Datasets:

FER-Universe
/

DiffusionFER

 ---
+layout: default
+title: Home
+nav_order: 1
+has_children: false
+annotations_creators:
+- no-annotation
+language:
+- en
+language_creators:
+- found
+pretty_name: DiffusionEmotion
+size_categories:
+- n<500MB
+source_datasets:
+- original
 license: cc0-1.0
+tags:
+- stable diffusion
+- prompt engineering
+- prompts
+- research paper
+- facial expression recognition
+- emotion recognition
+task_categories:
+- text-to-image
+task_ids:
+- image-captioning
+- face-detection
 ---
+## Dataset Description
+- **Homepage:** [DiffusionEmotion homepage](https://kdhht2334.github.io/)
+- **Repository:** [DiffusionEmotion repository](https://github.com/kdhht2334/Facial-Expression-Recognition-Zoo)
+- **Distribution:** [DiffusionEmotion Hugging Face Dataset](https://huggingface.co/datasets/kdhht2334/DiffusionEmotion)
+- **Point of Contact:** [Daeha Kim](mailto:kdhht5022@gmail.com)
+### Summary
+DiffusionEmotion is the large-scale text-to-image prompt database for face-related tasks. It contains about **1M(ongoing)** images generated by [Stable Diffusion](https://github.com/camenduru/stable-diffusion-webui-colab) using prompt(s) and other parameters.
+DiffusionEmotion is available at [🤗 Hugging Face Dataset](https://huggingface.co/datasets/kdhht2334/DiffusionEmotion).
+### Downstream Tasks and Leaderboards
+This DiffusionEmotion dataset can be utilized for the following downstream tasks.
+  - Face detection
+  - Facial expression recognition
+  - Text-to-emotion prompting
+In addition, the virtual subjects included in this dataset provide opportunities to perform various vision tasks related to face privacy.
+### Data Loading
+DiffusionEmotion can be loaded via both Python and Git. Please refer Hugging Face [`Datasets`](https://huggingface.co/docs/datasets/quickstart).
+```python
+from datasets import load_dataset
+dataset = load_dataset("kdhht2334/DiffusionEmotion")
+```
+```bash
+git lfs install
+git clone https://huggingface.co/datasets/kdhht2334/DiffusionEmotion
+```
+### Sample Gallery
+▼Happy
+![Gallery(happy)](https://drive.google.com/uc?id=10YW9XHXFJ9cjutis9Pwpgd0ld6JI84P3)
+▼Angry
+![Gallery(happy)](https://drive.google.com/uc?id=14qbmOgzqqXGxkatjMfqaUmf0xYwDz--g)
+### Subsets
+DiffusionEmotion supports a total of three distinct splits. And, each split additionally provides a face region cropped by [face detector](https://github.com/timesler/facenet-pytorch).
+   - DifussionEmotion_S (small), DifussionEmotion_M (medium), DifussionEmotion_L (large).
+|Subset|Num of Images|Size|Image Directory |
+|:--|--:|--:|--:|
+|DifussionEmotion_S (original) | 1.5K | 647M | `DifussionEmotion_S/` |
+|DifussionEmotion_S (cropped)  | 1.5K | 322M | `DiffusionEmotion_S_cropped/` |
+|DifussionEmotion_M (original) | N/A  | N/A  | `DifussionEmotion_M/` |
+|DifussionEmotion_M (cropped)  | N/A  | N/A  | `DiffusionEmotion_M_cropped/` |
+|DifussionEmotion_L (original) | N/A  | N/A  | `DifussionEmotion_L/` |
+|DifussionEmotion_L (cropped)  | N/A  | N/A  | `DiffusionEmotion_L_cropped/` |
+## Dataset Structure
+We provide DiffusionEmotion using a modular file structure. `DiffusionEmotion_S`, the smallest scale, contains about 1,500 images and is divided into folders of a total of 7 emotion classes. The class labels of all these images are included in `dataset_sheet.csv`.
+   - In `dataset_sheet.csv`, not only 7-emotion class but also _valence-arousal_ value are annotated.
+```bash
+# Small version of DB
+./
+├── DifussionEmotion_S
+│   ├── angry
+│   │   ├── aaaaaaaa_6.png
+│   │   ├── andtcvhp_6.png
+│   │   ├── azikakjh_6.png
+│   │   ├── [...]
+│   ├── fear
+│   ├── happy
+│   ├── [...]
+│   └── surprise
+└── dataset_sheet.csv
+```
+```bash
+# Medium version of DB
+(ongoing)
+```
+```bash
+# Large version of DB
