Mercurial > repos > bgruening > json2yolosegment
view preprocessing.py @ 0:252fd085940d draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit 67e0e1d123bcfffb10bab8cc04ae67259caec557
author | bgruening |
---|---|
date | Fri, 13 Jun 2025 11:23:35 +0000 |
parents | |
children | 97bc82ee2a61 |
line wrap: on
line source
import argparse import os import shutil from sklearn.model_selection import train_test_split def get_basename(f): return os.path.splitext(os.path.basename(f))[0] def pair_files(images_dir, labels_dir): img_files = [f for f in os.listdir(images_dir)] lbl_files = [f for f in os.listdir(labels_dir)] image_dict = {get_basename(f): f for f in img_files} label_dict = {get_basename(f): f for f in lbl_files} keys = sorted(set(image_dict) & set(label_dict)) return [(image_dict[k], label_dict[k]) for k in keys] def copy_pairs(pairs, image_src, label_src, image_dst, label_dst): os.makedirs(image_dst, exist_ok=True) os.makedirs(label_dst, exist_ok=True) for img, lbl in pairs: shutil.copy(os.path.join(image_src, img), os.path.join(image_dst, img)) shutil.copy(os.path.join(label_src, lbl), os.path.join(label_dst, lbl)) def write_yolo_yaml(output_dir): yolo_yaml_path = os.path.join(output_dir, "yolo.yml") with open(yolo_yaml_path, 'w') as f: f.write(f"path: {output_dir}\n") f.write("train: train\n") f.write("val: valid\n") f.write("test: test\n") f.write("\n") f.write("names: ['dataset']\n") def main(): parser = argparse.ArgumentParser() parser.add_argument("-i", "--images", required=True) parser.add_argument("-y", "--labels", required=True) parser.add_argument("-o", "--output", required=True) parser.add_argument("-p", "--train_percent", type=int, default=70) args = parser.parse_args() all_pairs = pair_files(args.images, args.labels) train_size = args.train_percent / 100.0 val_test_size = 1.0 - train_size train_pairs, val_test_pairs = train_test_split(all_pairs, test_size=val_test_size, random_state=42) val_pairs, test_pairs = train_test_split(val_test_pairs, test_size=0.5, random_state=42) copy_pairs(train_pairs, args.images, args.labels, os.path.join(args.output, "train/images"), os.path.join(args.output, "train/labels")) copy_pairs(val_pairs, args.images, args.labels, os.path.join(args.output, "valid/images"), os.path.join(args.output, "valid/labels")) copy_pairs(test_pairs, args.images, args.labels, os.path.join(args.output, "test/images"), os.path.join(args.output, "test/labels")) write_yolo_yaml(args.output) if __name__ == "__main__": main()