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1、步骤:rknn将tensorflow的pb模型转换为*.rknn模型
2、步骤:加载到python接口运行模型可以正常运行:
-->loading model
loading model done
--> Init runtime environment
D RKNNAPI: ==============================================
D RKNNAPI: RKNN VERSION:
D RKNNAPI: API: 1.2.0 (1190a71 build: 2019-09-25 12:39:26)
D RKNNAPI: DRV: 1.3.0 (c4f8c23 build: 2019-11-25 10:39:29)
D RKNNAPI: ==============================================
done
(1, 19200) (1, 76800) (1, 307200)
rknn use time {} and fps: {} 13.186838022000302 7.583319051402974
(1, 19200) (1, 76800) (1, 307200)
rknn use time {} and fps: {} 13.250182258001587 7.547065999006278
(1, 19200) (1, 76800) (1, 307200)
rknn use time {} and fps: {} 13.264743579999049 7.538781235905894
3.同一个模型加载到C接口报错如下:
This system has 6 processor(s).
Bind NPU process(0) to CPU 4
Bind Display process to CPU 3
Bind VideoCapture process to CPU 2
D RKNNAPI: ==============================================
D RKNNAPI: RKNN VERSION:
D RKNNAPI: API: 1.3.3 (f20f0bd build: 2020-05-14 14:14:51)
D RKNNAPI: DRV: 1.3.0 (c4f8c23 build: 2019-11-25 10:39:29)
D RKNNAPI: ==============================================
The initialization of NPU Process 0 has been completed.
read camera / video start
frame cnt 40 idxinputImage 1
frame cnt 40 idxinputImage 2
frame cnt 40 idxinputImage 3
frame cnt 40 idxinputImage 4
frame cnt 40 idxinputImage 5
frame cnt 40 idxinputImage 6
frame cnt 40 idxinputImage 7
frame cnt 40 idxinputImage 8
frame cnt 40 idxinputImage 9
frame cnt 40 idxinputImage 10
frame cnt 40 idxinputImage 11
rknn use time: 0.157895
[32857.995978] Core dump to |/usr/lib/systemd/systemd-coredump 27067 1000 1000 11 1600164092 18446744073709551615 debian10.toybrick yolov3-512 pipe failed
Segmentation fault
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