网络结构
import torch
import torch.nn as nn
import numpy as np
num_classes = 80
input_shape = [640, 640, 3]
anchors_mask = [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
anchors = [[10, 13], [16, 30], [33, 23], [30, 61], [62, 45], [59, 119], [116, 90], [156, 198], [373, 326]]
anchors=np.array(anchors)
class SiLU(nn.Module):
@staticmethod
def forward(x):
return x * torch.sigmoid(x)
def autopad(k, p=None):
if p is None:
p = k // 2 if isinstance(k, int) else [x // 2 for x in k]
return p
class Focus(nn.Module):
def __init__(self, c1, c2, k=1, s=1, p=None, g=1, act=True): # ch_in, ch_out, kernel, stride, padding, groups
super(Focus, self).__init__()
self.conv = Conv(c1 * 4, c2, k, s, p, g, act)
def forward(self, x):
return self.conv(torch.cat([x[..., ::2, ::2], x[..., 1::2, ::2], x[..., ::2, 1::2], x[..., 1::2, 1::2]], 1))
class Conv(nn.Modu