Function run_model

yolox_example/main.cpp:334–368

}

std::vector<float> run_model(LiteNetwork model) {
    struct timeval start;
    struct timeval end;
    gettimeofday(&start, NULL);
    LITE_CAPI_CHECK(LITE_forward(model), "run model failed\n");
    LITE_CAPI_CHECK(LITE_wait(model), "wait model failed\n");
    gettimeofday(&end, NULL);
    unsigned long diff =
            1000000 * (end.tv_sec - start.tv_sec) + end.tv_usec - start.tv_usec;
    printf("every iter use time: %fms\n", ((float)diff) / 1000);
    LiteTensor output;
    size_t nr_output = 0;
    LITE_CAPI_CHECK(
            LITE_get_all_output_name(model, &nr_output, NULL),
            "get output number failed\n");
    char* output_name_ptr[nr_output];
    LITE_CAPI_CHECK(
            LITE_get_all_output_name(model, NULL, (const char**)&output_name_ptr),
            "get output name failed\n");
    LITE_CAPI_CHECK(
            LITE_get_io_tensor(model, output_name_ptr[0], LITE_OUTPUT, &output),
            "get output tensor failed\n");
    size_t length = 0;
    LITE_CAPI_CHECK(
            LITE_get_tensor_total_size_in_byte(output, &length),
            "get output tensor size failed\n");
    float* output_ptr = NULL;
    LITE_CAPI_CHECK(
            LITE_get_tensor_memory(output, (void**)&output_ptr),
            "get output tensor memory failed\n");

    std::vector<float> output_vec(output_ptr, output_ptr + length / sizeof(float));

    return output_vec;
}

std::vector<float> inference(const char* model_path, std::vector<float>& input_data) {
    LITE_set_log_level(INFO);