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car-detection-bayes
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k for kernel_size

This commit is contained in:
Glenn Jocher 2020-04-11 12:37:03 -07:00
parent a34219a54b
commit ed1d4f5ae7
1 changed files with 8 additions and 8 deletions
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16
models.py
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@ -21,20 +21,20 @@ def create_modules(module_defs, img_size):
if mdef['type'] == 'convolutional':
bn = mdef['batch_normalize']
filters = mdef['filters']
size = mdef['size']
k = mdef['size'] # kernel size
stride = mdef['stride'] if 'stride' in mdef else (mdef['stride_y'], mdef['stride_x'])
if isinstance(size, int): # single-size conv
if isinstance(k, int): # single-size conv
modules.add_module('Conv2d', nn.Conv2d(in_channels=output_filters[-1],
out_channels=filters,
kernel_size=size,
kernel_size=k,
stride=stride,
padding=size // 2 if mdef['pad'] else 0,
padding=k // 2 if mdef['pad'] else 0,
groups=mdef['groups'] if 'groups' in mdef else 1,
bias=not bn))
else: # multiple-size conv
modules.add_module('MixConv2d', MixConv2d(in_ch=output_filters[-1],
out_ch=filters,
k=size,
k=k,
stride=stride,
bias=not bn))
@ -58,10 +58,10 @@ def create_modules(module_defs, img_size):
modules.running_var = torch.tensor([0.0524, 0.0502, 0.0506])
elif mdef['type'] == 'maxpool':
size = mdef['size']
k = mdef['size'] # kernel size
stride = mdef['stride']
maxpool = nn.MaxPool2d(kernel_size=size, stride=stride, padding=(size - 1) // 2)
if size == 2 and stride == 1: # yolov3-tiny
maxpool = nn.MaxPool2d(kernel_size=k, stride=stride, padding=(k - 1) // 2)
if k == 2 and stride == 1: # yolov3-tiny
modules.add_module('ZeroPad2d', nn.ZeroPad2d((0, 1, 0, 1)))
modules.add_module('MaxPool2d', maxpool)
else: