799959745 发表于 2022-4-11 10:45
没有试过
那用什么算法能达到视频实时效果，有试过吗？
东逝之水 发表于 2022-4-11 10:49
那用什么算法能达到视频实时效果，有试过吗？
没有试过，需要自行尝试研发
liu12111 发表于 2021-11-16 21:32
板子为core-1126-jd4。镜像为官方2021年4月19号的build镜像搭配debian10的三个文件。
按照上面方法装的环 ...
请问你刷的是这个镜像吗？从官方百度云盘下载后的路径是：AIO-RV1126(1109)-JD4\Debian10\debian10_2021_0429_1902\debian10\
里面就3个文件：
但我看到刷固件工具中需要指定以下这么多个文件，这个怎么选择与上述3个文件对应呢？
liu12111 发表于 2021-11-16 21:32
板子为core-1126-jd4。镜像为官方2021年4月19号的build镜像搭配debian10的三个文件。
按照上面方法装的环 ...
我一样遇到这个问题。原因是跑这个rknn真只能在root用户下跑。所以所有的pip3安装必须先切换到root用户下进行。。。然后就没有问题了。
这家的文档的水平真不敢恭维，惜字如金。他们的目标对象应该只是做底层的资深嵌入式工程师。想拿来玩和只想快速在上面做应用的小白就不要折腾它了。。。
这家的文档的水平真不敢恭维，惜字如金。他们的目标对象应该只是做底层的资深嵌入式工程师。
说的太对了{:4_105:}
--> Load RKNN model
done
--> Init runtime environment
E Catch exception when init runtime!
E Traceback (most recent call last):
File "/usr/local/lib/python3.7/dist-packages/rknnlite/api/rknn_lite.py", line 144, in init_runtime
async_mode=async_mode, rknn2precompile=rknn2precompile)
File "rknnlite/api/rknn_runtime.py", line 292, in rknnlite.api.rknn_runtime.RKNNRuntime.__init__
File "rknnlite/api/rknn_runtime.py", line 491, in rknnlite.api.rknn_runtime.RKNNRuntime._load_library
File "rknnlite/api/rknn_runtime.py", line 486, in rknnlite.api.rknn_runtime.RKNNRuntime._get_rknn_api_lib_path
Exception: Unsupported run platform: Linux armv7l
Init runtime environment failed
我这里提示 不支持 armv7l ，怎么回事？
root@439f7c3e208f:/opt/devel/rknn-toolkit/rknn-toolkit-lite/examples/inference_with_lite# python3 test.py
--> Load RKNN model
done
--> Init runtime environment
librknn_runtime version 1.7.1 (97198ce build: 2021-11-24 09:32:17 base: 1131)
done
--> Running model
resnet18
-----TOP 5-----
: 0.9993900656700134
: 0.0004593880439642817
: 2.9284517950145528e-05
: 2.9284517950145528e-05
: 1.850890475907363e-05
done
终于，在docker下，成功跑通，不过，这个运行速度好像很慢很慢。
1. Dockerfile:
FROM debian:buster
RUN apt update
RUN apt install python3-opencv git python3-pip -y
RUN /usr/bin/python3 -m pip install --upgrade pip
COPY ./rknn_toolkit_lite-1.7.1-cp37-cp37m-linux_armv7l.whl /tmp
RUN pip3 install /tmp/rknn_toolkit_lite-1.7.1-cp37-cp37m-linux_armv7l.whl
RUN rm -rf /tmp/rknn_toolkit_lite-1.7.1-cp37-cp37m-linux_armv7l.whl
RUN apt install libdrm-dev -y
COPY ./lib/* /usr/lib
2. copy rknpu driver files to build directory:
cp rknpu/drivers/linux-armhf-puma/usr/lib .
cp rknn-toolkit/rknn-toolkit-lite/packages/rknn_toolkit_lite-1.7.1-cp37-cp37m-linux_armv7l.whl .
3. docker build and run command:
docker build . -t debian10-python3-opencv:latest
docker run -it --rm --name rv1126 --privileged -v /dev/dri/card0:/dev/dri/card0 -v /opt/devel/:/opt/devel debian10-python3-opencv /bin/bash
这是运行的效果：耗时25秒左右。
real 0m24.747suser 0m24.492s
sys 0m0.705sroot@743eeb4de2f7:/opt/devel/rknn-toolkit/rknn-toolkit-lite/examples/inference_with_lite# time python3 test.py
--> list devices:
*************************
None devices connected.
*************************
done
--> query support target platform
**************************************************
Target platforms filled in RKNN model: ['RV1109']
Target platforms supported by this RKNN model: ['RV1109', 'RK1109', 'RV1126', 'RK1126']
**************************************************
done
--> Load RKNN model
done
--> Init runtime environment
librknn_runtime version 1.7.1 (97198ce build: 2021-11-24 09:32:17 base: 1131)
done
--> get sdk version:
==============================================
RKNN VERSION:
API: librknn_runtime version 1.7.1 (97198ce build: 2021-11-24 09:32:17 base: 1131)
DRV: 6.4.6.5.351518
==============================================
done
--> Running model
resnet18
-----TOP 5-----
: 0.9993900656700134
: 0.0004593880439642817
: 2.9284517950145528e-05
: 2.9284517950145528e-05
: 1.850890475907363e-05
done
同样的环境，跑 C 版本的demo，耗时只需要 0.7秒。差距大了{:5_241:}
root@743eeb4de2f7:/opt/devel/yolov5_detect_demo_release# time ./yolov5_detect_demo
librknn_runtime version 1.7.1 (97198ce build: 2021-11-24 09:32:17 base: 1131)
time_use is 126.657997
car @ (258 909 583 1109) 0.841335
car @ (534 736 739 859) 0.831931
bus@ (930 413 1206 531) 0.818415
car @ (1766 578 1872 657) 0.810571
car @ (721 760 927 921) 0.792803
car @ (563 950 801 1115) 0.770443
car @ (956 809 1138 968) 0.752421
car @ (801 991 1071 1115) 0.719339
person @ (1431 619 1461 686) 0.699269
car @ (0 495 137 598) 0.674166
person @ (1819 651 1863 739) 0.639357
car @ (1208 431 1261 472) 0.632317
car @ (862 402 936 469) 0.618040
car @ (1781 446 1845 504) 0.575020
person @ (1543 677 1590 771) 0.561444
person @ (375 481 399 528) 0.538842
car @ (1684 431 1737 478) 0.505462
motorbike@ (1508 748 1564 836) 0.475376
person @ (1200 589 1232 677) 0.471330
car @ (1839 451 1878 501) 0.438286
traffic light @ (1587 548 1608 607) 0.411564
car @ (715 390 777 425) 0.394160
truck@ (472 451 745 557) 0.392559
car @ (812 416 874 469) 0.387184
car @ (466 425 575 481) 0.358873
car @ (1622 410 1669 454) 0.350634
car @ (1481 331 1578 378) 0.340664
car @ (1191 357 1235 404) 0.321087
real 0m0.690s
user 0m0.454s
sys 0m0.191s