Datasets:
Tasks:
Text-to-Image
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
1K - 10K
Tags:
stable diffusion
prompt engineering
prompts
research paper
facial expression recognition
emotion recognition
License:
| layout: default | |
| title: Home | |
| nav_order: 1 | |
| has_children: false | |
| annotations_creators: | |
| - no-annotation | |
| language: | |
| - en | |
| language_creators: | |
| - found | |
| pretty_name: DiffusionFER | |
| 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:** [DiffusionFER homepage](https://kdhht2334.github.io/) | |
| - **Repository:** [DiffusionFER repository](https://github.com/kdhht2334/Facial-Expression-Recognition-Zoo) | |
| - **Distribution:** [DiffusionFER Hugging Face Dataset](https://huggingface.co/datasets/FER-Universe/DiffusionFER) | |
| - **Point of Contact:** [Daeha Kim](mailto:kdhht5022@gmail.com) | |
| ### Summary | |
| DiffusionFER 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. | |
| DiffusionFER is available at [🤗 Hugging Face Dataset](https://huggingface.co/datasets/FER-Universe/DiffusionFER). | |
| ### Downstream Tasks and Leaderboards | |
| This DiffusionFER 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 | |
| DiffusionFER 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("FER-Universe/DiffusionFER") | |
| ``` | |
| ```bash | |
| git lfs install | |
| git clone https://huggingface.co/datasets/FER-Universe/DiffusionFER | |
| ``` | |
| ### Pre-trained model | |
| You can easily download and use pre-trained __Swin Transformer__ model with the `Diffusion_Emotion_S` dataset. | |
| Later, Transformer models with the `Diffusion_Emotion_M` or `Diffusion_Emotion_L` will be released. | |
| ```python | |
| from transformers import AutoFeatureExtractor, AutoModelForImageClassification | |
| extractor = AutoFeatureExtractor.from_pretrained("kdhht2334/autotrain-diffusion-emotion-facial-expression-recognition-40429105176") | |
| model = AutoModelForImageClassification.from_pretrained("kdhht2334/autotrain-diffusion-emotion-facial-expression-recognition-40429105176") | |
| ``` | |
| Or just clone the model repo | |
| ```bash | |
| git lfs install | |
| git clone https://huggingface.co/kdhht2334/autotrain-diffusion-emotion-facial-expression-recognition-40429105176 | |
| ``` | |
| - Quick links: [huggingface model documentation](https://huggingface.co/docs/transformers/main/en/model_doc/swin#transformers.SwinForImageClassification) | |
| ### Sample Gallery | |
| â–¼Happy | |
|  | |
| â–¼Angry | |
|  | |
| ### Subsets | |
| DiffusionFER 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 DiffusionFER 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 | |
| ``` | |
| - Middle size DB will be uploaded soon. | |
| ```bash | |
| # Medium version of DB | |
| (ongoing) | |
| ``` | |
| - TBD | |
| ```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) one person, 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, smiley<br>sad emotion, with tears, lowered head, droopy eyebrows<br>surprise emotion, with open mouth, big eyes<br>fear emotion, scared, haunted<br>disgust emotion, frown, angry expression with open mouth<br>angry emotion, with open mouth, frown eyebrow, fierce, furious | | |
| | `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>mature<br>punky<br>freckles<br>beautiful crystal eyes<br>big eyes<br>small nose<br>... | | |
| | `Others` | 4K<br>8K<br>cyberpunk<br>camping<br>ancient<br>medieval Europe<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, backlight, (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), (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", | |
| "steps": 50, | |
| "sampling method": "DPM++ 2M Karras" | |
| "Width": "512", | |
| "Height": "512", | |
| "CFG scale": 12.0, | |
| "seed": -1, | |
| } | |
| ``` | |
| ### Annotations | |
| The DiffusionFER 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 | |
| DiffusionFER 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 DiffusionFER is available under the [CC0 1.0 License](https://creativecommons.org/publicdomain/zero/1.0/). NOTE: The primary purpose of this dataset is research. We are not responsible if you take any other action using this dataset. | |
| ### 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/). |