(self, input_channels=3, out_channels=14)
| 30 | |
| 31 | class BallTrackerNet(nn.Module): |
| 32 | def __init__(self, input_channels=3, out_channels=14): |
| 33 | super().__init__() |
| 34 | self.out_channels = out_channels |
| 35 | self.input_channels = input_channels |
| 36 | |
| 37 | self.conv1 = ConvBlock(in_channels=self.input_channels, out_channels=64) |
| 38 | self.conv2 = ConvBlock(in_channels=64, out_channels=64) |
| 39 | self.pool1 = nn.MaxPool2d(kernel_size=2, stride=2) |
| 40 | self.conv3 = ConvBlock(in_channels=64, out_channels=128) |
| 41 | self.conv4 = ConvBlock(in_channels=128, out_channels=128) |
| 42 | self.pool2 = nn.MaxPool2d(kernel_size=2, stride=2) |
| 43 | self.conv5 = ConvBlock(in_channels=128, out_channels=256) |
| 44 | self.conv6 = ConvBlock(in_channels=256, out_channels=256) |
| 45 | self.conv7 = ConvBlock(in_channels=256, out_channels=256) |
| 46 | self.pool3 = nn.MaxPool2d(kernel_size=2, stride=2) |
| 47 | self.conv8 = ConvBlock(in_channels=256, out_channels=512) |
| 48 | self.conv9 = ConvBlock(in_channels=512, out_channels=512) |
| 49 | self.conv10 = ConvBlock(in_channels=512, out_channels=512) |
| 50 | self.ups1 = nn.Upsample(scale_factor=2) |
| 51 | self.conv11 = ConvBlock(in_channels=512, out_channels=256) |
| 52 | self.conv12 = ConvBlock(in_channels=256, out_channels=256) |
| 53 | self.conv13 = ConvBlock(in_channels=256, out_channels=256) |
| 54 | self.ups2 = nn.Upsample(scale_factor=2) |
| 55 | self.conv14 = ConvBlock(in_channels=256, out_channels=128) |
| 56 | self.conv15 = ConvBlock(in_channels=128, out_channels=128) |
| 57 | self.ups3 = nn.Upsample(scale_factor=2) |
| 58 | self.conv16 = ConvBlock(in_channels=128, out_channels=64) |
| 59 | self.conv17 = ConvBlock(in_channels=64, out_channels=64) |
| 60 | self.conv18 = ConvBlock(in_channels=64, out_channels=self.out_channels) |
| 61 | |
| 62 | self._init_weights() |
| 63 | |
| 64 | def forward(self, x): |
| 65 | x = self.conv1(x) |
nothing calls this directly
no test coverage detected