Finding all image-label pairs...
Found 1500 unique image-label pairs

Splitting dataset (80% train, 10% val, 10% test)...
  Train: 1200 pairs (should be 1200)
  Val:   150 pairs (should be 150)
  Test:  150 pairs (should be 150)

Copying 1200 files to train...

  train:   0%|          | 0/1200 [00:00<?, ?it/s]
  train:   1%|1         | 15/1200 [00:00<00:08, 147.73it/s]
  train:   3%|2         | 31/1200 [00:00<00:07, 149.66it/s]
  train:   4%|3         | 46/1200 [00:00<00:07, 148.04it/s]
  train:   5%|5         | 61/1200 [00:00<00:07, 145.73it/s]
  train:   6%|6         | 76/1200 [00:00<00:07, 144.29it/s]
  train:   8%|7         | 91/1200 [00:00<00:07, 144.02it/s]
  train:   9%|8         | 106/1200 [00:00<00:07, 143.16it/s]
  train:  10%|#         | 121/1200 [00:00<00:07, 143.70it/s]
  train:  11%|#1        | 136/1200 [00:00<00:07, 138.66it/s]
  train:  12%|#2        | 150/1200 [00:01<00:07, 137.23it/s]
  train:  14%|#3        | 164/1200 [00:01<00:07, 135.00it/s]
  train:  15%|#5        | 180/1200 [00:01<00:07, 139.19it/s]
  train:  16%|#6        | 194/1200 [00:01<00:07, 137.42it/s]
  train:  17%|#7        | 208/1200 [00:01<00:07, 136.94it/s]
  train:  18%|#8        | 222/1200 [00:01<00:07, 135.75it/s]
  train:  20%|#9        | 237/1200 [00:01<00:06, 139.65it/s]
  train:  21%|##        | 251/1200 [00:01<00:07, 129.33it/s]
  train:  22%|##2       | 265/1200 [00:01<00:07, 130.33it/s]
  train:  23%|##3       | 280/1200 [00:02<00:06, 134.53it/s]
  train:  25%|##4       | 296/1200 [00:02<00:06, 140.81it/s]
  train:  26%|##6       | 312/1200 [00:02<00:06, 144.65it/s]
  train:  27%|##7       | 327/1200 [00:02<00:06, 138.37it/s]
  train:  28%|##8       | 341/1200 [00:02<00:06, 135.72it/s]
  train:  30%|##9       | 355/1200 [00:02<00:06, 129.09it/s]
  train:  31%|###       | 370/1200 [00:02<00:06, 131.39it/s]
  train:  32%|###2      | 385/1200 [00:02<00:06, 134.27it/s]
  train:  33%|###3      | 400/1200 [00:02<00:05, 137.87it/s]
  train:  34%|###4      | 414/1200 [00:03<00:05, 131.67it/s]
  train:  36%|###5      | 429/1200 [00:03<00:05, 134.05it/s]
  train:  37%|###7      | 444/1200 [00:03<00:05, 136.15it/s]
  train:  38%|###8      | 459/1200 [00:03<00:05, 138.04it/s]
  train:  39%|###9      | 473/1200 [00:03<00:05, 138.46it/s]
  train:  41%|####      | 487/1200 [00:03<00:05, 138.48it/s]
  train:  42%|####1     | 501/1200 [00:03<00:05, 137.95it/s]
  train:  43%|####2     | 515/1200 [00:03<00:05, 135.56it/s]
  train:  44%|####4     | 530/1200 [00:03<00:04, 137.32it/s]
  train:  45%|####5     | 544/1200 [00:03<00:04, 135.31it/s]
  train:  46%|####6     | 558/1200 [00:04<00:04, 133.81it/s]
  train:  48%|####7     | 573/1200 [00:04<00:04, 136.71it/s]
  train:  49%|####8     | 587/1200 [00:04<00:04, 137.45it/s]
  train:  50%|#####     | 601/1200 [00:04<00:04, 137.15it/s]
  train:  51%|#####1    | 616/1200 [00:04<00:04, 139.47it/s]
  train:  52%|#####2    | 630/1200 [00:04<00:04, 137.44it/s]
  train:  54%|#####3    | 645/1200 [00:04<00:03, 140.06it/s]
  train:  55%|#####5    | 660/1200 [00:04<00:03, 139.09it/s]
  train:  56%|#####6    | 674/1200 [00:04<00:03, 133.37it/s]
  train:  57%|#####7    | 688/1200 [00:05<00:04, 127.29it/s]
  train:  58%|#####8    | 701/1200 [00:05<00:03, 127.51it/s]
  train:  60%|#####9    | 715/1200 [00:05<00:03, 129.37it/s]
  train:  61%|######    | 728/1200 [00:05<00:03, 127.30it/s]
  train:  62%|######2   | 744/1200 [00:05<00:03, 136.08it/s]
  train:  63%|######3   | 759/1200 [00:05<00:03, 139.08it/s]
  train:  64%|######4   | 773/1200 [00:05<00:03, 138.73it/s]
  train:  66%|######5   | 787/1200 [00:05<00:03, 133.05it/s]
  train:  67%|######6   | 801/1200 [00:05<00:03, 131.26it/s]
  train:  68%|######7   | 815/1200 [00:05<00:02, 129.68it/s]
  train:  69%|######9   | 830/1200 [00:06<00:02, 135.20it/s]
  train:  70%|#######   | 844/1200 [00:06<00:02, 128.28it/s]
  train:  72%|#######1  | 858/1200 [00:06<00:02, 131.50it/s]
  train:  73%|#######2  | 872/1200 [00:06<00:02, 132.38it/s]
  train:  74%|#######3  | 886/1200 [00:06<00:02, 134.00it/s]
  train:  75%|#######5  | 900/1200 [00:06<00:02, 126.39it/s]
  train:  76%|#######6  | 914/1200 [00:06<00:02, 129.61it/s]
  train:  77%|#######7  | 928/1200 [00:06<00:02, 128.12it/s]
  train:  78%|#######8  | 941/1200 [00:06<00:02, 128.59it/s]
  train:  80%|#######9  | 954/1200 [00:07<00:01, 126.27it/s]
  train:  81%|########  | 967/1200 [00:07<00:01, 124.99it/s]
  train:  82%|########1 | 983/1200 [00:07<00:01, 132.53it/s]
  train:  83%|########3 | 997/1200 [00:07<00:01, 133.82it/s]
  train:  84%|########4 | 1012/1200 [00:07<00:01, 137.23it/s]
  train:  86%|########5 | 1028/1200 [00:07<00:01, 140.46it/s]
  train:  87%|########6 | 1043/1200 [00:07<00:01, 138.32it/s]
  train:  88%|########8 | 1057/1200 [00:07<00:01, 135.13it/s]
  train:  89%|########9 | 1071/1200 [00:07<00:00, 132.91it/s]
  train:  90%|######### | 1085/1200 [00:08<00:00, 126.40it/s]
  train:  92%|#########1| 1100/1200 [00:08<00:00, 130.89it/s]
  train:  93%|#########2| 1114/1200 [00:08<00:00, 126.20it/s]
  train:  94%|#########3| 1128/1200 [00:08<00:00, 129.08it/s]
  train:  95%|#########5| 1142/1200 [00:08<00:00, 128.86it/s]
  train:  96%|#########6| 1156/1200 [00:08<00:00, 130.76it/s]
  train:  98%|#########7| 1170/1200 [00:08<00:00, 132.42it/s]
  train:  99%|#########8| 1184/1200 [00:08<00:00, 131.78it/s]
  train: 100%|#########9| 1198/1200 [00:08<00:00, 125.32it/s]
  train: 100%|##########| 1200/1200 [00:08<00:00, 134.27it/s]

