Update Objects365.yaml to include the official validation set (#5194)
* Update Objects365.yaml Download the official Objects365 validation set and convert the labels * Enforce 4-space indent, reformat and cleanup * shorten list comprehension Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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@@ -62,43 +62,50 @@ names: ['Person', 'Sneakers', 'Chair', 'Other Shoes', 'Hat', 'Car', 'Lamp', 'Gla
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from pycocotools.coco import COCO
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from tqdm import tqdm
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from utils.general import download, Path
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# Make Directories
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dir = Path(yaml['path']) # dataset root dir
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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, delete=False) # 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',
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curl=True, delete=False, threads=8)
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# Move
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train = dir / 'images' / 'train'
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for f in tqdm(train.rglob('*.jpg'), desc=f'Moving images'):
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f.rename(train / f.name) # move to /images/train
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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 cid, 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 tqdm(coco.loadImgs(imgIds), desc=f'Class {cid + 1}/{len(names)} {cat}'):
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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"{cid} {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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# Train, Val Splits
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for split, patches in [('train', 50 + 1), ('val', 43 + 1)]:
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print(f"Processing {split} in {patches} patches ...")
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images, labels = dir / 'images' / split, dir / 'labels' / split
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# Download
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url = f"https://dorc.ks3-cn-beijing.ksyun.com/data-set/2020Objects365%E6%95%B0%E6%8D%AE%E9%9B%86/{split}/"
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if split == 'train':
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download([f'{url}zhiyuan_objv2_{split}.tar.gz'], dir=dir, delete=False) # annotations json
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download([f'{url}patch{i}.tar.gz' for i in range(patches)], dir=images, curl=True, delete=False, threads=8)
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elif split == 'val':
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download([f'{url}zhiyuan_objv2_{split}.json'], dir=dir, delete=False) # annotations json
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download([f'{url}images/v1/patch{i}.tar.gz' for i in range(15 + 1)], dir=images, curl=True, delete=False, threads=8)
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download([f'{url}images/v2/patch{i}.tar.gz' for i in range(16, patches)], dir=images, curl=True, delete=False, threads=8)
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# Move
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for f in tqdm(images.rglob('*.jpg'), desc=f'Moving {split} images'):
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f.rename(images / f.name) # move to /images/{split}
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# Labels
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coco = COCO(dir / f'zhiyuan_objv2_{split}.json')
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names = [x["name"] for x in coco.loadCats(coco.getCatIds())]
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for cid, 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 tqdm(coco.loadImgs(imgIds), desc=f'Class {cid + 1}/{len(names)} {cat}'):
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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(labels / 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"{cid} {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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