in src/controlnet_aux/open_pose/face.py [0:0]
def __init__(self):
super(FaceNet, self).__init__()
# cnn to make feature map
self.relu = ReLU()
self.max_pooling_2d = MaxPool2d(kernel_size=2, stride=2)
self.conv1_1 = Conv2d(in_channels=3, out_channels=64,
kernel_size=3, stride=1, padding=1)
self.conv1_2 = Conv2d(
in_channels=64, out_channels=64, kernel_size=3, stride=1,
padding=1)
self.conv2_1 = Conv2d(
in_channels=64, out_channels=128, kernel_size=3, stride=1,
padding=1)
self.conv2_2 = Conv2d(
in_channels=128, out_channels=128, kernel_size=3, stride=1,
padding=1)
self.conv3_1 = Conv2d(
in_channels=128, out_channels=256, kernel_size=3, stride=1,
padding=1)
self.conv3_2 = Conv2d(
in_channels=256, out_channels=256, kernel_size=3, stride=1,
padding=1)
self.conv3_3 = Conv2d(
in_channels=256, out_channels=256, kernel_size=3, stride=1,
padding=1)
self.conv3_4 = Conv2d(
in_channels=256, out_channels=256, kernel_size=3, stride=1,
padding=1)
self.conv4_1 = Conv2d(
in_channels=256, out_channels=512, kernel_size=3, stride=1,
padding=1)
self.conv4_2 = Conv2d(
in_channels=512, out_channels=512, kernel_size=3, stride=1,
padding=1)
self.conv4_3 = Conv2d(
in_channels=512, out_channels=512, kernel_size=3, stride=1,
padding=1)
self.conv4_4 = Conv2d(
in_channels=512, out_channels=512, kernel_size=3, stride=1,
padding=1)
self.conv5_1 = Conv2d(
in_channels=512, out_channels=512, kernel_size=3, stride=1,
padding=1)
self.conv5_2 = Conv2d(
in_channels=512, out_channels=512, kernel_size=3, stride=1,
padding=1)
self.conv5_3_CPM = Conv2d(
in_channels=512, out_channels=128, kernel_size=3, stride=1,
padding=1)
# stage1
self.conv6_1_CPM = Conv2d(
in_channels=128, out_channels=512, kernel_size=1, stride=1,
padding=0)
self.conv6_2_CPM = Conv2d(
in_channels=512, out_channels=71, kernel_size=1, stride=1,
padding=0)
# stage2
self.Mconv1_stage2 = Conv2d(
in_channels=199, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv2_stage2 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv3_stage2 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv4_stage2 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv5_stage2 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv6_stage2 = Conv2d(
in_channels=128, out_channels=128, kernel_size=1, stride=1,
padding=0)
self.Mconv7_stage2 = Conv2d(
in_channels=128, out_channels=71, kernel_size=1, stride=1,
padding=0)
# stage3
self.Mconv1_stage3 = Conv2d(
in_channels=199, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv2_stage3 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv3_stage3 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv4_stage3 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv5_stage3 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv6_stage3 = Conv2d(
in_channels=128, out_channels=128, kernel_size=1, stride=1,
padding=0)
self.Mconv7_stage3 = Conv2d(
in_channels=128, out_channels=71, kernel_size=1, stride=1,
padding=0)
# stage4
self.Mconv1_stage4 = Conv2d(
in_channels=199, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv2_stage4 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv3_stage4 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv4_stage4 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv5_stage4 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv6_stage4 = Conv2d(
in_channels=128, out_channels=128, kernel_size=1, stride=1,
padding=0)
self.Mconv7_stage4 = Conv2d(
in_channels=128, out_channels=71, kernel_size=1, stride=1,
padding=0)
# stage5
self.Mconv1_stage5 = Conv2d(
in_channels=199, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv2_stage5 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv3_stage5 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv4_stage5 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv5_stage5 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv6_stage5 = Conv2d(
in_channels=128, out_channels=128, kernel_size=1, stride=1,
padding=0)
self.Mconv7_stage5 = Conv2d(
in_channels=128, out_channels=71, kernel_size=1, stride=1,
padding=0)
# stage6
self.Mconv1_stage6 = Conv2d(
in_channels=199, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv2_stage6 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv3_stage6 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv4_stage6 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv5_stage6 = Conv2d(
in_channels=128, out_channels=128, kernel_size=7, stride=1,
padding=3)
self.Mconv6_stage6 = Conv2d(
in_channels=128, out_channels=128, kernel_size=1, stride=1,
padding=0)
self.Mconv7_stage6 = Conv2d(
in_channels=128, out_channels=71, kernel_size=1, stride=1,
padding=0)
for m in self.modules():
if isinstance(m, Conv2d):
init.constant_(m.bias, 0)