updates
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@ -657,7 +657,7 @@ def kmeans_targets(path='../coco/trainvalno5k.txt', n=9, img_size=416): # from
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from scipy import cluster
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# Get label wh
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dataset = LoadImagesAndLabels(path, augment=True, rect=True)
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dataset = LoadImagesAndLabels(path, augment=True, rect=True, cache_labels=True)
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for s, l in zip(dataset.shapes, dataset.labels):
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l[:, [1, 3]] *= s[0] # normalized to pixels
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l[:, [2, 4]] *= s[1]
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@ -671,8 +671,7 @@ def kmeans_targets(path='../coco/trainvalno5k.txt', n=9, img_size=416): # from
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# Measure IoUs
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iou = torch.stack([wh_iou(torch.Tensor(wh).T, torch.Tensor(x).T) for x in k], 0)
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biou = iou.max(0)[0] # closest anchor IoU
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print((biou < 0.2635).float().mean())
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print('Best possible recall: %.3f' % (biou > 0.2635).float().mean()) # BPR (best possible recall)
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# Print
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print('kmeans anchors (n=%g, img_size=%g, IoU=%.2f/%.2f/%.2f-min/mean/best): ' %
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