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annotate preprocessing.py @ 1:dfda27273ead draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit 9685f843a52451b3416416094cc0e740f8825dcc
author bgruening
date Mon, 07 Jul 2025 06:47:08 +0000
parents 252fd085940d
children 97bc82ee2a61
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252fd085940d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit 67e0e1d123bcfffb10bab8cc04ae67259caec557
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1 import argparse
252fd085940d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit 67e0e1d123bcfffb10bab8cc04ae67259caec557
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2 import os
252fd085940d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit 67e0e1d123bcfffb10bab8cc04ae67259caec557
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3 import shutil
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5 from sklearn.model_selection import train_test_split
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8 def get_basename(f):
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9 return os.path.splitext(os.path.basename(f))[0]
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12 def pair_files(images_dir, labels_dir):
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14 img_files = [f for f in os.listdir(images_dir)]
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15 lbl_files = [f for f in os.listdir(labels_dir)]
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17 image_dict = {get_basename(f): f for f in img_files}
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18 label_dict = {get_basename(f): f for f in lbl_files}
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20 keys = sorted(set(image_dict) & set(label_dict))
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22 return [(image_dict[k], label_dict[k]) for k in keys]
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25 def copy_pairs(pairs, image_src, label_src, image_dst, label_dst):
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26 os.makedirs(image_dst, exist_ok=True)
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27 os.makedirs(label_dst, exist_ok=True)
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28 for img, lbl in pairs:
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29 shutil.copy(os.path.join(image_src, img), os.path.join(image_dst, img))
252fd085940d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit 67e0e1d123bcfffb10bab8cc04ae67259caec557
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30 shutil.copy(os.path.join(label_src, lbl), os.path.join(label_dst, lbl))
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33 def write_yolo_yaml(output_dir):
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35 yolo_yaml_path = os.path.join(output_dir, "yolo.yml")
252fd085940d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit 67e0e1d123bcfffb10bab8cc04ae67259caec557
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36 with open(yolo_yaml_path, 'w') as f:
252fd085940d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit 67e0e1d123bcfffb10bab8cc04ae67259caec557
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37 f.write(f"path: {output_dir}\n")
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38 f.write("train: train\n")
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39 f.write("val: valid\n")
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40 f.write("test: test\n")
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41 f.write("\n")
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42 f.write("names: ['dataset']\n")
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45 def main():
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46 parser = argparse.ArgumentParser()
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47 parser.add_argument("-i", "--images", required=True)
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48 parser.add_argument("-y", "--labels", required=True)
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49 parser.add_argument("-o", "--output", required=True)
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50 parser.add_argument("-p", "--train_percent", type=int, default=70)
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51 args = parser.parse_args()
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53 all_pairs = pair_files(args.images, args.labels)
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54 train_size = args.train_percent / 100.0
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55 val_test_size = 1.0 - train_size
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57 train_pairs, val_test_pairs = train_test_split(all_pairs, test_size=val_test_size, random_state=42)
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58 val_pairs, test_pairs = train_test_split(val_test_pairs, test_size=0.5, random_state=42)
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60 copy_pairs(train_pairs, args.images, args.labels, os.path.join(args.output, "train/images"), os.path.join(args.output, "train/labels"))
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61 copy_pairs(val_pairs, args.images, args.labels, os.path.join(args.output, "valid/images"), os.path.join(args.output, "valid/labels"))
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62 copy_pairs(test_pairs, args.images, args.labels, os.path.join(args.output, "test/images"), os.path.join(args.output, "test/labels"))
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64 write_yolo_yaml(args.output)
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67 if __name__ == "__main__":
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68 main()