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car-detection-bayes
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updates

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Glenn Jocher 2019-04-18 15:01:58 +02:00
parent c5e58b6484
commit b177d01695
1 changed files with 2 additions and 2 deletions
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train.py
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@ -301,14 +301,14 @@ if __name__ == '__main__':
# Mutate hyperparameters # Mutate hyperparameters
old_hyp = hyp.copy() old_hyp = hyp.copy()
init_seeds(seed=int(time.time())) init_seeds(seed=int(time.time()))
s = [.3, .3, .3, .3, .3, .3, .3, .3, .05, .3] s = [.3, .3, .3, .3, .3, .3, .3, .3, .03, .3]
for i, k in enumerate(hyp.keys()): for i, k in enumerate(hyp.keys()):
x = (np.random.randn(1) * s[i] + 1) ** 1.1 # plt.hist(x.ravel(), 100) 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 hyp[k] = hyp[k] * float(x) # vary by about 30% 1sigma
# Apply limits # Apply limits
hyp['iou_t'] = np.clip(hyp['iou_t'], 0, 0.90) hyp['iou_t'] = np.clip(hyp['iou_t'], 0, 0.90)
hyp['momentum'] = np.clip(hyp['momentum'], 0.7, 0.98) hyp['momentum'] = np.clip(hyp['momentum'], 0.8, 0.95)
hyp['weight_decay'] = np.clip(hyp['weight_decay'], 0, 0.01) hyp['weight_decay'] = np.clip(hyp['weight_decay'], 0, 0.01)
# Normalize loss components (sum to 1) # Normalize loss components (sum to 1)