{"id":26397688,"url":"https://github.com/hissain/dnn_vfi","last_synced_at":"2026-05-31T23:31:41.966Z","repository":{"id":278039534,"uuid":"934320171","full_name":"hissain/dnn_vfi","owner":"hissain","description":"This repository contains a machine learning demo for video frame interpolation (VFI) using three different models: UNet, RIFE, and Mamba. The goal is to predict an intermediate frame (2nd frame) given the 1st and 3rd frames as input. 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The goal is to predict an intermediate frame (2nd frame) given the 1st and 3rd frames as input. The project is under the MIT license.\n\n## 📂 Project Structure\n```\n.\n├── LICENSE                # MIT License\n├── README.md              # Project Documentation\n├── __pycache__/           # Compiled Python files\n├── input/                 # Sample videos\n│   ├── enjoy.mp4\n│   ├── glob.mp4\n│   └── motion.mp4\n├── mamba/                 # Mamba-based VFI\n│   ├── vfi.ipynb\n│   └── vfi_model.py\n├── requirements.txt       # Required dependencies\n├── rife/                  # RIFE-based VFI\n│   └── RIFE.ipynb\n└── unet/                  # UNet-based VFI\n    ├── Unet2d.ipynb\n    └── Unet3d.ipynb\n```\n\n## 🚀 Models Implemented\n\n__UNet:__ Convolutional neural network (CNN) based architecture for frame interpolation.\n\n__RIFE:__ Real-time Intermediate Flow Estimation model.\n\n__Mamba:__ A sequence modeling architecture applied to frame interpolation.\n\n## 📌 Features\n\n* Sample videos included for testing.\n\n* Frame extraction and dataset preparation.\n\n* Training notebooks for different models.\n\n## 🔧 Installation\n\nClone the repository and install dependencies:\n\n```\ngit clone https://github.com/hissain/dnn_vfi.git\ncd dnn_vfi\npip install -r requirements.txt\n```\n\n## 📊 Usage\n\nRun the corresponding Jupyter notebooks inside the mamba/, rife/, or unet/ directories to train and evaluate the models.\n\njupyter notebook\n\n## 📜 License\n\nThis project is licensed under the MIT License - see the LICENSE file for details.\n\n## 🤝 Contributing\n\nFeel free to submit issues or pull requests to improve the project!\n\n## 📬 Contact\n\nFor any inquiries, reach out to [hissain.khan@gmail.com] or create an issue in the repository.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhissain%2Fdnn_vfi","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhissain%2Fdnn_vfi","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhissain%2Fdnn_vfi/lists"}