Datasets:

trojblue
/

test-anime-rating-v3-batch1

+ {"id": "9927910e-57b3-46c7-b4e3-28171ac1aeb0", "inserted_at": "2024-10-02T22:30:56.432921", "updated_at": "2024-10-03T10:37:47.181396", "name": "test_anime_rating_100_v3", "status": "ready", "guidelines": "Classify the Images according to the rules.", "allow_extra_metadata": false, "distribution": {"strategy": "overlap", "min_submitted": 1}, "workspace_id": "1b54bbb4-ae99-404d-a046-022649991442", "last_activity_at": "2024-10-03T10:37:47.180272"}

.argilla/settings.json ADDED Viewed

	@@ -0,0 +1 @@

+ {"guidelines": "Classify the Images according to the rules.", "questions": [{"id": "e5e4a154-e239-4eb3-9a6a-f8559670f527", "name": "composition_rating", "settings": {"type": "label_selection", "options": [{"value": "thoughtful composition", "text": "thoughtful composition", "description": null}, {"value": "has composition", "text": "has composition", "description": null}, {"value": "average or none composition", "text": "average or none composition", "description": null}, {"value": "bad composition", "text": "bad composition", "description": null}, {"value": "SKIP", "text": "SKIP", "description": null}], "visible_options": 5}, "title": "Composition? (framing, item arrangements, flow of lines, etc)", "description": "thoughtful composition: \u5728\u6784\u56fe\u4e0a\u6709\u4e00\u5b9a\u601d\u8003, \u6267\u884c\u5f97\u5f53, \u4f7f\u7528\u6444\u5f71/framing techniques\u4ea7\u751f\u4e86\u89c6\u89c9\u6548\u679c (\u6bd4\u5982\u62cd\u6444\u89d2\u5ea6, \u80cc\u666f\u548c\u524d\u666f\u7684\u642d\u914d, \u826f\u597d\u7684\u7a7a\u95f4\u5173\u7cfb, 2d\u6784\u56fe\u7b49) | The image should adhere to certain principles of professional photography composition, including the 'Rule Of Thirds', 'Depth and Layering', and more. https://danbooru.donmai.us/posts/6743649\n\nhas composition: \u5b58\u5728\u4e00\u4e9b\u6709\u610f\u8bc6\u7684\u6784\u56fe\u642d\u914d, \u4f46\u6709\u5c0f\u95ee\u9898 (\u4e0d\u662f\u6ca1\u6709\u7279\u70b9)\n\naverage or none composition: \u6ca1\u6709\u4ec0\u4e48\u7279\u70b9\u7684\u666e\u901a\u7ad9\u6869\u6784\u56fe\n\nbad composition: \u5b58\u5728\u8be1\u5f02, \u8ba9\u4eba\u4e0d\u8212\u670d, \u6a21\u578b\u591a\u534a\u4e5f\u5b66\u4e0d\u4f1a\u7684\u6784\u56fe\n\nSKIP: \u4e0d\u597d\u9009\u62e9", "required": true, "inserted_at": "2024-10-02T22:30:57.140173", "updated_at": "2024-10-02T22:30:57.140173", "type": "label_selection"}, {"id": "e63d1133-632d-4ad6-9bb0-efa5108c3edd", "name": "lighting_rating", "settings": {"type": "label_selection", "options": [{"value": "correct dynamic lighting", "text": "correct dynamic lighting", "description": null}, {"value": "has lighting", "text": "has lighting", "description": null}, {"value": "minimal or none lighting", "text": "minimal or none lighting", "description": null}, {"value": "bad lighting", "text": "bad lighting", "description": null}, {"value": "SKIP", "text": "SKIP", "description": null}], "visible_options": 5}, "title": "Lighting? (PBR only; fake lighting doesn't count)", "description": "correct dynamic lighting: \u5149\u5f71\u6b63\u786e\u5e73\u8861, \u886c\u6258\u4e86\u753b\u9762 | balanced exposure that enhances the image, for example, lighting that originates from an angle, casting highlights on select areas of the background and subject(s). https://danbooru.donmai.us/posts/6802960\n\nhas lighting: \u5b58\u5728\u4e00\u4e9b\u5149\u5f71\u642d\u914d, \u4f46\u6548\u679c\u6709\u5c0f\u95ee\u9898 (\u4e0d\u662f\u6ca1\u6709\u5149\u5f71)\n\nminimal or none lighting: \u6ca1\u6709\u4ec0\u4e48\u7279\u70b9\u7684\u5149\u5f71\u9009\u62e9 (\u63a5\u8fd1\u5e73\u6d82, \u53ef\u4ee5\u55b7\u67aa\u4e0a\u8fc7\u4e00\u4e9b\u9634\u5f71, \u4f46\u662f\u5149\u6e90\u4e0d\u5bf9/\u6f66\u8349/\u592a\u7b80\u7565)\n\nbad lighting: \u592a\u4eae/\u592a\u6697/\u592a\u6781\u7aef, \u753b\u9762\u8fc7\u66dd, etc | artificial or lackluster lighting, excessively dim or overexposed light\n\nSKIP: \u4e0d\u597d\u9009\u62e9", "required": true, "inserted_at": "2024-10-02T22:30:57.267134", "updated_at": "2024-10-02T22:38:35.142908", "type": "label_selection"}, {"id": "c79853fa-8b54-421a-a72b-fa96ff23bf05", "name": "color_contrast_rating", "settings": {"type": "label_selection", "options": [{"value": "vibrant and popping", "text": "vibrant and popping", "description": null}, {"value": "harmonious but not special", "text": "harmonious but not special", "description": null}, {"value": "average colors", "text": "average colors", "description": null}, {"value": "bad colors", "text": "bad colors", "description": null}, {"value": "SKIP", "text": "SKIP", "description": null}], "visible_options": 5}, "title": "Color and Contrast?", "description": "vibrant and popping: \u5728\u989c\u8272\u548c\u5bf9\u6bd4\u5ea6\u4e0a\u6709\u4e00\u5b9a\u601d\u8003, \u6267\u884c\u5f97\u5f53, \u4ea7\u751f\u4e86\u89c6\u89c9\u6548\u679c (\u6bd4\u5982*\u6709\u610f\u8bc6\u7684*\u51b7\u6696\u5bf9\u6bd4, \u8272\u5f69\u642d\u914d, \u649e\u8272, \u9971\u548c\u5ea6\u9009\u62e9\u7b49) | We prefer images with vibrant colors and strong color contrast. We avoid monochromatic images or those where a single color dominates the entire frame.\n\nharmonious but not special: \u989c\u8272\u548c\u8c10\u4f46\u4e0d\u7a81\u51fa, contrast\u4e0d\u591f\u6216\u8005\u6545\u610flow contrast\n\naverage colors: \u6ca1\u6709\u4ec0\u4e48\u7279\u70b9\u7684\u666e\u901a\u989c\u8272\u9009\u62e9, \u8fd8\u539f\u4e86\u89d2\u8272\u539f\u672c\u7684\u989c\u8272\n\nbad colors: \u914d\u8272\u8ba9\u4eba\u4e0d\u8212\u670d, \u989c\u8272\u810f\u4e71, \u5355\u4e00\u989c\u8272\u6ca1\u6709\u5bf9\u6bd4, \u753b\u9762\u8fc7\u4e8e\u5355\u8c03\n\nSKIP: \u4e0d\u597d\u9009\u62e9", "required": true, "inserted_at": "2024-10-02T22:30:57.383710", "updated_at": "2024-10-02T22:30:57.383710", "type": "label_selection"}, {"id": "14496415-f08b-4238-bc55-b921e694758e", "name": "subject_background_rating", "settings": {"type": "label_selection", "options": [{"value": "yes", "text": "yes", "description": null}, {"value": "mostly yes", "text": "mostly yes", "description": null}, {"value": "no", "text": "no", "description": null}, {"value": "SKIP", "text": "SKIP", "description": null}], "visible_options": 4}, "title": "Is the forground not obstructed or cutoff, and background not cluttered? (text is obstruction)", "description": "yes: \u7126\u70b9\u6e05\u6670, \u753b\u9762\u6e05\u6670, \u6ca1\u6709\u6a21\u7cca (\u6216\u8005\u6709\u610f\u8bc6\u7684\u6a21\u7cca)\n\nmostly yes: \u5927\u90e8\u5206\u6e05\u6670, \u4f46\u5b58\u5728\u4e00\u4e9b\u6a21\u7cca, \u6216\u8005\u6709\u610f\u8bc6\u7684\u6a21\u7cca\n\nno: \u7126\u70b9\u666e\u901a, \u753b\u9762\u504f\u6a21\u7cca, \u6ca1\u6709\u592a\u591a\u7ec6\u8282\n\nSKIP: \u4e0d\u597d\u9009\u62e9", "required": true, "inserted_at": "2024-10-02T22:30:57.507555", "updated_at": "2024-10-02T22:40:52.600660", "type": "label_selection"}, {"id": "0bfad964-5f4b-49ad-b868-0d066201b0c2", "name": "detail_rating", "settings": {"type": "label_selection", "options": [{"value": "highly detailed", "text": "highly detailed", "description": null}, {"value": "some detail", "text": "some detail", "description": null}, {"value": "average detail", "text": "average detail", "description": null}, {"value": "low detail", "text": "low detail", "description": null}, {"value": "SKIP", "text": "SKIP", "description": null}], "visible_options": 5}, "title": "Details?", "description": "highly detailed: \u9ad8\u7ec6\u8282, \u753b\u9762\u7cbe\u7ec6, \u6709\u4e00\u5b9a\u7684\u7eb9\u7406 (\u6216\u8005\u6709\u610f\u8bc6\u7684\u7b80\u5355\u6e05\u6670), \u770b\u8d77\u6765\u5f88\u7cbe\u81f4 | all critical details are clearly visible without compromise; the level of detail on the foreground subject is extremely important. https://x.com/SuperPig2046/status/1628983316811759616\n\nsome detail: \u5b58\u5728\u4e00\u4e9b\u7ec6\u8282/texture\u7684\u5229\u7528, \u4f46\u5b8c\u6210\u5ea6\u4e0d\u591f, \u6216\u8005\u7ec6\u8282\u4e0d\u591f\u7cbe\u7ec6\n\naverage detail: \u7ec6\u8282\u666e\u901a, \u753b\u9762\u504f\u7b80\u5355, \u6ca1\u6709\u592a\u591a\u7ec6\u8282 (\u6781\u7b80\u4e5f\u7b97)\n\nlow detail: \u7ec6\u8282\u4e0d\u8db3, \u753b\u9762\u7c97\u7cd9\n\nSKIP: \u4e0d\u597d\u9009\u62e9", "required": true, "inserted_at": "2024-10-02T22:30:57.637107", "updated_at": "2024-10-02T22:30:57.637107", "type": "label_selection"}, {"id": "80a0fd87-8f48-404a-a15a-cb2c066d905f", "name": "expressive_rating", "settings": {"type": "label_selection", "options": [{"value": "expressive image", "text": "expressive image", "description": null}, {"value": "mostly expressive", "text": "mostly expressive", "description": null}, {"value": "average expressiveness", "text": "average expressiveness", "description": null}, {"value": "stiff", "text": "stiff", "description": null}, {"value": "SKIP", "text": "SKIP", "description": null}], "visible_options": 5}, "title": "Expressiveness?", "description": "expressive image: \u7ebf\u6761\u6d41\u7545, \u6784\u9020\u7cbe\u81f4, \u8138\u90e8\u81ea\u7136, \u52a8\u4f5c\u751f\u52a8\u7b49, \u770b\u8d77\u6765\u5f88\u6709\u8868\u73b0\u529b, \u753b\u9762\u5f20\u529b\u9ad8 https://danbooru.donmai.us/posts/5844547\n\nmostly expressive: \u753b\u9762\u751f\u52a8\u6709\u4e00\u5b9a\u5f20\u529b, \u4f46\u5b8c\u6210\u5ea6\u592a\u4f4e\u6216\u8005\u5b58\u5728\u9519\u8bef (\u6bd4\u5982\u63a8\u7279\u7684\u5f88\u591arakugaki / \u968f\u624b\u753b)\n\naverage expressiveness: \u666e\u901a\u7684\u8868\u73b0\u529b, \u753b\u9762\u504f\u50f5\u786c, \u770b\u8d77\u6765\u4e0d\u751f\u52a8\n\nstiff: \u4e1a\u4f59\u6c34\u51c6, \u4f4e\u4e8e\u5e73\u5747\u6c34\u5e73, \u753b\u9762\u8868\u73b0\u529b\u4e0d\u8db3\u6216\u8005\u8be1\u5f02, \u8ba9\u4eba\u4e0d\u8212\u670d https://danbooru.donmai.us/posts/7431687\n\nSKIP: \u4e0d\u597d\u9009\u62e9", "required": true, "inserted_at": "2024-10-02T22:30:57.756862", "updated_at": "2024-10-02T22:30:57.756862", "type": "label_selection"}, {"id": "827fc231-1cfd-40ba-963c-ef59b60c606c", "name": "anatomy_rating", "settings": {"type": "label_selection", "options": [{"value": "good anatomy", "text": "good anatomy", "description": null}, {"value": "mostly