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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-12-30 13:28:32 -08:00
parent 121526aa98
commit ad20ccce65
1 changed files with 6 additions and 6 deletions
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12
utils/utils.py
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@ -740,14 +740,14 @@ def kmeans_targets(path='data/coco64.txt', n=9, img_size=416): # from utils.uti
from scipy import cluster
# Get label wh
wh = []
dataset = LoadImagesAndLabels(path, augment=True, rect=True, cache_labels=True)
for s, l in zip(dataset.shapes, dataset.labels):
l[:, [1, 3]] *= s[0] # normalized to pixels
l[:, [2, 4]] *= s[1]
l[:, 1:] *= img_size / max(s)
l = l[:, 3:5] * (s / max(s)) # image normalized to letterbox normalized wh
l = l.repeat(10, axis=0) # augment 10x
l *= np.random.uniform(288, 640, size=(l.shape[0], 1)) / img_size # multi-scale box
wh = np.concatenate(dataset.labels, 0)[:, 3:5] # wh from cxywh
l *= np.random.uniform(img_size[0], img_size[1], size=(l.shape[0], 1)) # normalized to pixels (multi-scale)
wh.append(l)
wh = np.concatenate(wh, 0) # wh from cxywh
# Kmeans calculation
k, dist = cluster.vq.kmeans(wh, n) # points, mean distance
@ -767,7 +767,7 @@ def kmeans_targets(path='data/coco64.txt', n=9, img_size=416): # from utils.uti
print('Best Possible Recall (BPR): %.3f' % (biou > 0.225).float().mean()) # BPR (best possible recall)
# Print
print('kmeans anchors (n=%g, img_size=%g, IoU=%.2f/%.2f/%.2f-min/mean/best): ' %
print('kmeans anchors (n=%g, img_size=%s, IoU=%.2f/%.2f/%.2f-min/mean/best): ' %
(n, img_size, biou.min(), iou.mean(), biou.mean()), end='')
for i, x in enumerate(k):
print('%i,%i' % (round(x[0]), round(x[1])), end=', ' if i < len(k) - 1 else '\n') # use in *.cfg