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模型导出环境

rknn-toolkit 1.7.1

部署环境

设备测试环境：RV1126
交叉编译环境：Ubuntu18.04

当一个yolov5_6.2模型训练完成后

模型导出

1 pt模型 转 onnx

进入rockchip_rknn_yolov5\yolov5_6.2_export目录
执行

python export.py --weights yolov5s_v6.2.pt --img 640 --batch 1 --include onnx torchscript

yolov5s_v6.2.pt 是自己训练的模型
会生成onnx模型

2 onnx模型 转 rknn

进入rockchip_rknn_yolov5\yolov5_6.2_export目录
执行

python yolov562_to_rknn_3_4.py

C++ 部署

YOLOv562Detector.cpp
YOLOv562Detector.h
test_image.cc

文件所在路径rockchip_rknn_yolov5\C++\yolov5_62

使用方法

test_image "/userdata/yolov5s_v6.2_output3_4.rknn"  80  640

1 模型路径 /userdata/yolov5s_v6.2_output3_4.rknn
2 模型推理类别个数 80
3 模型输入大小 640

rockchip_rknn_yolov5's People

Contributors

boboding avatar shaoshengsong avatar

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