good", "text": "mostly good", "description": null}, {"value": "average anatomy", "text": "average anatomy", "description": null}, {"value": "bad anatomy", "text": "bad anatomy", "description": null}, {"value": "SKIP", "text": "SKIP", "description": null}], "visible_options": 5}, "title": "Anatomy?", "description": "good anatomy: \u52a8\u6001\u611f\u597d, \u59ff\u52bf\u81ea\u7136\u6d41\u7545 https://danbooru.donmai.us/posts/5972188\n\nmostly good: \u603b\u4f53\u6bd4\u8f83\u597d, \u4f46\u4e3a\u827a\u672f\u6548\u679c\u505a\u4e86\u5938\u5f20, \u6bd4\u5982\u624b\u592a\u5c0f\u592a\u9f87\u7b49 https://danbooru.donmai.us/posts/6908818\n\naverage anatomy: anatomy\u666e\u901a, \u6709\u70b9\u6b7b\u677f(\u6807\u51c6\u7ad9\u6869, \u52a8\u4f5c\u751f\u786c\u7b49)\n\nbad anatomy: \u4e1a\u4f59\u6c34\u51c6, anatomy\u626d\u66f2, \u5b58\u5728\u5938\u5f20\u4e0d\u5408\u7406\u7684\u53d8\u5f62\u7b49, \u4e0d\u7b26\u5408\u4eba\u4f53\u7ed3\u6784 https://danbooru.donmai.us/posts/5030231\n\nSKIP: \u8df3\u8fc7 (\u4e0d\u662f\u4eba\u50cf, \u8138\u88ab\u906e\u4f4f, \u4eba\u7269\u592a\u8fdc\u7b49) *\u52a8\u7269\u7c7b\u5e94\u8be5\u6309\u6709\u8138\u6253\u6807", "required": true, "inserted_at": "2024-10-02T22:30:57.882535", "updated_at": "2024-10-02T22:30:57.882535", "type": "label_selection"}, {"id": "f7b95390-c907-4870-86cd-803a717abc52", "name": "five_category_rating", "settings": {"type": "label_selection", "options": [{"value": "best quality", "text": "best quality", "description": null}, {"value": "good quality", "text": "good quality", "description": null}, {"value": "average quality", "text": "average quality", "description": null}, {"value": "bad quality", "text": "bad quality", "description": null}, {"value": "worst quality", "text": "worst quality", "description": null}, {"value": "SKIP", "text": "SKIP", "description": null}], "visible_options": 6}, "title": "Overall Rating?", "description": "best quality: \u6311\u4e0d\u51fa\u6bdb\u75c5\u5168\u65b9\u4f4d\u7684\u597d\u56fe\n\ngood quality: \u6574\u4f53\u8fd8\u4e0d\u9519 \u770b\u8d77\u6765\u6709\u7f8e\u611f, \u4f46\u80fd\u770b\u51fa\u6709\u5c0f\u95ee\u9898\n\naverage quality: \u666e\u901a, \u6ca1\u6709\u592a\u591a\u7279\u70b9, \u4f46\u4e5f\u6ca1\u6709\u592a\u591a\u95ee\u9898\n\nbad quality: \u6709\u660e\u663e\u95ee\u9898\u7684\u56fe (\u4f46\u6ca1\u5230\u6050\u6016)\n\nworst quality: \u975e\u5e38\u574f\u6216\u8005\u8fbe\u5230\u4e86\u6050\u6016\u8c37\u7684\u56fe\n\nSKIP: Skip", "required": true, "inserted_at": "2024-10-02T22:30:58.005422", "updated_at": "2024-10-02T22:30:58.005422", "type": "label_selection"}], "fields": [{"id": "5cd4a13e-9c6f-4dda-9ca2-3949372155fd", "inserted_at": "2024-10-02T22:30:56.868763", "updated_at": "2024-10-02T22:30:56.868763", "name": "image_url", "settings": {"type": "image"}, "title": "image_url", "required": true, "description": null, "dataset_id": "9927910e-57b3-46c7-b4e3-28171ac1aeb0", "type": "image"}, {"id": "ec3309f3-a583-4842-876f-9836565e82dd", "inserted_at": "2024-10-02T22:30:56.997664", "updated_at": "2024-10-02T22:30:56.997664", "name": "s3_uri", "settings": {"type": "text", "use_markdown": false}, "title": "s3_uri", "required": true, "description": null, "dataset_id": "9927910e-57b3-46c7-b4e3-28171ac1aeb0", "type": "text"}], "vectors": [], "metadata": [], "allow_extra_metadata": false, "distribution": {"strategy": "overlap", "min_submitted": 1}, "mapping": null}

