使用pytorch写一段fpn网络的代码
时间: 2023-03-15 22:14:14 浏览: 79
以下是使用PyTorch实现一段Faster R-CNN网络的代码示例:import torch
from torch import nnclass FPN(nn.Module):
def __init__(self, num_classes):
super(FPN, self).__init__()
self.num_classes = num_classes
self.backbone = Backbone() # 定义后端特征提取网络 self.fpn_layers = nn.Sequential(
nn.Conv2d(in_channels=256, out_channels=256, kernel_size=3, stride=1, padding=1),
nn.ReLU(inplace=True),
nn.Conv2d(in_channels=256, out_channels=256, kernel_size=3, stride=1, padding=1),
nn.ReLU(inplace=True)
) self.rpn_head = RPNHead() # 定义RPN头 self.roi_head = RoIHead(num_classes) # 定义RoIHead def forward(self, x):
c3, c4, c5 = self.backbone(x) # 使用后端特征提取网络提取特征
p3, p4, p5 = self.fpn_layers(c3), self.fpn_layers(c4), self.fpn_layers(c5) # 使用FPN提取特征
rpn_locs, rpn_scores, rois, roi_indices, anchor = self.rpn_head(p3, p4, p5) # 使用RPN头进行锚框回归和分类
cls_locs, cls_scores = self.roi_head(p3, p4, p5, rois) # 使用RoIHead进行RoI分类
return cls_locs, cls_scores, rpn_locs, rpn_scores, rois, roi_indices, anchor