YOLOv5s: Target Detection
YOLOv5 is a one-stage structure target detection network framework, in which the main structure consists of 4 parts, including the network backbone composed of modified CSPNet, the high-resolution feature fusion module composed of FPN (Feature Paramid Network), composed of SPP (Spatial Pyramid Pooling) constitutes a pooling module, and three different detection heads are used to detect targets of different sizes.
Source model
- Input shape: 640x640
- Number of parameters: 7.2M
- Model size: 29.0MB
- Output shape: 1x25200x85
Source model repository: yolov5
YOLOv5 is a one-stage structure target detection network framework, in which the main structure consists of 4 parts, including the network backbone composed of modified CSPNet, the high-resolution feature fusion module composed of FPN (Feature Paramid Network), composed of SPP (Spatial Pyramid Pooling) constitutes a pooling module, and three different detection heads are used to detect targets of different sizes.
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