README.md CHANGED Viewed

@@ -1,73 +1,372 @@
 ---
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: status
-    dtype: string
-  - name: _server_id
-    dtype: string
-  - name: image_url
-    dtype: string
-  - name: s3_uri
-    dtype: string
-  - name: composition_rating.responses
-    sequence: string
-  - name: composition_rating.responses.users
-    sequence: string
-  - name: composition_rating.responses.status
-    sequence: string
-  - name: lighting_rating.responses
-    sequence: string
-  - name: lighting_rating.responses.users
-    sequence: string
-  - name: lighting_rating.responses.status
-    sequence: string
-  - name: color_contrast_rating.responses
-    sequence: string
-  - name: color_contrast_rating.responses.users
-    sequence: string
-  - name: color_contrast_rating.responses.status
-    sequence: string
-  - name: subject_background_rating.responses
-    sequence: string
-  - name: subject_background_rating.responses.users
-    sequence: string
-  - name: subject_background_rating.responses.status
-    sequence: string
-  - name: detail_rating.responses
-    sequence: string
-  - name: detail_rating.responses.users
-    sequence: string
-  - name: detail_rating.responses.status
-    sequence: string
-  - name: expressive_rating.responses
-    sequence: string
-  - name: expressive_rating.responses.users
-    sequence: string
-  - name: expressive_rating.responses.status
-    sequence: string
-  - name: anatomy_rating.responses
-    sequence: string
-  - name: anatomy_rating.responses.users
-    sequence: string
-  - name: anatomy_rating.responses.status
-    sequence: string
-  - name: five_category_rating.responses
-    sequence: string
-  - name: five_category_rating.responses.users
-    sequence: string
-  - name: five_category_rating.responses.status
-    sequence: string
-  splits:
-  - name: train
-    num_bytes: 107614
-    num_examples: 100
-  download_size: 41851
-  dataset_size: 107614
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
 ---

 ---
+size_categories: n<1K
+tags:
+- rlfh
+- argilla
+- human-feedback
 ---
+# Dataset Card for test-anime-rating-v3-batch1
+This dataset has been created with [Argilla](https://github.com/argilla-io/argilla). As shown in the sections below, this dataset can be loaded into your Argilla server as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets).
+## Using this dataset with Argilla
+To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code:
+```python
+import argilla as rg
+ds = rg.Dataset.from_hub("trojblue/test-anime-rating-v3-batch1")
+```
+This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation.
+## Using this dataset with `datasets`
+To load the records of this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code:
+```python
+from datasets import load_dataset
+ds = load_dataset("trojblue/test-anime-rating-v3-batch1")
+```
+This will only load the records of the dataset, but not the Argilla settings.
+## Dataset Structure
+This dataset repo contains:
+* Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `rg.Dataset.from_hub` and can be loaded independently using the `datasets` library via `load_dataset`.
+* The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla.
+* A dataset configuration folder conforming to the Argilla dataset format in `.argilla`.
