class TinyYolo(nn.Module):
def __init__(self):
super(TinyYolo, self).__init__()
num_class = 20
self.network = nn.Sequential(
nn.Conv2d(in_channels=3, out_channels=16, kernel_size=3, stride=1, padding=1),
nn.BatchNorm2d(16),
nn.LeakyReLU(0.1, inplace=True),
nn.MaxPool2d(kernel_size=2, stride=2),
nn.Conv2d(in_channels=16, out_channels=32, kernel_size=3, stride=1, padding=1),
nn.BatchNorm2d(32),
nn.LeakyReLU(0.1, inplace=True),
nn.MaxPool2d(kernel_size=2, stride=2),
nn.Conv2d(in_channels=32, out_channels=64, kernel_size=3, stride=1, padding=1),
nn.BatchNorm2d(64),
nn.LeakyReLU(0.1, inplace=True),
nn.MaxPool2d(kernel_size=2, stride=2),
nn.Conv2d(in_channels=64, out_channels=128, kernel_size=3, stride=1, padding=1),
nn.BatchNorm2d(128),
nn.LeakyReLU(0.1, inplace=True),
nn.MaxPool2d(kernel_size=2, stride=2),
nn.Conv2d(in_channels=128, out_channels=256, kernel_size=3, stride=1, padding=1),
nn.BatchNorm2d(256),
nn.LeakyReLU(0.1, inplace=True),
nn.MaxPool2d(kernel_size=2, stride=2),
nn.Conv2d(in_channels=256, out_channels=512, kernel_size=3, stride=1, padding=1),
nn.BatchNorm2d(512),
nn.LeakyReLU(0.1, inplace=True),
nn.MaxPool2d(kernel_size=2, stride=2),
nn.Conv2d(in_channels=512, out_channels=1024, kernel_size=3, stride=1, padding=1),
nn.BatchNorm2d(1024),
nn.LeakyReLU(0.1, inplace=True),
nn.Conv2d(in_channels=1024, out_channels=256, kernel_size=3, stride=1, padding=1),
nn.BatchNorm2d(256),
nn.LeakyReLU(0.1, inplace=True),
)
self.fc = nn.Linear(in_features=2304, out_features=7*7*30)
def forward(self, x):
x = self.network(x)
x = x.view(x.size(0), -1)
x = self.fc(x)
return x
I implement tiny-yolo (version 1), but I`m not sure this is correct.
Anyone can check this network ?