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标题: RK1808M0 在PC端运行 [打印本页]

作者: anqingcheng 时间: 2020-11-6 18:01
标题: RK1808M0 在PC端运行
import numpy as np
import cv2
import yolov3 as yolov
from rknn.api import RKNN

if __name__ == '__main__':

capture = cv2.VideoCapture(0)  # VideoCapture 读取本地视频和打开摄像头
height = capture.get(cv2.CAP_PROP_FRAME_HEIGHT)  # 计算视频的高
width = capture.get(cv2.CAP_PROP_FRAME_WIDTH)  # 计算视频的宽

print(height)
print(width)

# cv2.VideoWriter 保存摄像头视频          #VideoWriter_fourcc()输入四个字符代码即可得到对应的视频编码器
out = cv2.VideoWriter("D:/demo.mp4", cv2.VideoWriter_fourcc('D', 'I', 'V', 'X'), 15,
                        (np.int(width), np.int(height)), True)
# Create RKNN object
rknn = RKNN()
print('done')
rknn.load_rknn(path='./yolov3_tiny.rknn')
ret = rknn.init_runtime()
if ret != 0:
      print('Init runtime environment failed')
      exit(ret)

while True:
      ret, frame = capture.read()
      if ret is True:
         frame = cv2.flip(frame, 1)  # cv2.flip 图像翻转

         rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)  # cvtColor()颜色空间转换函数

         cv2.imshow("frame", rgb)
         x, y = rgb.shape[0:2]

         cv2.resize(rgb, (416, 416), rgb)
         #cv2.imwrite("aa.jpg",rgb);
         # Inference
         print('--> Running model')
         outputs = rknn.inference(inputs=[rgb])
         data = yolov.post_process(outputs)
         print(data)

         c = cv2.waitKey(10)
         if c == 27:
            break
      else:
         break
cv2.destroyAllWindows()
rknn.release()
# perf
print('--> Begin evaluate model performance')
#perf_results = rknn.eval_perf(inputs=[img])
print('done')

/home/gerrard/PycharmProjects/pythonProject/venv/bin/python /home/gerrard/PycharmProjects/pythonProject/yolov3_test.py
done
--> Running model
W [rknn_inputs_set:2063] warning: inputs[0] expected input len is 519168, but actual len is 921600!
(None, None, None)
W [rknn_inputs_set:2063] warning: inputs[0] expected input len is 519168, but actual len is 921600!
--> Running model
(None, None, None)
W [rknn_inputs_set:2063] warning: inputs[0] expected input len is 519168, but actual len is 921600!
--> Running model
(None, None, None)
W [rknn_inputs_set:2063] warning: inputs[0] expected input len is 519168, but actual len is 921600!
--> Running model

使用的是官方的./yolov3_tiny.rknn模型，但是一直识别失败！

作者: jefferyzhang 时间: 2020-11-7 09:52
失败日志是什么？
计算卡的rknn driver升级到最新的了么？
rknntoolkit和计算卡的drv版本是否匹配

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