+The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**.
+### Fields
+The **fields** are the features or text of a dataset's records. For example, the 'text' column of a text classification dataset of the 'prompt' column of an instruction following dataset.
+| Field Name | Title | Type | Required | Markdown |
+| ---------- | ----- | ---- | -------- | -------- |
+| image_url | image_url | image | True |  |
+| s3_uri | s3_uri | text | True | False |
+### Questions
+The **questions** are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking.
+| Question Name | Title | Type | Required | Description | Values/Labels |
+| ------------- | ----- | ---- | -------- | ----------- | ------------- |
+| composition_rating | Composition? (framing, item arrangements, flow of lines, etc) | label_selection | True | thoughtful composition: 在构图上有一定思考, 执行得当, 使用摄影/framing techniques产生了视觉效果 (比如拍摄角度, 背景和前景的搭配, 良好的空间关系, 2d构图等) | The image should adhere to certain principles of professional photography composition, including the 'Rule Of Thirds', 'Depth and Layering', and more. https://danbooru.donmai.us/posts/6743649
+has composition: 存在一些有意识的构图搭配, 但有小问题 (不是没有特点)
+average or none composition: 没有什么特点的普通站桩构图
+bad composition: 存在诡异, 让人不舒服, 模型多半也学不会的构图
+SKIP: 不好选择 | ['thoughtful composition', 'has composition', 'average or none composition', 'bad composition', 'SKIP'] |
+| lighting_rating | Lighting? (PBR only; fake lighting doesn't count) | label_selection | True | correct dynamic lighting: 光影正确平衡,  衬托了画面 | balanced exposure that enhances the image, for example, lighting that originates from an angle, casting highlights on select areas of the background and subject(s). https://danbooru.donmai.us/posts/6802960
+has lighting: 存在一些光影搭配, 但效果有小问题 (不是没有光影)
+minimal or none lighting: 没有什么特点的光影选择 (接近平涂, 可以喷枪上过一些阴影, 但是光源不对/潦草/太简略)
+bad lighting: 太亮/太暗/太极端, 画面过曝, etc | artificial or lackluster lighting, excessively dim or overexposed light
+SKIP: 不好选择 | ['correct dynamic lighting', 'has lighting', 'minimal or none lighting', 'bad lighting', 'SKIP'] |
+| color_contrast_rating | Color and Contrast? | label_selection | True | vibrant and popping: 在颜色和对比度上有一定思考, 执行得当, 产生了视觉效果 (比如*有意识的*冷暖对比, 色彩搭配, 撞色, 饱和度选择等) | We prefer images with vibrant colors and strong color contrast. We avoid monochromatic images or those where a single color dominates the entire frame.
+harmonious but not special: 颜色和谐但不突出, contrast不够或者故意low contrast
+average colors: 没有什么特点的普通颜色选择, 还原了角色原本的颜色
+bad colors: 配色让人不舒服, 颜色脏乱, 单一颜色没有对比, 画面过于单调
+SKIP: 不好选择 | ['vibrant and popping', 'harmonious but not special', 'average colors', 'bad colors', 'SKIP'] |
+| subject_background_rating | Is the forground not obstructed or cutoff, and background not cluttered? (text is obstruction) | label_selection | True | yes: 焦点清晰, 画面清晰, 没有模糊 (或者有意识的模糊)
+mostly yes: 大部分清晰, 但存在一些模糊, 或者有意识的模糊
+no: 焦点普通, 画面偏模糊, 没有太多细节
+SKIP: 不好选择 | ['yes', 'mostly yes', 'no', 'SKIP'] |
+| detail_rating | Details? | label_selection | True | highly detailed: 高细节, 画面精细, 有一定的纹理 (或者有意识的简单清晰), 看起来很精致 | all critical details are clearly visible without compromise; the level of detail on the foreground subject is extremely important. https://x.com/SuperPig2046/status/1628983316811759616
+some detail: 存在一些细节/texture的利用, 但完成度不够, 或者细节不够精细
+average detail: 细节普通, 画面偏简单, 没有太多细节 (极简也算)
+low detail: 细节不足, 画面粗糙
+SKIP: 不好选择 | ['highly detailed', 'some detail', 'average detail', 'low detail', 'SKIP'] |
