{"id":24037345,"url":"https://github.com/pd-mera/object-detection-data-synthesis","last_synced_at":"2026-06-07T20:31:50.860Z","repository":{"id":235769104,"uuid":"791135801","full_name":"PD-Mera/object-detection-data-synthesis","owner":"PD-Mera","description":"Synthesis data in YOLO format given background and object 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Object Detection Data Synthesis\n\nData Synthesis pipeline to generate object detection data\n\n\u003ca href=\"https://pypi.org/project/mdetsyn/\"\u003e\u003cimg alt=\"Alt text\" src=\"https://img.shields.io/badge/PyPI-3775A9.svg?style=for-the-badge\u0026logo=PyPI\u0026logoColor=white\"/\u003e\u003c/a\u003e\n\n## How to run\n\n### Run with pip\n\n``` bash\npip install mdetsyn\n```\n\nAnd run in python file \n\n``` python\nfrom mdetsyn import run_synthesis, create_args\n\nargs = create_args()\nrun_synthesis(args)\n```\n\n### Run with command line\n\n``` bash\npython synthesis.py --backgrounds ./backgrounds \\\n                    --objects ./objects \\\n                    --savename ./synthesis \\\n                    --number 1000 \\\n                    --class_mapping ./class_mapping.json \\\n                    --class_txt ./classes.txt\n```\n\n## Sample\n\n- Backgrounds folder contain background images (in any folmat)\n\n```\n├── backgrounds/\n    ├── background-0.jpg\n    ├── background-1.jpg\n    └── ...\n```\n\n- Objects folder contain object images in subfolders (the best is `.png` format with `A` channel but any format is still runnable)\n\n```\n├── objects/\n    ├── class_1/\n    │   ├── image-0.png\n    │   ├── image-1.png\n    │   └── ...\n    ├── class_2/\n    └── ...\n```\n\n- Each image in objects folder will be synthesis by `n` times with `n` is user input\n\n- Output is a synthesis folder contain `images` and `labels` dir same as YOLO format\n\n- Sample visualization:\n\n| Background | Object | Synthesis |\n| :---: | :---: | :---: |\n| ![](./sample/backgrounds/background-0.jpg) | ![](./sample/objects/vanamo/vanamo-0.png) | ![](./sample/synthesis/images/4b09b7ae-3290-45d7-afef-82a7c5cef26d.jpg) |\n\n## Support synthesis methods\n\n- Random Resize\n- Random Rotate\n- Random Transparency\n- Random Perspective Transform\n- Seamless Clone\n- Grayscale\n\n## Error and TODO\n\n- [ ] Sometimes seamless clone does not work\n- [x] Input parameter for each augment\n- [ ] Add default arguments to argparse help","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpd-mera%2Fobject-detection-data-synthesis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpd-mera%2Fobject-detection-data-synthesis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpd-mera%2Fobject-detection-data-synthesis/lists"}