{"id":30384420,"url":"https://github.com/noxs1d/cv-emotion-classification","last_synced_at":"2026-04-09T02:02:22.603Z","repository":{"id":310020106,"uuid":"1029926094","full_name":"noxs1d/cv-emotion-classification","owner":"noxs1d","description":"This project is a deep learning-based system for detecting human emotions from facial images using TensorFlow, OpenCV, and NumPy. 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It is trained on the FER-2013 dataset and offers two model variants:\n\n* A custom-built CNN (Convolutional Neural Network)\n* A transfer learning model based on pre-trained VGG16\n\n---\n\n## 🧠 Features\n\n* Real-time emotion detection via webcam (OpenCV)\n* FER-2013 dataset support (7 emotion classes)\n* Two models: scratch-trained CNN and VGG16-based transfer learning\n* Pretrained models included\n* Architecture overview diagram included (see assets)\n\n---\n\n## 🔍 Emotion Classes\n\n* Angry\n* Disgust\n* Fear\n* Happy\n* Sad\n* Surprise\n* Neutral\n\n---\n\n## 📂 Project Structure\n\n```\n.\n├── main.py                    # Main script for webcam-based emotion detection\n├── README.md\n│\n├── models/                   # Saved model files\n│   ├── fer2013_model_tensorflow.h5\n│   └── pretrained_model.keras\n│\n├── notebook/                 # Jupyter Notebook for exploration and training\n│   └── CV_project.ipynb\n│\n├── __pycache__/             # Compiled Python cache\n│   └── main.cpython-312.pyc\n│\n└── .idea/                   # IDE configuration (PyCharm)\n```\n\n---\n\n## 🧱 Model Architecture Diagram\n\n![Model Architecture](img/IMG_4942.PNG)\n\n---\n\n## 🚀 Getting Started\n\n### Install Requirements\n\n```bash\npip install -r requirements.txt\n```\n\n### Run the Application\n\n```bash\npython main.py\n```\n\n### Train Your Own Model (optional)\n\nOpen the notebook:\n\n```\nnotebook/CV_project.ipynb\n```\n\n---\n\n## 🐳 Docker Support\n\nDockerfile example:\n\n```Dockerfile\nFROM python:3.10-slim\nWORKDIR /app\nCOPY requirements.txt .\nRUN pip install --no-cache-dir -r requirements.txt\nCOPY . .\nCMD [\"python\", \"main.py\"]\n```\n\nBuild \u0026 run:\n\n```bash\ndocker build -t emotion-detector .\ndocker run --rm -it emotion-detector\n```\n\n---\n\n## 📈 Results\n\n| Model                     | Accuracy | Val Accuracy |\n| ------------------------- |----------| ------------ |\n| Custom CNN                | \\~60%    | \\~54%        |\n| VGG16 (Transfer Learning) | \\~94%    | \\~65%        |\n\n---\n\n## 📄 License\n\nThis project is released under the MIT License.\n\n---\n\n## 🙌 Credits\n\n* FER-2013 Dataset (Kaggle)\n* TensorFlow / Keras\n* OpenCV\n* NumPy\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnoxs1d%2Fcv-emotion-classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnoxs1d%2Fcv-emotion-classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnoxs1d%2Fcv-emotion-classification/lists"}