rknn_inputs_set(ctx, io_num.n_input, inputs);if(ret < 0){qDebug("rknn_input_set fail!
inputs[i].fmt = RKNN_TENSOR_NHWC; inputs[i].buf = img.data; } ret = rknn_inputs_set(lands_ctx, io_num.n_input, inputs); // 运行rknn模型 ret = rknn_run(lands_ctx, NULL); if(ret != RKNN_SUCC){ LOGE("rknn_run fail! ret=%d\n", ret); } // 获取rknn结果...
ret =rknn_inputs_set(ctx, io_num.n_input, inputs);if(ret <0) {printf("rknn_input_set fail! ret=%d\n", ret);returnNULL; }// Runprintf("rknn_run\n"); ret =rknn_run(ctx,NULL);if(ret <0) {printf("rknn_run fail! ret=%d\n", ret);returnNULL; }// Get Outputrknn_output...
fseek(fp, 0, SEEK_SET); if(model_len != fread(model_net_2, 1, model_len, fp)) { printf("fread %s fail!\n", net[1]); free(model_net_2); return -1; } printf("model_len:%d\n",model_len); // rknn_init ret = rknn_init(&context_2, model_net_2, model_len, RKNN_FLA...
inputs［0］.buf = img.data;ret = rknn_inputs_set（ctx，io_num.n_input，inputs）;if（ret ...
pass_through = 0; inputs[0].type = RKNN_TENSOR_FLOAT16; inputs[0].fmt = RKNN_TENSOR_NHWC; ret = rknn_inputs_set(ctx, io_num.n_input, inputs); if (ret < 0) { printf("rknn_input_set fail! ret=%d\n", ret); return -1; } // Run printf("rknn_run\n"); ret = rknn_...
5. 6. 7. RKNN的python demo中,输出了模型的输入输出参数,对应上面的两种输出模式 : YOLO.RKNN model input num: 1, output num: 3 #index=0, name=images, n_dims=4, dims=[1, 640, 640, 3], n_elems=1228800, size=1228800, fmt=NHWC, type=INT8, qnt_type=AFFINE, zp=-128, scale=0.0039...
/* Set major static */ #define DEV_NAME "s3c_ds18b20" /* dynamic major by default */ #ifndef DEV_MAJOR #define DEV_MAJOR 0 #endif #define DQ S3C2410_GPG(0) #define INPUT S3C2410_GPIO_INPUT #define OUTPUT S3C2410_GPIO_OUTPUT
示例代码如下: rknn_sdk_version version; ret = rknn_query(ctx, RKNN_QUERY_SDK_VERSION, &version, sizeof(rknn_sdk_version)); printf("sdk api version: %s\n", version.api_version); printf("driver version: %s\n", version.drv_version); 3.2.3.4 rknn_inputs_set 通过 rknn_inputs_set ...
[0].type = RKNN_TENSOR_UINT8; inputs[0].size = img_width*img_height*img_channels; inputs[0].pass_through = FALSE; inputs[0].fmt = RKNN_TENSOR_NHWC; inputs[0].buf = in_data; ret = rknn_inputs_set(ctx, 1, inputs); For more detailed usage, see the step 4 of the [RKNN...