[问答]

求大佬分享RK3399运行瑞芯微官方yolov5 C++代码

2025 深度学习 RK3399

问答对人有帮助，内容完整，我也想知道答案 0 求大佬分享RK3399运行瑞芯微官方yolov5 C++代码 0
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答案对人有帮助，有参考价值 0 运行结果 img width = 1280, img height = 720 Loading mode... D RKNNAPI: ============================================== D RKNNAPI: RKNN VERSION: D RKNNAPI: API: 1.4.0 (bbe0dfc build: 2020-09-14 14:06:05) D RKNNAPI: DRV: 1.6.0 (159d2d3 build: 2021-01-12 15:23:09) D RKNNAPI: ============================================== sdk version: 1.4.0 (bbe0dfc build: 2020-09-14 14:06:05) driver version: 1.6.0 (159d2d3 build: 2021-01-12 15:23:09) model input num: 1, output num: 3 index=0 name=images_165 n_dims=4 dims=[1 3 640 640] n_elems=1228800 size=1228800 fmt=0 type=3 qnt_type=2 fl=0 zp=0 scale=0.003922 index=0 name=Conv_Conv_159/out0_0 n_dims=4 dims=[1 255 80 80] n_elems=1632000 size=1632000 fmt=0 type=3 qnt_type=2 fl=0 zp=187 scale=0.127843 index=1 name=Conv_Conv_160/out0_1 n_dims=4 dims=[1 255 40 40] n_elems=408000 size=408000 fmt=0 type=3 qnt_type=2 fl=0 zp=182 scale=0.113217 index=2 name=Conv_Conv_161/out0_2 n_dims=4 dims=[1 255 20 20] n_elems=102000 size=102000 fmt=0 type=3 qnt_type=2 fl=0 zp=172 scale=0.103272 model is NCHW input fmt model input height=640, width=640, channel=3 Rga built version:1.04 2134dde+2021-05-18 11:00:36 once run use 77.443000 ms loadLabelName /home/toybrick/workspace/rockchip_yolov5/model/coco_80_labels_list.txt result 0: (1128, 74, 1280, 532), horse result 1: ( 668, 41, 892, 525), horse result 2: ( 26, 20, 224, 529), horse result 6: (1126, 38, 1278, 284), person result 10: ( 914, 47, 1112, 532), horse result 13: ( 216, 67, 414, 578), horse result 23: ( 186, 0, 438, 319), person result 37: ( 858, 29, 1080, 300), person @ (1128 74 1280 532) 0.326754 @ (668 41 892 525) 0.373704 @ (26 20 224 529) 0.398172 @ (1126 38 1278 284) 0.398172 @ (914 47 1112 532) 0.349865 @ (216 67 414 578) 0.326754 @ (186 0 438 319) 0.423160 @ (858 29 1080 300) 0.398172 result 0: (1128, 74, 1280, 532), horse result 1: ( 668, 41, 892, 525), horse result 2: ( 26, 20, 224, 529), horse result 6: (1126, 38, 1278, 284), person result 10: ( 914, 47, 1112, 532), horse result 13: ( 216, 67, 414, 578), horse result 23: ( 186, 0, 438, 319), person result 37: ( 858, 29, 1080, 300), person result 0: (1128, 74, 1280, 532), horse result 1: ( 668, 41, 892, 525), horse result 2: ( 26, 20, 224, 529), horse result 6: (1126, 38, 1278, 284), person result 10: ( 914, 47, 1112, 532), horse result 13: ( 216, 67, 414, 578), horse result 23: ( 186, 0, 438, 319), person result 37: ( 858, 29, 1080, 300), person result 0: (1128, 74, 1280, 532), horse result 1: ( 668, 41, 892, 525), horse result 2: ( 26, 20, 224, 529), horse result 6: (1126, 38, 1278, 284), person result 10: ( 914, 47, 1112, 532), horse result 23: ( 186, 0, 438, 319), person result 37: ( 858, 29, 1080, 300), person result 0: (1128, 74, 1280, 532), horse result 1: ( 668, 41, 892, 525), horse result 2: ( 26, 20, 224, 529), horse result 6: (1126, 38, 1278, 284), person result 10: ( 914, 47, 1112, 532), horse result 13: ( 216, 67, 414, 578), horse result 23: ( 186, 0, 438, 319), person result 37: ( 858, 29, 1080, 300), person result 0: (1128, 74, 1280, 532), horse result 1: ( 668, 41, 892, 525), horse result 2: ( 26, 20, 224, 529), horse result 6: (1126, 38, 1278, 284), person result 10: ( 914, 47, 1112, 532), horse result 13: ( 216, 67, 414, 578), horse result 23: ( 186, 0, 438, 319), person result 37: ( 858, 29, 1080, 300), person result 0: (1128, 74, 1280, 532), horse result 1: ( 668, 41, 892, 525), horse result 2: ( 26, 20, 224, 529), horse result 6: (1126, 38, 1278, 284), person result 10: ( 914, 47, 1112, 532), horse result 13: ( 216, 67, 414, 578), horse result 23: ( 186, 0, 438, 319), person result 37: ( 858, 29, 1080, 300), person result 0: (1128, 74, 1280, 532), horse result 1: ( 668, 41, 892, 525), horse result 2: ( 26, 20, 224, 529), horse result 6: (1126, 38, 1278, 284), person result 10: ( 914, 47, 1112, 532), horse result 13: ( 216, 67, 414, 578), horse result 23: ( 186, 0, 438, 319), person result 37: ( 858, 29, 1080, 300), person result 0: (1128, 74, 1280, 532), horse result 1: ( 668, 41, 892, 525), horse result 2: ( 26, 20, 224, 529), horse result 6: (1126, 38, 1278, 284), person result 13: ( 216, 67, 414, 578), horse result 23: ( 186, 0, 438, 319), person result 37: ( 858, 29, 1080, 300), person result 0: (1128, 74, 1280, 532), horse result 1: ( 668, 41, 892, 525), horse result 2: ( 26, 20, 224, 529), horse result 6: (1126, 38, 1278, 284), person result 10: ( 914, 47, 1112, 532), horse result 13: ( 216, 67, 414, 578), horse result 23: ( 186, 0, 438, 319), person result 37: ( 858, 29, 1080, 300), person result 0: (1128, 74, 1280, 532), horse result 1: ( 668, 41, 892, 525), horse result 2: ( 26, 20, 224, 529), horse result 6: (1126, 38, 1278, 284), person result 10: ( 914, 47, 1112, 532), horse result 13: ( 216, 67, 414, 578), horse result 23: ( 186, 0, 438, 319), person result 37: ( 858, 29, 1080, 300), person loop count = 10 , average run 84.673900 ms yolov5 C++代码代码地址 https://github.com/rockchip-linux/rknpu.git /rknn/rknn_api/example/rknn_yolov5_demo rknn 模型使用 rknpu/rknn/rknn_api/examples)/rknn_yolov5_demo/model/rk180x/yolov5s_relu_rk180x_out_opt.rknn 地址yolov5s_relu_rk180x_out_opt.rknn) https://github.com/EASY-EAI/yolov5.git 转换模型代码调整替换rknn初始化rknn_init改为rknn_init2指定npu设备号 rknn_init_extend rknnInitExtend; rknnInitExtend.; ret = rknn_init2(&ctx, model_data, model_data_size, 0,&rknnInitExtend); rknn_api 调整在yolov5 C++demo代码的CMakeFileLists.txt文件中使用系统自带的librknn_api.so文件 link_libraries( /usr/lib/aarch64-linux-gnu/librknn_api.so ...... ) 编译RGA(可选) 本人使用板子rk3399proD没有自带的librga.so文件故需要编译rga 代码地址 https://github.com/rockchip-linux/linux-rga.git 编译调整原因：在瑞芯微yolov5demo代码中通过dlsym使用c_RkRgaInit，c_RkRgaDeInit，c_RkRgaBlit函数，瑞芯微开源的RGA默认编译不含该函数 CMakeFileList.txt文件增加如下信息 set(IM2D_SRCS core/RockchipRga.cpp core/GrallocOps.cpp core/NormalRga.cpp core/RgaApi.cpp --------此处为新增 core/NormalRgaApi.cpp core/RgaUtils.cpp im2d_api/im2d.cpp)

2022-3-7 09:39:35 评论举报谢海莲