Bienqq
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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-04-18 12:21:39 +02:00
parent 9a440cfa15
commit 8831913f10
1 changed files with 15 additions and 4 deletions
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19
train.py
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@ -301,14 +301,15 @@ if __name__ == '__main__':
# Mutate hyperparameters
old_hyp = hyp.copy()
init_seeds(seed=int(time.time()))
for k in hyp.keys():
x = (np.random.randn(1) * 0.2 + 1) ** 1.1 # plt.hist(x.ravel(), 100)
s = [.3, .3, .3, .3, .3, .3, .3, .3, .05, .3]
for i, k in enumerate(hyp.keys()):
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'] = 0.9 # np.clip(hyp['momentum'], 0, 0.98)
hyp['weight_decay'] = 0.0005 # np.clip(hyp['weight_decay'], 0, 0.01)
hyp['momentum'] = np.clip(hyp['momentum'], 0.7, 0.98)
hyp['weight_decay'] = np.clip(hyp['weight_decay'], 0, 0.01)
# Normalize loss components (sum to 1)
lcf = ['xy', 'wh', 'cls', 'conf']
@ -345,3 +346,13 @@ if __name__ == '__main__':
best_fitness = mutation_fitness
else:
hyp = old_hyp.copy() # reset hyp to
import numpy as np
import matplotlib.pyplot as plt
a = np.loadtxt('evolve.txt')
x = a[:,3]
fig = plt.figure(figsize=(14, 7))
for i in range(1,10):
plt.subplot(2,5,i)
plt.plot(x,a[:,i+5],'.')