画一张yolov5的模型结构图的python代码

要画出Yolov5的模型结构图，需要使用Graphviz库。以下是一个简单的Python代码示例，可以绘制出Yolov5的模型结构图：

import graphviz

dot = graphviz.Digraph(comment='Yolov5 Model')

# input layer
dot.node('input', 'Input Shape: (608, 608, 3)')

# backbone
with dot.subgraph(name='cluster_backbone') as backbone:
    backbone.attr(style='filled', color='lightgrey')
    backbone.node('backbone_input', 'Input Shape: (608, 608, 3)')
    backbone.node('CSP1', 'CSP Block')
    backbone.node('CSP2', 'CSP Block')
    backbone.node('CSP3', 'CSP Block')
    backbone.node('CSP4', 'CSP Block')
    backbone.node('CSP5', 'CSP Block')
    backbone.node('CSP6', 'CSP Block')
    backbone.node('FPN1', 'FPN Block')
    backbone.node('FPN2', 'FPN Block')
    backbone.node('FPN3', 'FPN Block')
    backbone.edge('backbone_input', 'CSP1')
    backbone.edge('CSP1', 'CSP2')
    backbone.edge('CSP2', 'CSP3')
    backbone.edge('CSP3', 'CSP4')
    backbone.edge('CSP4', 'CSP5')
    backbone.edge('CSP5', 'CSP6')
    backbone.edge('CSP6', 'FPN1')
    backbone.edge('CSP6', 'FPN2')
    backbone.edge('CSP6', 'FPN3')

# neck
with dot.subgraph(name='cluster_neck') as neck:
    neck.attr(style='filled', color='lightgrey')
    neck.node('neck_input', 'Input Shape: (None, None, 256)')
    neck.node('SPP', 'SPP Block')
    neck.node('Conv1', 'Convolutional Layer')
    neck.node('Conv2', 'Convolutional Layer')
    neck.edge('neck_input', 'SPP')
    neck.edge('SPP', 'Conv1')
    neck.edge('Conv1', 'Conv2')

# head
with dot.subgraph(name='cluster_head') as head:
    head.attr(style='filled', color='lightgrey')
    head.node('head_input', 'Input Shape: (None, None, 512)')
    head.node('Conv3', 'Convolutional Layer')
    head.node('Upsample', 'Upsample Layer')
    head.node('Concat', 'Concatenate Layer')
    head.node('Conv4', 'Convolutional Layer')
    head.node('Detection', 'Detection Layer')
    head.edge('head_input', 'Conv3')
    head.edge('Conv3', 'Upsample')
    head.edge('Upsample', 'Concat')
    head.edge('FPN1', 'Concat')
    head.edge('Conv2', 'Conv4')
    head.edge('Conv4', 'Concat')
    head.edge('Concat', 'Detection')

# output layer
dot.node('output', 'Output Shape: (None, None, 85)')

# connect layers
dot.edge('input', 'CSP1')
dot.edge('FPN3', 'neck_input')
dot.edge('Conv2', 'head_input')
dot.edge('Detection', 'output')

# render the graph
dot.render('yolov5_model', view=True)

这段代码使用了Graphviz库中的digraph类来创建一个新的图形，然后使用节点和边表示模型结构中的层次关系。最后，使用render方法将图形保存为一个PDF文件，并打开它以查看模型结构。