rk1126 模型加载rknn_init fail! ret=-6

[复制链接] · 发表于 2021-1-11 19:19:29

Check model fail
rknn_init fail! ret=-6
int main(int argc, char **argv) {
rknn_context ctx;
      int ret;
      int model_len = 0;
      unsigned char *model;
      const char *model_path = argv[1];int xx=argc;
      if(xx<0)
            printf("xxxxxxxxxxxxxxxxxxxxerrrrrrrrrrrr\n");
      printf("xxxxxxxxxxxxxx  Loading model ...\n");
      model = load_model(model_path, &model_len);
      ret = rknn_init(&ctx, model, model_len, 0);
      if (ret < 0) {
            printf("rknn_init fail! ret=%d\n", ret);
            return -1;}rknn_sdk_version version;ret = rknn_query(ctx, RKNN_QUERY_SDK_VERSION, &version,
                     sizeof(rknn_sdk_version));
      printf("api version : %s\n", version.api_version);
      printf("driver version: %s\n", version.drv_version);
}RKNN Toolkit: rknn_toolkit-1.4.0-cp36-cp36m-linux_x86_64.whl
RKNN Toolkit: （rknn_toolkit-1.6.0-cp36-cp36m-win_amd64.whl 下午升级1.6.0也是一样的问题）
[root@RV1126_RV1109:~]# strings /usr/lib/librknn_runtime.so | grep build
vsi_nn_kernel_add_build_option
librknn_runtime version 1.5.1 (161f53f build: 2020-11-05 15:12:30 base: 1126)
rw-r--r- 1 root root 3126876 Dec 30 11:45 /usr/lib/librknn_runtime.so
api version : librknn_runtime version 1.5.1 (161f53f build: 2020-11-05 15:12:30 base: 1126)
driver version: 10126pc 默认模型 yolov3-tiny转码：
if name == '__main__':
MODEL_PATH = './yolov3tinyp.cfg'
WEIGHT_PATH = './yolov3tinyp.weights'
RKNN_MODEL_PATH = './yolov3tinyp.rknn'
im_file = './dog_bike_car_416x416.jpg'
DATASET = './dataset.txt'

download_yolov3_weight(WEIGHT_PATH)

Create RKNN object
rknn = RKNN

NEED_BUILD_MODEL = Trueif NEED_BUILD_MODEL: # Load caffe model
      print('--> Loading model')
      ret = rknn.load_darknet(model=MODEL_PATH, weight=WEIGHT_PATH)
      if ret != 0:
         print('load caffe model failed!')
         exit(ret)
      print('done')rknn.config(reorder_channel='0 1 2', mean_values=[[0, 0, 0]], std_values=[[255, 255, 255]],target_platform=['rk1109','rk1126'])

Build model
print('--> Building model')
ret = rknn.build(do_quantization=True, dataset='./dataset.txt')
if ret != 0:
print('build model failed.')
exit(ret)
print('done')

Export rknn model
print('--> Export RKNN model')
ret = rknn.export_rknn(RKNN_MODEL_PATH)
if ret != 0:
print('Export rknn model failed.')
exit(ret)
print('done')
else:
Direct load rknn model
print('Loading RKNN model')
ret = rknn.load_rknn(RKNN_MODEL_PATH)
if ret != 0:
print('load rknn model failed.')
exit(ret)
print('done')

print('--> init runtime')

ret = rknn.init_runtime()
ret = rknn.init_runtime()
if ret != 0:
print('init runtime failed.')
exit(ret)
print('done')

img = cv2.imread(im_file)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

inference
print('--> inference')
outputs = rknn.inference(inputs=[img])
print('done')

input0_data = outputs[0]
input1_data = outputs[1]
input2_data = outputs[2]input0_data = input0_data.reshape(SPAN, LISTSIZE, GRID0, GRID0)
input1_data = input1_data.reshape(SPAN, LISTSIZE, GRID1, GRID1)
input2_data = input2_data.reshape(SPAN, LISTSIZE, GRID2, GRID2)input_data = []
input_data.append(np.transpose(input0_data, (2, 3, 0, 1)))
input_data.append(np.transpose(input1_data, (2, 3, 0, 1)))
input_data.append(np.transpose(input2_data, (2, 3, 0, 1)))boxes, classes, scores = yolov3_post_process(input_data)image = cv2.imread(im_file)
if boxes is not None:
draw(image, boxes, scores, classes)cv2.imshow("results", image)
cv2.waitKeyEx(0)rknn.release()

只看该作者 · 发表于 2021-1-11 19:21:59

D [compute_node:349]Instance node[26] "CONV2D" ...
D [compute_node:349]Instance node[27] "RESIZE" ...
D [compute_node:349]Instance node[28] "CONCAT" ...
D [compute_node:349]Instance node[29] "CONV2D" ...
D [compute_node:349]Instance node[30] "LEAKY_RELU" ...
D [compute_node:349]Instance node[31] "CONV2D" ...
Check model fail
rknn_init fail! ret=-6

rk1126 模型加载rknn_init fail! ret=-6

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