基于瑞芯微RK3588 NPU的NanoTrack跟踪算法,可运行于RK3588开发板,可达120FPS.
numpy
opencv
rknn_toolkit_lite2 == 1.3
RKNN3588对应的rknn_toolkit_lite2官方开发库以及开发文档请参考rknn-toolkit2
模型转换需先使用rknn-toolkit2转为.rknn格式
python3 main.py
- video_name 为目标视频地址
- init_rect 为初始检测bbox
python版本基于rk3588的NanoTrack,每秒可达120FPS
基于瑞芯微RK3588 NPU的NanoTrack跟踪算法,可运行于RK3588开发板,可达120FPS.
numpy
opencv
rknn_toolkit_lite2 == 1.3
RKNN3588对应的rknn_toolkit_lite2官方开发库以及开发文档请参考rknn-toolkit2
模型转换需先使用rknn-toolkit2转为.rknn格式
python3 main.py
您好,我试用了您的模型,发现效果很不错,比NanoTrack官方提供的模型帧率有明显提升,想问一下您是自己又经过了剪枝等工作吗?
大佬你好,我看你是在rk3588上运行的nonatrack rknn模型,跟踪效果怎么样呢,fps是120吗,我只在pc上测试过nanotrack,能力有限不能转化为rknn,能否分享下你的转换方法呢
我在RK3588上测试跟踪视频,在生成坐标的函数中用到了cfg.Point_Stride参数,作者设置为8,我修改为了16,为什么映射回的坐标没有发生变化?
请问一下转模型用的是rknn-toolkit2的哪个版本啊?
您好,像问一下模型输入尺寸是否必须固定为127,255?我尝试设置其他尺寸转为rknn模型,板上推理不报错但是得分很低,这是什么原因?感谢您的回答!
Hello, I want to run this implementation using the RKNPU2 C++ APIs, but I encountered a problem. When I examine the models one by one in Netron App, I see that the inputs of the models are in NCHW format. However, when I load the model using the RKNPU2 C++ APIs, I see that the inputs are in NHWC format. Therefore, I believe that the implementation is not working correctly. How can I resolve this issue? Can you assist me?
您好,请问转rknn时,mean_values,std_values都是多少,量化提供了多少张图片呢,head模型量化的数据是否来自前两个backbone模型的输出
您好,在3588上尝试了你的代码,效果挺不错的。目前打算针对特定的场景重新训练模型,请教下应该怎么操作呢?能提供相关代码吗,谢谢。
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