Duplicate from imadhavan/FER2025

Co-authored-by: Adhavan <imadhavan@users.noreply.huggingface.co>

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Angry.tar

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Disgust.tar

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Fear.tar

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Happy.tar

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Neutral.tar

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README.md

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+---
+
+name: "FER2025"
+tags: ["facial-emotion", "FER", "emotion-recognition", "deep-learning"]
+license: "cc-by-nc-4.0"
+
+---
+
+# FER2025 – Facial Expression Recognition Dataset
+
+[![License: Research Use Only](https://img.shields.io/badge/License-Research%20Use%20Only-lightgrey.svg)](#license--attribution)
+[![Total Images](https://img.shields.io/badge/Total%20Images-1.59M-blue)](#overview)
+[![Classes](https://img.shields.io/badge/Classes-7-green)](#overview)
+
+---
+
+## Overview
+
+**FER2025** is a **large-scale, balanced facial emotion dataset** designed for **deep learning and computer vision research**. It contains **1,589,810 images** across **7 emotion classes**:
+
+| Class      | Images  |
+|------------|---------|
+| Angry      | 224,624 |
+| Disgust    | 239,366 |
+| Fear       | 223,466 |
+| Happy      | 222,082 |
+| Neutral    | 234,230 |
+| Sad        | 217,884 |
+| Surprise   | 228,158 |
+
+**Image formats:** jpg, jpeg, png
+**Balanced:** Maximum class difference ≈ 1.3%  
+
+FER2025 is suitable for **feature extraction, model training, and benchmarking**and**Training deep learning model**.
+
+---
+
+## Dataset Structure
+
+FER2025/ ➡️ Angry.tar | Disgust.tar | Fear.tar | Happy.tar | Neutral.tar | Sad.tar | Surprise.tar
+
+Each TAR contains **images + corresponding `.cls` label files** for efficient streaming.
+
+---
+
+## Recommended Usage
+
+- **Feature Extraction:** ResNet, EfficientNet, ViT embeddings  
+- **Training & Evaluation:** Balanced classes remove need for oversampling or class weighting  
+- **Large-Scale Training:** Use TAR/WebDataset format for GPU-efficient streaming  
+
+---
+
+## Example: Loading FER2025 with PyTorch + WebDataset
+
+```python
+import webdataset as wds
+from torchvision import transforms
+import torch
+
+transform = transforms.Compose([
+    transforms.Resize((224,224)),
+    transforms.ToTensor(),
+])
+
+dataset = (
+    wds.WebDataset("FER2025/{Angry,Disgust,Fear,Happy,Neutral,Sad,Surprise}.tar")
+    .decode("pil")
+    .to_tuple("jpg", "cls")
+    .map_tuple(transform, int)
+)
+
+loader = torch.utils.data.DataLoader(dataset, batch_size=64, num_workers=4, shuffle=True)
+
+for images, labels in loader:
+    print(images.shape, labels.shape)
+    break
+```
+
+---
+
+## License & Ethical Use
+
+**License:** CC BY-NC 4.0 – Attribution required, non-commercial use
+
+**Ethical Use:** Images are sourced from publicly available data for research. Users must respect privacy and avoid commercial misuse.
+
+---
+
+## Citations
+
+@dataset
+{FER2025,
+  author = {Adhavan M},
+  title = {FER2025: Large-Scale Balanced Facial Expression Dataset},
+  year = {2025},
+  url = https://huggingface.co/datasets/imadhavan/FER2025
+}

Sad.tar

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Surprise.tar

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data.json

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+{
+  "name": "FER2025",
+  "description": "FER2025 is a large-scale, balanced facial emotion dataset containing 1,589,810 images across 7 emotion classes (Angry, Disgust, Fear, Happy, Neutral, Sad, Surprise). It is designed for feature extraction, model training, and benchmarking in computer vision and deep learning.",
+  "version": "1.0.0",
+  "total_images": 1589810,
+  "classes": ["Angry", "Disgust", "Fear", "Happy", "Neutral", "Sad", "Surprise"],
+  "formats": ["jpg", "jpeg", "png"],
+  "recommended_usage": [
+    "Feature extraction with CNNs or ViT",
+    "Training deep learning models",
+    "Benchmarking facial expression recognition algorithms"
+  ],
+  "dataset_structure": [
+    "Sharded TAR/WebDataset: FER2025/ClassName.tar (images + .cls labels)"
+  ],
+  "license": "Research-use-only",
+  "usage_notes": "FER2025 is for research and non-commercial purposes only. Users must respect the licenses of the original datasets included (FER2013, AffectNet, CK+, RAF-DB, etc.) and provide proper attribution.",
+  "source_datasets": [
+    {"name": "FER2013", "license": "CC BY-NC"},
+    {"name": "AffectNet", "license": "Research-use-only"},
+    {"name": "CK+", "license": "Research-use-only"},
+    {"name": "RAF-DB", "license": "Research-use-only"}
+  ],
+  "citation": "Adhavan M. FER2025: Large-Scale Balanced Facial Expression Dataset. 2025. URL: https://huggingface.co/datasets/imadhavan/FER2025"
+}