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Optim code.
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5 files changed

+180
-6
lines changed

‎darknet2coco.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -11,7 +11,7 @@
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import cv2 as cv
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class DARKNET2COCO:
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class DARKNET2COCO():
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def __init__(self, genconfig_data):
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self.src_data = genconfig_data
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self.src = Path(self.src_data).parent

‎dataset/YOLOV5_COCO_format/annotations/instances_train2017.json‎

Lines changed: 175 additions & 1 deletion
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{"info": {"year": 2022, "version": "1.0", "description": "For object detection", "date_created": "2022"}, "images": [{"date_captured": "2022", "file_name": "000000000001.jpg", "id": 1, "height": 224, "width": 224}, {"date_captured": "2022", "file_name": "000000000002.jpg", "id": 2, "height": 424, "width": 550}], "licenses": [{"id": 1, "name": "Apache License v2.0", "url": "https://github.com/RapidAI/YOLO2COCO/LICENSE"}], "type": "instances", "annotations": [{"segmentation": [[18.000080000000004, 2.999920000000003, 105.000112, 2.999920000000003, 105.000112, 89.000016, 18.000080000000004, 89.000016]], "area": 7482.011104003072, "iscrowd": 0, "image_id": 1, "bbox": [18.000080000000004, 2.999920000000003, 87.000032, 86.000096], "category_id": 1, "id": 1}, {"segmentation": [[126.99993599999999, 3.9999679999999955, 210.999936, 3.9999679999999955, 210.999936, 88.999904, 126.99993599999999, 88.999904]], "area": 7139.994624000001, "iscrowd": 0, "image_id": 1, "bbox": [126.99993599999999, 3.9999679999999955, 84.0, 84.999936], "category_id": 1, "id": 2}, {"segmentation": [[74.99990400000002, 76.000064, 150.99996800000002, 76.000064, 150.99996800000002, 153.000064, 74.99990400000002, 153.000064]], "area": 5852.004927999999, "iscrowd": 0, "image_id": 1, "bbox": [74.99990400000002, 76.000064, 76.000064, 77.0], "category_id": 1, "id": 3}, {"segmentation": [[12.000127999999997, 135.000096, 97.00006400000001, 135.000096, 97.00006400000001, 220.00003200000003, 12.000127999999997, 220.00003200000003]], "area": 7224.989120004097, "iscrowd": 0, "image_id": 1, "bbox": [12.000127999999997, 135.000096, 84.999936, 84.999936], "category_id": 1, "id": 4}, {"segmentation": [[132.00006399999998, 136.999968, 215.00012799999996, 136.999968, 215.00012799999996, 220.00003199999998, 132.00006399999998, 220.00003199999998]], "area": 6889.010624004095, "iscrowd": 0, "image_id": 1, "bbox": [132.00006399999998, 136.999968, 83.000064, 83.000064], "category_id": 1, "id": 5}, {"segmentation": [], "area": 0, "iscrowd": 0, "image_id": 2, "bbox": [], "category_id": -1, "id": 6}], "categories": [{"supercategory": "stamp", "id": 1, "name": "stamp"}]}
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{
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"info": {
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"year": 2022,
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"version": "1.0",
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"description": "For object detection",
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"date_created": "2022"
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},
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"images": [
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{
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"date_captured": "2022",
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"file_name": "000000000001.jpg",
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"id": 1,
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"height": 224,
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"width": 224
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},
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{
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"date_captured": "2022",
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"file_name": "000000000002.jpg",
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"id": 2,
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"height": 424,
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"width": 550
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}
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],
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"licenses": [
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{
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"id": 1,
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"name": "Apache License v2.0",
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"url": "https://github.com/RapidAI/YOLO2COCO/LICENSE"
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}
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],
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"type": "instances",
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"annotations": [
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{
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"segmentation": [
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[
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18.000080000000004,
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2.999920000000003,
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105.000112,
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2.999920000000003,
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105.000112,
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89.000016,
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18.000080000000004,
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89.000016
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]
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],
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"area": 7482.011104003072,
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"iscrowd": 0,
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"image_id": 1,
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"bbox": [
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18.000080000000004,
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2.999920000000003,
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87.000032,
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86.000096
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],
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"category_id": 1,
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"id": 1
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},
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{
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"segmentation": [
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[
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126.99993599999999,
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3.9999679999999955,
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210.999936,
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3.9999679999999955,
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210.999936,
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88.999904,
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126.99993599999999,
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88.999904
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]
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],
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"area": 7139.994624000001,
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"iscrowd": 0,
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"image_id": 1,
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"bbox": [
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126.99993599999999,
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3.9999679999999955,
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84.0,
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84.999936
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],
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"category_id": 1,
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"id": 2
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},
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{
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"segmentation": [
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[
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74.99990400000002,
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76.000064,
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150.99996800000002,
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76.000064,
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150.99996800000002,
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153.000064,
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74.99990400000002,
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153.000064
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]
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],
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"area": 5852.004927999999,
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"iscrowd": 0,
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"image_id": 1,
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"bbox": [
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74.99990400000002,
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76.000064,
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76.000064,
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77.0
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],
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"category_id": 1,
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"id": 3
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},
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{
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"segmentation": [
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[
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12.000127999999997,
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135.000096,
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97.00006400000001,
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135.000096,
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97.00006400000001,
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220.00003200000003,
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12.000127999999997,
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220.00003200000003
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]
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],
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"area": 7224.989120004097,
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"iscrowd": 0,
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"image_id": 1,
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"bbox": [
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12.000127999999997,
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135.000096,
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84.999936,
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84.999936
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],
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"category_id": 1,
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"id": 4
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},
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{
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"segmentation": [
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[
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132.00006399999998,
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136.999968,
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215.00012799999996,
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136.999968,
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215.00012799999996,
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220.00003199999998,
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132.00006399999998,
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220.00003199999998
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]
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],
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"area": 6889.010624004095,
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"iscrowd": 0,
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"image_id": 1,
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"bbox": [
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132.00006399999998,
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136.999968,
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83.000064,
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83.000064
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],
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"category_id": 1,
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"id": 5
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},
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{
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"segmentation": [],
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"area": 0,
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"iscrowd": 0,
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"image_id": 2,
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"bbox": [],
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"category_id": -1,
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"id": 6
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}
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],
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"categories": [
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{
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"supercategory": "stamp",
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"id": 1,
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"name": "stamp"
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}
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]
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}

‎labelImg_2_yolov5.py‎

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@@ -10,7 +10,7 @@
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from tqdm import tqdm
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class LabelImgToYOLOV5(object):
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class LabelImgToYOLOV5():
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def __init__(self, root_dir, out_dir, val_ratio, have_test, test_ratio):
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self.root_dir = Path(root_dir)
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self.verify_exists(self.root_dir)

‎yolov5_2_coco.py‎

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@@ -5,15 +5,15 @@
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import argparse
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import json
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import shutil
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from pathlib import Path
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import time
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import warnings
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from pathlib import Path
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import cv2
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from tqdm import tqdm
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class YOLOV5ToCOCO(object):
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class YOLOV5ToCOCO():
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def __init__(self, data_dir):
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self.raw_data_dir = Path(data_dir)
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‎yolov5_yaml_2_coco.py‎

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@@ -29,7 +29,7 @@ def verify_exists(file_path):
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raise FileNotFoundError(f'The {file_path} is not exists!!!')
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class YOLOV5CFG2COCO(object):
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class YOLOV5CFG2COCO():
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def __init__(self, yaml_path):
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verify_exists(yaml_path)
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with open(yaml_path, 'r', encoding="UTF-8") as f:

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