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46 lines
1.9 KiB
Python
46 lines
1.9 KiB
Python
# Objects365 https://www.objects365.org labels JSON to YOLO script
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# 1. Download Object 365 from the Object 365 website And unpack all images in datasets/object365/images
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# 2. Place this file and zhiyuan_objv2_train.json file in datasets/objects365
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# 3. Execute this file from datasets/object365 path
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# /datasets
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# /objects365
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# /images
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# /labels
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from pycocotools.coco import COCO
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from utils.general import download, Path
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# Make Directories
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dir = Path('../datasets/objects365') # dataset directory
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for p in 'images', 'labels':
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(dir / p).mkdir(parents=True, exist_ok=True)
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for q in 'train', 'val':
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(dir / p / q).mkdir(parents=True, exist_ok=True)
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# Download
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url = "https://dorc.ks3-cn-beijing.ksyun.com/data-set/2020Objects365%E6%95%B0%E6%8D%AE%E9%9B%86/train/"
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download([url + 'zhiyuan_objv2_train.tar.gz'], dir=dir) # annotations json
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download([url + f for f in [f'patch{i}.tar.gz' for i in range(51)]], dir=dir / 'images' / 'train', threads=8)
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# Labels
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coco = COCO(dir / 'zhiyuan_objv2_train.json')
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names = [x["name"] for x in coco.loadCats(coco.getCatIds())]
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for categoryId, cat in enumerate(names):
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catIds = coco.getCatIds(catNms=[cat])
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imgIds = coco.getImgIds(catIds=catIds)
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for im in coco.loadImgs(imgIds):
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width, height = im["width"], im["height"]
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path = Path(im["file_name"]) # image filename
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try:
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with open(dir / 'labels' / 'train' / path.with_suffix('.txt').name, 'a') as file:
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annIds = coco.getAnnIds(imgIds=im["id"], catIds=catIds, iscrowd=None)
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for a in coco.loadAnns(annIds):
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x, y, w, h = a['bbox'] # bounding box in xywh (xy top-left corner)
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x, y = x + w / 2, y + h / 2 # xy to center
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file.write(f"{categoryId} {x / width:.5f} {y / height:.5f} {w / width:.5f} {h / height:.5f}\n")
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except Exception as e:
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print(e)
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