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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-07-14 21:38:55 +02:00
parent ac39ff5aa2
commit 9c776b8052
1 changed files with 4 additions and 0 deletions
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train.py
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@ -13,6 +13,9 @@ from utils.utils import *
# 0.109 0.297 0.15 0.126 7.04 1.666 4.062 0.1845 42.6 3.34 12.61 8.338 0.2705 0.001 -4 0.9 0.0005 320 giou + best_anchor False # 0.109 0.297 0.15 0.126 7.04 1.666 4.062 0.1845 42.6 3.34 12.61 8.338 0.2705 0.001 -4 0.9 0.0005 320 giou + best_anchor False
# 0.223 0.218 0.138 0.189 9.28 1.153 4.376 0.08263 24.28 3.05 20.93 2.842 0.2759 0.001357 -5.036 0.9158 0.0005722 mAP/F1 - 50/50 weighting # 0.223 0.218 0.138 0.189 9.28 1.153 4.376 0.08263 24.28 3.05 20.93 2.842 0.2759 0.001357 -5.036 0.9158 0.0005722 mAP/F1 - 50/50 weighting
# 0.231 0.215 0.135 0.191 9.51 1.432 3.007 0.06082 24.87 3.477 24.13 2.802 0.3436 0.001127 -5.036 0.9232 0.0005874
# 0.246 0.194 0.128 0.192 8.12 1.101 3.954 0.0817 22.83 3.967 19.83 1.779 0.3352 0.000895 -5.036 0.9238 0.0007973
hyp = {'giou': 1.153, # giou loss gain hyp = {'giou': 1.153, # giou loss gain
'xy': 4.062, # xy loss gain 'xy': 4.062, # xy loss gain
'wh': 0.1845, # wh loss gain 'wh': 0.1845, # wh loss gain
@ -161,6 +164,7 @@ def train(
results = (0, 0, 0, 0, 0) # P, R, mAP, F1, test_loss results = (0, 0, 0, 0, 0) # P, R, mAP, F1, test_loss
n_burnin = min(round(nb / 5 + 1), 1000) # burn-in batches n_burnin = min(round(nb / 5 + 1), 1000) # burn-in batches
t, t0 = time.time(), time.time() t, t0 = time.time(), time.time()
torch.cuda.empty_cache()
for epoch in range(start_epoch, epochs): for epoch in range(start_epoch, epochs):
model.train() model.train()
print(('\n%8s%12s' + '%10s' * 7) % print(('\n%8s%12s' + '%10s' * 7) %