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ScalpPipeline (pipeline.py)
Refactored pipeline combining all steps into a single class.
Usage
python pipeline.py --pixel_ratio 2.54
Arguments:
--root_dir: Root directory of the project (default:.)--pixel_ratio: Pixel to micrometer ratio (default:2.54)
Dependencies (Files)
The pipeline requires the following files and directories to exist:
Input Images:
datasets/data/: Directory containing input images (.jpg,.jpeg,.png).
Model Weights:
segmentation/model/U2NET.pth: Pre-trained U2NET model.sam_vit_h_4b8939.pth: SAM (Segment Anything Model) checkpoint (ViT-H).
Code Modules:
segmentation/data_loader.py: Data loading utilities for U2NET.
Output
Results are saved in:
datasets/seg_train/(U2NET masks)prediction/sam_result/sam_val/(SAM masks)prediction/ensemble_result/ensemble_val/(Ensemble masks)alopecia/thickness_result/(Thickness data & visualization)alopecia/count_result/(Hair count CSV & visualization)
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