wendys-llc commited on
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c19b0f2
1 Parent(s): 9a9a2ca

Update app.py

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Files changed (1) hide show
  1. app.py +58 -21
app.py CHANGED
@@ -1,17 +1,34 @@
1
  #!/usr/bin/env python3
2
  import gradio as gr
3
  from clip_interrogator import Config, Interrogator
 
4
 
5
- # MODELS = ['ViT-L (best for Stable Diffusion 1.*)', 'ViT-H (best for Stable Diffusion 2.*)']
6
- # MODELS = ['ViT-L (best for Stable Diffusion 1.*)',]
7
 
8
  # load BLIP and ViT-L https://huggingface.co/openai/clip-vit-large-patch14
9
- from PIL import Image
10
- from clip_interrogator import Config, Interrogator
11
-
12
- ci = Interrogator(Config(clip_model_name="ViT-L-14/openai"))
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
13
 
14
- def image_analysis(image):
15
  image = image.convert('RGB')
16
  image_features = ci.image_to_features(image)
17
 
@@ -30,7 +47,22 @@ def image_analysis(image):
30
  return medium_ranks, artist_ranks, movement_ranks, trending_ranks, flavor_ranks
31
 
32
 
33
- def image_to_prompt(image, mode):
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
34
  image = image.convert('RGB')
35
  if mode == 'best':
36
  prompt = ci.interrogate(image)
@@ -41,7 +73,7 @@ def image_to_prompt(image, mode):
41
  elif mode == 'negative':
42
  prompt = ci.interrogate_negative(image)
43
 
44
- return prompt
45
 
46
 
47
  TITLE = """
@@ -61,7 +93,7 @@ TITLE = """
61
  <p style="margin-bottom: 10px; font-size: 94%">
62
  Want to figure out what a good prompt might be to create new images like an existing one?<br>The CLIP Interrogator is here to get you answers!
63
  </p>
64
- <p>You can skip the queue by duplicating this space and upgrading to gpu in settings: <a style='display:inline-block' href='https://huggingface.co/spaces/pharma/CLIP-Interrogator?duplicate=true'><img src='https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14' alt='Duplicate Space'></a></p>
65
  </div>
66
  """
67
 
@@ -72,11 +104,9 @@ ARTICLE = """
72
  and <a href="https://pixabay.com/illustrations/animal-painting-cat-feline-pet-7154059/">Lin Tong</a>
73
  from pixabay.com
74
  </p>
75
-
76
  <p>
77
  Server busy? You can also run on <a href="https://colab.research.google.com/github/pharmapsychotic/clip-interrogator/blob/main/clip_interrogator.ipynb">Google Colab</a>
78
  </p>
79
-
80
  <p>
81
  Has this been helpful to you? Follow me on twitter
82
  <a href="https://twitter.com/pharmapsychotic">@pharmapsychotic</a><br>
@@ -126,14 +156,14 @@ def analyze_tab():
126
  trending = gr.Label(label="Trending", num_top_classes=5)
127
  flavor = gr.Label(label="Flavor", num_top_classes=5)
128
 
129
- button = gr.Button("Analyze")
130
  button.click(image_analysis, inputs=[image, model], outputs=[medium, artist, movement, trending, flavor])
131
 
132
  examples=[['example01.jpg', MODELS[0]], ['example02.jpg', MODELS[0]]]
133
  ex = gr.Examples(
134
  examples=examples,
135
  fn=image_analysis,
136
- inputs=[input_image],
137
  outputs=[medium, artist, movement, trending, flavor],
138
  cache_examples=True,
139
  run_on_click=True
@@ -149,16 +179,22 @@ with gr.Blocks(css=CSS) as block:
149
  with gr.Row():
150
  input_image = gr.Image(type='pil', elem_id="input-img")
151
  with gr.Column():
 
152
  input_mode = gr.Radio(['best', 'fast', 'classic', 'negative'], value='best', label='Mode')
153
- submit_btn = gr.Button("Submit")
154
  output_text = gr.Textbox(label="Output", elem_id="output-txt")
155
 
156
- examples=[['example01.jpg', 'best'], ['example02.jpg', 'best']]
 
 
 
 
 
157
  ex = gr.Examples(
158
  examples=examples,
159
  fn=image_to_prompt,
160
- inputs=[input_image, input_mode],
161
- outputs=[output_text],
162
  cache_examples=True,
163
  run_on_click=True
164
  )
@@ -171,8 +207,9 @@ with gr.Blocks(css=CSS) as block:
171
 
172
  submit_btn.click(
173
  fn=image_to_prompt,
174
- inputs=[input_image, input_mode],
175
- outputs=[output_text]
176
  )
 
177
 
178
- block.queue(max_size=64).launch(show_api=False)
 
1
  #!/usr/bin/env python3
2
  import gradio as gr
3
  from clip_interrogator import Config, Interrogator
4
+ from share_btn import community_icon_html, loading_icon_html, share_js
5
 
6
+ MODELS = ['ViT-L (best for Stable Diffusion 1.*)']#, 'ViT-H (best for Stable Diffusion 2.*)']
 
