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car-detection-bayes
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mAP recorded during training

This commit is contained in:
Glenn Jocher 2018-11-15 00:56:03 +01:00
parent 45c5567723
commit a17280ac72
1 changed files with 4 additions and 4 deletions
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8
test.py
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@ -119,10 +119,10 @@ def main(opt):
# Append image mAP to list # Append image mAP to list
mAPs.append(mAP) mAPs.append(mAP)
mean_mAP = np.mean(mAPs)
# Print image mAP and running mean mAP # Print image mAP and running mean mAP
print( print('Image %d/%d AP: %.4f (%.4f)' % (len(mAPs), len(dataloader) * opt.batch_size, mAP, mean_mAP))
'+ Sample [%d/%d] AP: %.4f (%.4f)' % (len(mAPs), len(dataloader) * opt.batch_size, mAP, np.mean(mAPs)))
# Print mAP per class # Print mAP per class
classes = load_classes(opt.class_path) # Extracts class labels from file classes = load_classes(opt.class_path) # Extracts class labels from file
@ -130,8 +130,8 @@ def main(opt):
print('%15s: %-.4f' % (c, AP_accum[i] / AP_accum_count[i])) print('%15s: %-.4f' % (c, AP_accum[i] / AP_accum_count[i]))
# Print mAP # Print mAP
print('Mean Average Precision: %.4f' % np.mean(mAPs)) print('Mean Average Precision: %.4f' % mean_mAP)
return mAP return mean_mAP
if __name__ == '__main__': if __name__ == '__main__':