def __init__(self, channel=128):
super(exp_4, self).__init__()
self.channel = channel
self.encoder = encoder()
self.decoder_0 = self._make_layer(Bottleneck,
channel // 4,
3,
stride=1)
self.decoder_1 = self._make_layer(Bottleneck,
channel // 4,
3,
stride=1)
self.decoder_2 = self._make_layer(Bottleneck,
channel // 4,
3,
stride=1)
self.decoder_3 = self._make_layer(Bottleneck,
channel // 4,
3,
stride=1)
self.decoder_4 = self._make_layer(Bottleneck,
channel // 4,
3,
stride=1)
self.decoder_5 = self._make_layer(Bottleneck,
channel // 4,
3,
stride=1)
self.ppm = PPM(channel)
self.output_s = ConcatOutput(channel)
weight_init(self)
def init_weights(self):
logger.info('=> init weights from normal distribution')
for m in self.modules():
if isinstance(m, nn.Conv2d):
nn.init.normal_(m.weight, std=0.001)
elif isinstance(m, BatchNorm2d):
nn.init.constant_(m.weight, 1)
nn.init.constant_(m.bias, 0)
weight_init(self)
'''
def __init__(self, channel=256):
super(baseline, self).__init__()
self.resnet = ResNet50()
self.reduce_s1 = Reduction(256, channel)
self.reduce_s2 = Reduction(512, channel)
self.reduce_s3 = Reduction(1024, channel)
self.reduce_s4 = Reduction(2048, channel)
self.ppm = PPM(channel)
self.output_s = ConcatOutput(channel)
weight_init(self)
def __init__(self, channel=64):
super(exp_res2net, self).__init__()
self.resnet = res2net101_v1b_26w_4s(pretrained=True)
self.reduce_s0 = Reduction(64, channel)
self.reduce_s1 = Reduction(256, channel)
self.reduce_s2 = Reduction(512, channel)
self.reduce_s3 = Reduction(1024, channel)
self.reduce_s4 = Reduction(2048, channel)
self.ppm = PPM(channel)
self.output_s = ConcatOutput(channel)
weight_init(self)
def __init__(self, channel=128):
super(exp_1, self).__init__()
self.encoder = encoder()
self.reduce_s0 = Reduction(128, channel)
self.reduce_s1 = Reduction(256, channel)
self.reduce_s2 = Reduction(512, channel)
self.reduce_s3 = Reduction(1024, channel)
self.reduce_s4 = Reduction(2048, channel)
self.ppm = PPM(channel)
self.output_s = ConcatOutput(channel)
weight_init(self)
def __init__(self, channel=128):
super(exp_8, self).__init__()
self.channel = channel
self.encoder = encoder_w()
self.reduce_s0 = Reduction(64, channel)
self.reduce_s1 = Reduction(128, channel)
self.reduce_s2 = Reduction(256, channel)
self.reduce_s3 = Reduction(512, channel)
self.reduce_s4 = Reduction(1024, channel)
self.reduce_s5 = Reduction(2048, channel)
self.decoder_0 = self._make_layer(Bottle2neck,
channel // 4,
3,
stride=1)
self.decoder_1 = self._make_layer(Bottle2neck,
channel // 4,
3,
stride=1)
self.decoder_2 = self._make_layer(Bottle2neck,
channel // 4,
3,
stride=1)
self.decoder_3 = self._make_layer(Bottle2neck,
channel // 4,
3,
stride=1)
self.decoder_4 = self._make_layer(Bottle2neck,
channel // 4,
3,
stride=1)
self.decoder_5 = self._make_layer(Bottle2neck,
channel // 4,
3,
stride=1)
self.aspp_1 = ASPP(in_channel=2048, depth=2048)
self.aspp_2 = ASPP(in_channel=channel, depth=channel)
self.stage_1 = ConcatFusion(channel)
self.output_s = ConcatOutput(channel)
weight_init(self)
def __init__(self, channel=128):
super(exp_2, self).__init__()
self.channel = channel
self.encoder = encoder()
self.reduce_s0 = Reduction(128, channel)
self.reduce_s1 = Reduction(256, channel)
self.reduce_s2 = Reduction(512, channel)
self.reduce_s3 = Reduction(1024, channel)
self.reduce_s4 = Reduction(2048, channel)
self.decoder_0 = self._make_layer(Bottleneck, channel // 4, 3, stride=1)
self.decoder_1 = self._make_layer(Bottleneck, channel // 4, 3, stride=1)
self.decoder_2 = self._make_layer(Bottleneck, channel // 4, 3, stride=1)
self.decoder_3 = self._make_layer(Bottleneck, channel // 4, 3, stride=1)
self.decoder_4 = self._make_layer(Bottleneck, channel // 4, 3, stride=1)
self.ppm = PPM(channel)
self.output_s = ConcatOutput(channel)
weight_init(self)
def __init__(self, channel=256):
super(hrnet_v3, self).__init__()
self.hrnet = get_seg_model()
weight_init(self)
def __init__(self, channel=128):
super(exp_29, self).__init__()
self.channel = channel
self.encoder = encoder_w()
self.reduce_s0 = Reduction(64, channel)
self.reduce_s1 = Reduction(128, channel)
self.reduce_s2 = Reduction(256, channel)
self.reduce_s3 = Reduction(512, channel)
self.reduce_s4 = Reduction(1024, channel)
self.reduce_s5 = Reduction(2048, channel)
self.decoder_0 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_1 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_2 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_3 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_4 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_5 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_6 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_7 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_8 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_9 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_10 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_11 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_12 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_13 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_14 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_15 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_16 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.decoder_17 = self._make_layer(Bottle2neck, channel // 4, 3, stride=1)
self.aspp_1 = ASPP(in_channel=channel, depth=channel)
self.aspp_2 = ASPP(in_channel=channel, depth=channel)
self.aspp_3 = ASPP(in_channel=channel, depth=channel)
self.stage_1 = ConcatFusion(channel)
self.stage_2 = ConcatFusion(channel)
self.output_s = ConcatOutput(channel)
self.decoder_0_0 = Decoder(channel + channel, channel, channel)
self.decoder_1_0 = Decoder(channel + channel, channel, channel)
self.decoder_2_0 = Decoder(channel + channel, channel, channel)
self.decoder_3_0 = Decoder(channel + channel, channel, channel)
self.decoder_4_0 = Decoder(channel + channel, channel, channel)
self.decoder_5_0 = Decoder(channel + channel, channel, channel)
self.decoder_0_1 = Decoder(channel * 2, channel, channel)
self.decoder_1_1 = Decoder(channel * 2, channel, channel)
self.decoder_2_1 = Decoder(channel * 2, channel, channel)
self.decoder_3_1 = Decoder(channel * 2, channel, channel)
self.decoder_4_1 = Decoder(channel * 2, channel, channel)
self.decoder_5_1 = Decoder(channel * 2, channel, channel)
self.decoder_0_2 = Decoder(channel * 2, channel, channel)
self.decoder_1_2 = Decoder(channel * 2, channel, channel)
self.decoder_2_2 = Decoder(channel * 2, channel, channel)
self.decoder_3_2 = Decoder(channel * 2, channel, channel)
self.decoder_4_2 = Decoder(channel * 2, channel, channel)
self.decoder_5_2 = Decoder(channel * 2, channel, channel)
self.logit = nn.Sequential(
nn.Conv2d(channel, channel, kernel_size=3, padding=1),
nn.ELU(inplace=True),
nn.Conv2d(channel, 1, kernel_size=1, padding=0),
)
self.maxpool = nn.MaxPool2d(kernel_size=2, stride=2)
weight_init(self)