+| expressive_rating | Expressiveness? | label_selection | True | expressive image: 线条流畅, 构造精致, 脸部自然, 动作生动等, 看起来很有表现力, 画面张力高 https://danbooru.donmai.us/posts/5844547
+mostly expressive: 画面生动有一定张力, 但完成度太低或者存在错误 (比如推特的很多rakugaki / 随手画)
+average expressiveness: 普通的表现力, 画面偏僵硬, 看起来不生动
+stiff: 业余水准, 低于平均水平, 画面表现力不足或者诡异, 让人不舒服 https://danbooru.donmai.us/posts/7431687
+SKIP: 不好选择 | ['expressive image', 'mostly expressive', 'average expressiveness', 'stiff', 'SKIP'] |
+| anatomy_rating | Anatomy? | label_selection | True | good anatomy: 动态感好, 姿势自然流畅 https://danbooru.donmai.us/posts/5972188
+mostly good: 总体比较好, 但为艺术效果做了夸张, 比如手太小太龇等 https://danbooru.donmai.us/posts/6908818
+average anatomy: anatomy普通, 有点死板(标准站桩, 动作生硬等)
+bad anatomy: 业余水准, anatomy扭曲, 存在夸张不合理的变形等, 不符合人体结构 https://danbooru.donmai.us/posts/5030231
+SKIP: 跳过 (不是人像, 脸被遮住, 人物太远等) *动物类应该按有脸打标 | ['good anatomy', 'mostly good', 'average anatomy', 'bad anatomy', 'SKIP'] |
+| five_category_rating | Overall Rating? | label_selection | True | best quality: 挑不出毛病全方位的好图
+good quality: 整体还不错 看起来有美感, 但能看出有小问题
+average quality: 普通, 没有太多特点, 但也没有太多问题
+bad quality: 有明显问题的图 (但没到恐怖)
+worst quality: 非常坏或者达到了恐怖谷的图
+SKIP: Skip | ['best quality', 'good quality', 'average quality', 'bad quality', 'worst quality', 'SKIP'] |
+<!-- check length of metadata properties -->
+### Data Instances
+An example of a dataset instance in Argilla looks as follows:
+```json
+{
+    "_server_id": "25779056-2f36-4042-a87c-1988d0e25321",
+    "fields": {
+        "image_url": "https://bucket-external.s3.amazonaws.com/dataset/dataset_qft/qft_v5c_twitter-logfav_9.6_60k/image_6567598.webp?AWSAccessKeyId=AKIAVVWUPRZ2AC6O2S3I\u0026Signature=M%2BVwsOUf7HOsOaqMRX%2Bl3f8ZyyQ%3D\u0026Expires=1727994782",
+        "s3_uri": "s3://bucket-external/dataset/dataset_qft/qft_v5c_twitter-logfav_9.6_60k/image_6567598.webp"
+    },
+    "id": "d0f58939-a0ab-45c5-a013-da54504c587a",
+    "metadata": {},
+    "responses": {
+        "anatomy_rating": [
+            {
+                "user_id": "6951ac60-243a-468a-b9fc-926520320d48",
+                "value": "good anatomy"
+            }
+        ],
+        "color_contrast_rating": [
+            {
+                "user_id": "6951ac60-243a-468a-b9fc-926520320d48",
+                "value": "vibrant and popping"
+            }
+        ],
+        "composition_rating": [
+            {
+                "user_id": "6951ac60-243a-468a-b9fc-926520320d48",
+                "value": "has composition"
+            }
+        ],
+        "detail_rating": [
+            {
+                "user_id": "6951ac60-243a-468a-b9fc-926520320d48",
+                "value": "highly detailed"
+            }
+        ],
+        "expressive_rating": [
+            {
+                "user_id": "6951ac60-243a-468a-b9fc-926520320d48",
+                "value": "expressive image"
+            }
+        ],
+        "five_category_rating": [
+            {
+                "user_id": "6951ac60-243a-468a-b9fc-926520320d48",
+                "value": "best quality"
+            }
+        ],
+        "lighting_rating": [
+            {
+                "user_id": "6951ac60-243a-468a-b9fc-926520320d48",
+                "value": "has lighting"
+            }
+        ],
+        "subject_background_rating": [
+            {
+                "user_id": "6951ac60-243a-468a-b9fc-926520320d48",
+                "value": "no"
+            }
+        ]
+    },
+    "status": "completed",
+    "suggestions": {},
+    "vectors": {}
+}
+```
+While the same record in HuggingFace `datasets` looks as follows:
+```json
+{
+    "_server_id": "25779056-2f36-4042-a87c-1988d0e25321",
+    "anatomy_rating.responses": [
+        "good anatomy"
+    ],
+    "anatomy_rating.responses.status": [
+        "submitted"
+    ],
+    "anatomy_rating.responses.users": [
+        "6951ac60-243a-468a-b9fc-926520320d48"
+    ],
+    "color_contrast_rating.responses": [
+        "vibrant and popping"
+    ],
+    "color_contrast_rating.responses.status": [
+        "submitted"
+    ],
+    "color_contrast_rating.responses.users": [
+        "6951ac60-243a-468a-b9fc-926520320d48"
+    ],
+    "composition_rating.responses": [
+        "has composition"
+    ],
+    "composition_rating.responses.status": [
+        "submitted"
+    ],
+    "composition_rating.responses.users": [
+        "6951ac60-243a-468a-b9fc-926520320d48"
+    ],
+    "detail_rating.responses": [
+        "highly detailed"
+    ],
+    "detail_rating.responses.status": [
+        "submitted"
+    ],
+    "detail_rating.responses.users": [
+        "6951ac60-243a-468a-b9fc-926520320d48"
+    ],
+    "expressive_rating.responses": [
+        "expressive image"
+    ],
+    "expressive_rating.responses.status": [
+        "submitted"
+    ],
+    "expressive_rating.responses.users": [
+        "6951ac60-243a-468a-b9fc-926520320d48"
+    ],
+    "five_category_rating.responses": [
+        "best quality"
+    ],
+    "five_category_rating.responses.status": [
+        "submitted"
+    ],
+    "five_category_rating.responses.users": [
+        "6951ac60-243a-468a-b9fc-926520320d48"
+    ],
+    "id": "d0f58939-a0ab-45c5-a013-da54504c587a",
+    "image_url": "https://bucket-external.s3.amazonaws.com/dataset/dataset_qft/qft_v5c_twitter-logfav_9.6_60k/image_6567598.webp?AWSAccessKeyId=AKIAVVWUPRZ2AC6O2S3I\u0026Signature=M%2BVwsOUf7HOsOaqMRX%2Bl3f8ZyyQ%3D\u0026Expires=1727994782",
+    "lighting_rating.responses": [
+        "has lighting"
+    ],
+    "lighting_rating.responses.status": [
+        "submitted"
+    ],
+    "lighting_rating.responses.users": [
+        "6951ac60-243a-468a-b9fc-926520320d48"
+    ],
+    "s3_uri": "s3://bucket-external/dataset/dataset_qft/qft_v5c_twitter-logfav_9.6_60k/image_6567598.webp",
+    "status": "completed",
+    "subject_background_rating.responses": [
+        "no"
+    ],
+    "subject_background_rating.responses.status": [
+        "submitted"
+    ],
+    "subject_background_rating.responses.users": [
+        "6951ac60-243a-468a-b9fc-926520320d48"
+    ]
+}
+```
+### Data Splits
+The dataset contains a single split, which is `train`.
+## Dataset Creation
+### Curation Rationale
+[More Information Needed]
+### Source Data
+#### Initial Data Collection and Normalization
+[More Information Needed]
+#### Who are the source language producers?
+[More Information Needed]
+### Annotations
+#### Annotation guidelines
+Classify the Images according to the rules.
+#### Annotation process
+[More Information Needed]
+#### Who are the annotators?
+[More Information Needed]
+### Personal and Sensitive Information
+[More Information Needed]
+## Considerations for Using the Data
+### Social Impact of Dataset
+[More Information Needed]
+### Discussion of Biases
+[More Information Needed]
+### Other Known Limitations
+[More Information Needed]
+## Additional Information
+### Dataset Curators
+[More Information Needed]
+### Licensing Information
+[More Information Needed]
+### Citation Information
+[More Information Needed]
+### Contributions
+[More Information Needed]