Copying 150 files to val...

  val:   0%|          | 0/150 [00:00<?, ?it/s]
  val:   9%|8         | 13/150 [00:00<00:01, 122.03it/s]
  val:  17%|#7        | 26/150 [00:00<00:01, 123.63it/s]
  val:  28%|##8       | 42/150 [00:00<00:00, 138.84it/s]
  val:  37%|###7      | 56/150 [00:00<00:00, 133.35it/s]
  val:  47%|####6     | 70/150 [00:00<00:00, 131.76it/s]
  val:  57%|#####6    | 85/150 [00:00<00:00, 136.72it/s]
  val:  66%|######6   | 99/150 [00:00<00:00, 136.24it/s]
  val:  75%|#######5  | 113/150 [00:00<00:00, 129.22it/s]
  val:  85%|########4 | 127/150 [00:00<00:00, 131.40it/s]
  val:  94%|#########3| 141/150 [00:01<00:00, 131.03it/s]
  val: 100%|##########| 150/150 [00:01<00:00, 132.65it/s]

Copying 150 files to test...

  test:   0%|          | 0/150 [00:00<?, ?it/s]
  test:  11%|#         | 16/150 [00:00<00:00, 154.96it/s]
  test:  21%|##1       | 32/150 [00:00<00:00, 142.70it/s]
  test:  31%|###1      | 47/150 [00:00<00:00, 137.28it/s]
  test:  41%|####      | 61/150 [00:00<00:00, 129.05it/s]
  test:  49%|####9     | 74/150 [00:00<00:00, 125.64it/s]
  test:  58%|#####8    | 87/150 [00:00<00:00, 124.07it/s]
  test:  67%|######7   | 101/150 [00:00<00:00, 126.78it/s]
  test:  77%|#######6  | 115/150 [00:00<00:00, 124.93it/s]
  test:  85%|########5 | 128/150 [00:01<00:00, 122.65it/s]
  test:  94%|#########3| 141/150 [00:01<00:00, 119.77it/s]
  test: 100%|##########| 150/150 [00:01<00:00, 126.80it/s]

Created data.yaml: C:\Users\82104\Downloads\COCO_format\dataset\data.yaml

============================================================
Dataset split completed!
============================================================
Output directory: C:\Users\82104\Downloads\COCO_format\dataset

Structure:
  dataset/
    戍式式 images/
    弛   戍式式 train/  (1200 images)
    弛   戍式式 val/    (150 images)
    弛   戌式式 test/   (150 images)
    戍式式 labels/
    弛   戍式式 train/  (1200 labels)
    弛   戍式式 val/    (150 labels)
    弛   戌式式 test/   (150 labels)
    戌式式 data.yaml