+(ongoing)
+```
+### Prompt Format
+Basic format is as follows: "`Emotion`, `Race` `Age` style, a realistic portrait of `Style` `Gender`, upper body, `Others`".
+- ex) neutral emotion, white middle-aged style, a realistic portrait of man, upper body
+Examples of format categories are listed in the table below.
+| Category | Prompt(s) |
+| --- | --- |
+| `Emotion` | neutral emotion<br>happy emotion, with open mouth<br>sad emotion with tears, lowered head, droopy eyebrows<br>surprise emotion, open mouth<br>fear emotion, fear expression, haunted<br>disgust emotion, angry expression with open mouth<br>angry emotion with open mouth, frown eyebrow |
+| `Race`    | white<br>black<br>latin |
+| `Age`     | teen<br>middle-aged<br>old |
+| `Gender`  | man<br>woman |
+| `Style`   | gentle<br>handsome<br>pretty<br>cute<br>punky<br>medieval Europe<br>Cyberpunk<br>Camping<br>... |
+| `Others`  | beautiful crystal eyes<br>big eyes<br>small nose<br>... |
+### Prompt Engineering
+You can improve the performance and quality of generating default prompts with the settings below.
+```
+{
+  "negative prompt": "sketches, (worst quality:2), (low quality:2), (normal quality:2), lowres, normal quality, ((monochrome)), ((grayscale)), skin spots, acnes, skin blemishes, age spot, (outdoor:1.6), manboobs, backlight, (ugly:1.331), (duplicate:1.331), (morbid:1.21), (mutilated:1.21), mutated hands, (poorly drawn hands:1.331), (bad anatomy:1.21), (bad proportions:1.331), extra limbs, (disfigured:1.331), (more than 2 nipples:1.331), (missing arms:1.331), (extra legs:1.331), (fused fingers:1.61051), (too many fingers:1.61051), (unclear eyes:1.331), bad hands, missing fingers, extra digit, (futa:1.1)",
+  "steps": 50,
+  "sampling method": "DPM++ 2M Karras"
+  "Width": "512",
+  "Height": "512",
+  "CFG scale": 12.0,
+  "seed": -1,
+}
+```
+### Annotations
+The DiffusionEmotion contains annotation process both 7-emotion classes and valence-arousal values.
+#### Annotation process
+This process was carried out inspired by the theory of the two research papers below.
+  - JA Russell, [A circumplex model of affect](https://d1wqtxts1xzle7.cloudfront.net/38425675/Russell1980-libre.pdf?1439132613=&response-content-disposition=inline%3B+filename%3DRussell1980.pdf&Expires=1678595455&Signature=UtbPsezND6w8vbISBiuL-ECk6hDI0etLcJSE7kJMC~hAkMSu9YyQcPKdVpdHSSq7idfcQ~eEKsqptvYpy0199DX0gi-nHJwhsciahC-zgDwylEUo6ykhP6Ab8VWCOW-DM21jHNvbYLQf7Pwi66fGvm~5bAXPc1o4HHpQpk-Cr7b0tW9lYnl3qgLoVeIICg6FLu0elbtVztgH5OS1uL6V~QhiP2PCwZf~WCHuJRQrWdPt5Kuco0lsNr1Qikk1~d7HY3ZcUTRZcMNDdem8XAFDH~ak3QER6Ml~JDkNFcLuygz~tjL4CdScVhByeAuMe3juyijtBFtYWH2h30iRkUDalg__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA)
+  - A Mollahosseini et al., [AffectNet](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8013713&casa_token=C3QmhmiB6Y8AAAAA:1CiUll0bhIq06M17YwFIvxuse7GOosEN9G1A8vxVzR8Vb5eaFp6ERIjg7xhSIQlf008KLsfJ-w&tag=1)
+#### Who are the annotators?
+[Daeha Kim](mailto:kdhht5022@gmail.com) and [Dohee Kang](mailto:asrs777@naver.com)
+## Additional Information
+### Dataset Curators
+DiffusionEmotion is created by [Daeha Kim](https://kdhht2334.github.io/) and [Dohee Kang](https://github.com/KangDohee2270).
+### Acknowledgments
+This repository is heavily inspired by [DiffusionDB](https://huggingface.co/datasets/poloclub/diffusiondb), with some format references. Thank you for your interest in [DiffusionDB](https://huggingface.co/datasets/poloclub/diffusiondb).
+### Licensing Information
+The DiffusionEmotion is available under the [CC0 1.0 License](https://creativecommons.org/publicdomain/zero/1.0/).
+### Contributions
+If you have any questions, feel free to [open an issue](https://github.com/kdhht2334/Facial-Expression-Recognition-Zoo/issues/new) or contact [Daeha Kim](https://kdhht2334.github.io/).