mindspore mindyolo目标检测华为昇腾上推理使用

loong_XL2023-11-13 17:36

参考：

https://github.com/mindspore-lab/mindyolo

使用案例：

https://github.com/mindspore-lab/mindyolo/blob/master/GETTING_STARTED.md

安装：

matlab 复制代码

pip install mindyolo

特别注意opencv-python、opencv-python-headless版本问题，不然会遇到ImportError: libGL.so.1: cannot open shared object file: No such file or directory等问题

代码

1）下载项目

matlab 复制代码

git clone https://github.com/mindspore-lab/mindyolo

2)运行测试

模型权重下载：https://github.com/mindspore-lab/mindyolo/blob/master/MODEL_ZOO.md

测试这种命令形式用华为昇腾npu推理速度不算快

matlab 复制代码

cd mindyolo

# Run with Ascend (By default)华为昇腾npu推理
python demo/predict.py --config ./configs/yolov7/yolov7.yaml --weight=/path_to_ckpt/WEIGHT.ckpt --image_path /path_to_image/IMAGE.jpg

# Run with GPU
python demo/predict.py --config ./configs/yolov7/yolov7.yaml --weight=/path_to_ckpt/WEIGHT.ckpt --image_path /path_to_image/IMAGE.jpg --device_target=GPU

## 我这里用的yolov7-tiny测试
python demo/predict.py --config ./configs/yolov7/yolov7-tiny.yaml --weight=../yolov7-tiny_300e_mAP375-d8972c94.ckpt --image_path  ../17people.jpg --device_target=CPU

推理图片结果保存在runs_infer下