing city at night, the tornado is made of smoke
|
88 |
+
An oil painting of a couple in formal evening wear going home get caught in a heavy downpour with umbrellas
|
89 |
+
Clown fish swimming through the coral reef
|
90 |
+
Hyper-realistic spaceship landing on Mars
|
91 |
+
The bund Shanghai, vibrant color
|
92 |
+
Vincent van Gogh is painting in the room
|
93 |
+
Yellow flowers swing in the wind
|
VBench/prompts/prompts_per_dimension/scene.txt
ADDED
@@ -0,0 +1,86 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
alley
|
2 |
+
amusement park
|
3 |
+
aquarium
|
4 |
+
arch
|
5 |
+
art gallery
|
6 |
+
bathroom
|
7 |
+
bakery shop
|
8 |
+
ballroom
|
9 |
+
bar
|
10 |
+
barn
|
11 |
+
basement
|
12 |
+
beach
|
13 |
+
bedroom
|
14 |
+
bridge
|
15 |
+
botanical garden
|
16 |
+
cafeteria
|
17 |
+
campsite
|
18 |
+
campus
|
19 |
+
carrousel
|
20 |
+
castle
|
21 |
+
cemetery
|
22 |
+
classroom
|
23 |
+
cliff
|
24 |
+
crosswalk
|
25 |
+
construction site
|
26 |
+
corridor
|
27 |
+
courtyard
|
28 |
+
desert
|
29 |
+
downtown
|
30 |
+
driveway
|
31 |
+
farm
|
32 |
+
food court
|
33 |
+
football field
|
34 |
+
forest road
|
35 |
+
fountain
|
36 |
+
gas station
|
37 |
+
glacier
|
38 |
+
golf course
|
39 |
+
indoor gymnasium
|
40 |
+
harbor
|
41 |
+
highway
|
42 |
+
hospital
|
43 |
+
house
|
44 |
+
iceberg
|
45 |
+
industrial area
|
46 |
+
jail cell
|
47 |
+
junkyard
|
48 |
+
kitchen
|
49 |
+
indoor library
|
50 |
+
lighthouse
|
51 |
+
laboratory
|
52 |
+
mansion
|
53 |
+
marsh
|
54 |
+
mountain
|
55 |
+
indoor movie theater
|
56 |
+
indoor museum
|
57 |
+
music studio
|
58 |
+
nursery
|
59 |
+
ocean
|
60 |
+
office
|
61 |
+
palace
|
62 |
+
parking lot
|
63 |
+
pharmacy
|
64 |
+
phone booth
|
65 |
+
raceway
|
66 |
+
restaurant
|
67 |
+
river
|
68 |
+
science museum
|
69 |
+
shower
|
70 |
+
ski slope
|
71 |
+
sky
|
72 |
+
skyscraper
|
73 |
+
baseball stadium
|
74 |
+
staircase
|
75 |
+
street
|
76 |
+
supermarket
|
77 |
+
indoor swimming pool
|
78 |
+
tower
|
79 |
+
outdoor track
|
80 |
+
train railway
|
81 |
+
train station platform
|
82 |
+
underwater coral reef
|
83 |
+
valley
|
84 |
+
volcano
|
85 |
+
waterfall
|
86 |
+
windmill
|