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It supports multiple obfuscation modes such as **blur**, **pixelate**, and **emoji overlay**. The project is designed as a portfolio‑ready demo with a clean CLI, documentation, and tests.\n\n## Repository Structure\n\n```\nface-anonymizer/\n├─ src/              # Source code (main CLI)\n├─ test/             # Tests and examples\n├─ docs/             # Documentation\n│  └─ assets/        # Images, diagrams\n├─ models/           # Model files (not tracked)\n├─ data/             # Local datasets (not tracked)\n├─ notebooks/        # Jupyter notebooks (optional)\n├─ build/            # Output files (not tracked)\n├─ configs/          # Config files (YAML)\n├─ archive/          # Legacy code\n├─ requirements.txt  # Minimal dependencies\n├─ LICENSE           # MIT License\n└─ README.md         # Project description\n```\n\n## Getting Started\n\n### Prerequisites\n\n* Python 3.10+\n* Install dependencies:\n\n```powershell\npip install -r requirements.txt\n```\n\n### Usage\n\n#### Anonymize an Image\n\n```powershell\npython .\\src\\main.py --input .\\data\\your_image.jpg --method blur --output .\\build\\out.jpg\n```\n\n#### Anonymize a Video\n\n```powershell\npython .\\src\\main.py --input .\\data\\your_video.mp4 --method pixelate --output .\\build\\out_video.mp4\n```\n\n#### Anonymize from Webcam\n\n```powershell\npython .\\src\\main.py --webcam 0 --method blur --draw --output .\\build\\out_cam.mp4\n```\n\n#### Use Emoji Overlay\n\n```powershell\npython .\\src\\main.py --input .\\data\\your_image.jpg --method emoji --emoji .\\data\\emoji.png --output .\\build\\emoji_image.png\n```\n\n### CLI Options\n\n* `--input / -i`: Path to image or video.\n* `--webcam / -w`: Webcam index (default 0).\n* `--method / -m`: Anonymization method (`blur`, `pixelate`, `emoji`).\n* `--emoji`: Path to PNG emoji (required for `--method emoji`).\n* `--draw`: Draw bounding boxes around detected faces.\n* `--output / -o`: Output path for anonymized media.\n* `--config / -c`: YAML config file for detector settings.\n\n## Dataset \u0026 Models\n\n* Place your own media in `data/`. See [data/README.md](data/README.md).\n* Place pretrained models or cascade files in `models/` (not tracked). Add instructions in `models/README.md`.\n\n## Features\n\n* Real‑time face detection using MediaPipe.\n* Multiple anonymization modes (blur, pixelate, emoji overlay).\n* Simple CLI with PowerShell examples.\n* Modular codebase with configs and archive for legacy code.\n\n## What I Learned\n\n* Practical integration of MediaPipe FaceDetection with OpenCV.\n* Building a CLI‑based tool with relative paths and configs.\n* Managing datasets/models in a portfolio‑ready structure.\n* Using conventional commits and clear repository scaffolding.\n\n## Roadmap\n\n* [ ] Add test suite in `test/`.\n* [ ] Expand anonymization methods (mosaic, cartoon).\n* [ ] Dockerfile for containerized usage.\n* [ ] Optional GPU acceleration.\n\n## License\n\nThis project is licensed under the MIT License – see the [LICENSE](LICENSE) file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falbertomarquillas%2Fface-anonymizer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falbertomarquillas%2Fface-anonymizer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falbertomarquillas%2Fface-anonymizer/lists"}