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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-04-24 14:09:15 +02:00
parent bd2378fad1
commit 3a375f7132
1 changed files with 8 additions and 7 deletions
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15
train.py
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@ -326,15 +326,16 @@ if __name__ == '__main__':
x = (np.random.randn(1) * s[i] + 1) ** 1.1 # plt.hist(x.ravel(), 100)
hyp[k] = hyp[k] * float(x) # vary by about 30% 1sigma
# Apply limits
hyp['iou_t'] = np.clip(hyp['iou_t'], 0, 0.90)
hyp['momentum'] = np.clip(hyp['momentum'], 0.8, 0.95)
hyp['weight_decay'] = np.clip(hyp['weight_decay'], 0, 0.01)
# Clip to limits
keys = ['iou_t', 'momentum', 'weight_decay']
limits = [(0, 0.90), (0.80, 0.95), (0, 0.01)]
for k, v in zip(keys, limits):
hyp[k] = np.clip(hyp[k], v[0], v[1])
# Normalize loss components (sum to 1)
lcf = ['xy', 'wh', 'cls', 'conf']
s = sum([v for k, v in hyp.items() if k in lcf])
for k in lcf:
keys = ['xy', 'wh', 'cls', 'conf']
s = sum([v for k, v in hyp.items() if k in keys])
for k in keys:
hyp[k] /= s
# Determine mutation fitness