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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-08-22 23:41:51 +02:00
parent 858fc67954
commit 0040c85b9a
1 changed files with 14 additions and 16 deletions
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30
models.py
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@ -77,23 +77,21 @@ def create_modules(module_defs, img_size):
yolo_index=yolo_index) # 0, 1 or 2
# Initialize preceding Conv2d() bias (https://arxiv.org/pdf/1708.02002.pdf section 3.3)
bias = module_list[-1][0].bias.view(len(mask), -1) # 255 to 3x85
if arc == 'normal':
bias[:, 4] -= 5.0 # obj
bias[:, 5:] -= 4.0 # cls
elif arc == 'uCE': # unified CE (1 background + 80 classes)
bias[:, 4] += 3.0 # obj
bias[:, 5:] -= 4.0 # cls
elif arc == 'uBCE': # unified BCE (80 classes)
bias[:, 4] -= 5.0 # obj
bias[:, 5:] -= 4.0 # cls
module_list[-1][0].bias = torch.nn.Parameter(bias.view(-1))
try:
if arc == 'normal':
b = [-5.0, -4.0] # obj, cls
elif arc == 'uCE': # unified CE (1 background + 80 classes)
b = [3.0, -4.0] # obj, cls
elif arc == 'uBCE': # unified BCE (80 classes)
b = [-5.0, -4.0] # obj, cls
# for l in model.yolo_layers: # print pretrained biases
# b = model.module_list[l - 1][0].bias.view(3, -1) # bias 3x85
# print('regression: %.2f+/-%.2f, ' % (b[:, :4].mean(), b[:, :4].std()),
# 'objectness: %.2f+/-%.2f, ' % (b[:, 4].mean(), b[:, 4].std()),
# 'classification: %.2f+/-%.2f' % (b[:, 5:].mean(), b[:, 5:].std()))
bias = module_list[-1][0].bias.view(len(mask), -1) # 255 to 3x85
bias[:, 4] += b[0] # obj
bias[:, 5:] += b[1] # cls
module_list[-1][0].bias = torch.nn.Parameter(bias.view(-1))
# utils.print_model_biases(model)
except:
print('WARNING: smart bias initialization failure.')
else:
print('Warning: Unrecognized Layer Type: ' + mdef['type'])