7
 
8
  # load BLIP and ViT-L https://huggingface.co/openai/clip-vit-large-patch14
9
+ config = Config(clip_model_name="ViT-L-14/openai")
10
+ ci_vitl = Interrogator(config)
11
+ # ci_vitl.clip_model = ci_vitl.clip_model.to("cpu")
12
+
13
+ # load ViT-H https://huggingface.co/laion/CLIP-ViT-H-14-laion2B-s32B-b79K
14
+ # config.blip_model = ci_vitl.blip_model
15
+ # config.clip_model_name = "ViT-H-14/laion2b_s32b_b79k"
16
+ # ci_vith = Interrogator(config)
17
+ # ci_vith.clip_model = ci_vith.clip_model.to("cpu")
18
+
19
+
20
+ def image_analysis(image, clip_model_name):
21
+ # move selected model to GPU and other model to CPU
22
+ # if clip_model_name == MODELS[0]:
23
+ # ci_vith.clip_model = ci_vith.clip_model.to("cpu")
24
+ # ci_vitl.clip_model = ci_vitl.clip_model.to(ci_vitl.device)
25
+ # ci = ci_vitl
26
+ # else:
27
+ # ci_vitl.clip_model = ci_vitl.clip_model.to("cpu")
28
+ # ci_vith.clip_model = ci_vith.clip_model.to(ci_vith.device)
29
+ # ci = ci_vith
30
+ ci = ci_vitl
31
 
 
32
  image = image.convert('RGB')
33
  image_features = ci.image_to_features(image)
34
 
 
47
  return medium_ranks, artist_ranks, movement_ranks, trending_ranks, flavor_ranks
48
 
49
 
50
+ def image_to_prompt(image, clip_model_name, mode):
51
+ # move selected model to GPU and other model to CPU
52
+ # if clip_model_name == MODELS[0]:
53
+ # ci_vith.clip_model = ci_vith.clip_model.to("cpu")
54
+ # ci_vitl.clip_model = ci_vitl.clip_model.to(ci_vitl.device)
55
+ # ci = ci_vitl
56
+ # else:
57
+ # ci_vitl.clip_model = ci_vitl.clip_model.to("cpu")
58
+ # ci_vith.clip_model = ci_vith.clip_model.to(ci_vith.device)
59
+ # ci = ci_vith
60
+ ci = ci_vitl
61
+
62
+ ci.config.blip_num_beams = 64
63
+ ci.config.chunk_size = 2048
64
+ ci.config.flavor_intermediate_count = 2048 if clip_model_name == MODELS[0] else 1024
65
+
66
  image = image.convert('RGB')
67
  if mode == 'best':
68
  prompt = ci.interrogate(image)
 
73
  elif mode == 'negative':
74
  prompt = ci.interrogate_negative(image)
75
 
76
+ return prompt, gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
77
 
78
 
79
  TITLE = """
 
93
  <p style="margin-bottom: 10px; font-size: 94%">
94
  Want to figure out what a good prompt might be to create new images like an existing one?<br>The CLIP Interrogator is here to get you answers!
95
  </p>
96
+ <p>You can skip the queue by duplicating this space and upgrading to gpu in settings: <a style='display:inline-block' href='https://huggingface.co/spaces/pharmapsychotic/CLIP-Interrogator?duplicate=true'><img src='https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14' alt='Duplicate Space'></a></p>
97
  </div>
98
  """
99
 
 
104
  and <a href="https://pixabay.com/illustrations/animal-painting-cat-feline-pet-7154059/">Lin Tong</a>
105
  from pixabay.com
106
  </p>
 
107
  <p>
108
  Server busy? You can also run on <a href="https://colab.research.google.com/github/pharmapsychotic/clip-interrogator/blob/main/clip_interrogator.ipynb">Google Colab</a>
109
  </p>
 
110
  <p>
111
  Has this been helpful to you? Follow me on twitter
112
  <a href="https://twitter.com/pharmapsychotic">@pharmapsychotic</a><br>
 
156
  trending = gr.Label(label="Trending", num_top_classes=5)
157
  flavor = gr.Label(label="Flavor", num_top_classes=5)
158
 
159
+ button = gr.Button("Analyze", api_name="image-analysis")
160
  button.click(image_analysis, inputs=[image, model], outputs=[medium, artist, movement, trending, flavor])
161
 
162
  examples=[['example01.jpg', MODELS[0]], ['example02.jpg', MODELS[0]]]
163
  ex = gr.Examples(
164
  examples=examples,
165
  fn=image_analysis,
166
+ inputs=[input_image, input_model],
167
  outputs=[medium, artist, movement, trending, flavor],
168
  cache_examples=True,
169
  run_on_click=True
 
179
  with gr.Row():
180
  input_image = gr.Image(type='pil', elem_id="input-img")
181
  with gr.Column():
182
+ input_model = gr.Dropdown(MODELS, value=MODELS[0], label='CLIP Model')
183
  input_mode = gr.Radio(['best', 'fast', 'classic', 'negative'], value='best', label='Mode')
184
+ submit_btn = gr.Button("Submit", api_name="image-to-prompt")
185
  output_text = gr.Textbox(label="Output", elem_id="output-txt")
186
 
187
+ with gr.Group(elem_id="share-btn-container"):
188
+ community_icon = gr.HTML(community_icon_html, visible=False)
189
+ loading_icon = gr.HTML(loading_icon_html, visible=False)
190
+ share_button = gr.Button("Share to community", elem_id="share-btn", visible=False)
191
+
192
+ examples=[['example01.jpg', MODELS[0], 'best'], ['example02.jpg', MODELS[0], 'best']]
193
  ex = gr.Examples(
194
  examples=examples,
195
  fn=image_to_prompt,
196
+ inputs=[input_image, input_model, input_mode],
197
+ outputs=[output_text, share_button, community_icon, loading_icon],
198
  cache_examples=True,
199
  run_on_click=True
200
  )
 
207
 
208
  submit_btn.click(
209
  fn=image_to_prompt,
210
+ inputs=[input_image, input_model, input_mode],
211
+ outputs=[output_text, share_button, community_icon, loading_icon]
212
  )
213
+ share_button.click(None, [], [], _js=share_js)
214
 
215
+ block.queue(max_size=64).launch(show_api=False)