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Description
Patchmentation Core Function
- Collections
- BBox
- Mask
- Image
- Patch
- ImagePatch
- Dataset
- Filtering
- Filter by width
- Filter by height
- Filter by aspect ratio
- Transform
- Resize
- Random resize
- Scale
- Random scale
- Grayscale
- Random grayscale
- Visibility thresholding
- Patch distribution
- Patch blending mode
- Hard edge
- Soft edge
- Negative patching
- Background patching
Description: Sometimes background already has positive patches. We want to preserve it.
Dataset
- Dataset loader
- Loader for YOLO format dataset
- Loader for COCO format dataset
- Loader for Pascal VOC format dataset
- Default dataset
- COCO 2017
- COCO 2014
- PASCAL VOC 2007
- PASCAL VOC 2012
- Penn-Fudan Database for Pedestrian Detection and Segmentation
Automation
- GitHub actions test
- PyPI deployment
- Deployment script
- Deployment automation with GitHub action
Additional Tasks
- README for patchmentation
- Documentation
- Docstrings
Benchmarking
- Benchmarking on Pascal VOC / COCO dataset using YOLOv?
- Custom dataset for benchmarking
- Benchmarking on a custom dataset using YOLOv?
Development Tools / Optimization (Optional)
- Visualization using Streamlit
- Conditional package installation (reference)
- Docker environment
- Implement caching
- Shape, width, height, channel
- Fix code formatting
- Implements property / descriptors to collections
- Account gamma corrections when blending colors (reference)
- Optimize mask saving for image with no transparency
- Add progress bar when loading a dataset
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