Hello 分類サンプル#

// Copyright (C) 2018-2024 Intel Corporation 
// SPDX-License-Identifier: Apache-2.0 
// 

#include <opencv_c_wrapper.h> 
#include <stdbool.h> 
#include <stdio.h> 
#include <stdlib.h> 
#include <string.h> 

#include "openvino/c/openvino.h" 

/**
 * @brief Struct to store infer results
 */ 
struct infer_result { 
    size_t class_id; 
    float probability; 
}; 

/**
 * @brief Sort result by probability
 * @param struct with infer results to sort
 * @param result_size of the struct
 * @return none
 */ 
int compare(const void* a, const void* b) { 
    const struct infer_result* sa = (const struct infer_result*)a; 
    const struct infer_result* sb = (const struct infer_result*)b; 
    if (sa->probability < sb->probability) { 
        return 1; 
    } else if ((sa->probability == sb->probability) && (sa->class_id > sb->class_id)) { 
        return 1; 
    } else if (sa->probability > sb->probability) { 
        return -1; 
    } 
    return 0; 
} 
void infer_result_sort(struct infer_result* results, size_t result_size) { 
    qsort(results, result_size, sizeof(struct infer_result), compare); 
} 

/**
 * @brief Convert output tensor to infer result struct for processing results
 * @param tensor of output tensor
 * @param result_size of the infer result
 * @return struct infer_result
 */ 
struct infer_result* tensor_to_infer_result(ov_tensor_t* tensor, size_t* result_size) { 
    ov_shape_t output_shape = {0}; 
    ov_status_e status = ov_tensor_get_shape(tensor, &output_shape); 
    if (status != OK) 
        return NULL; 

    *result_size = output_shape.dims[1]; 

    struct infer_result* results = (struct infer_result*)malloc(sizeof(struct infer_result) * (*result_size)); 
    if (!results) 
        return NULL; 

    void* data = NULL; 
    status = ov_tensor_data(tensor, &data); 
    if (status != OK) { 
        free(results); 
        return NULL; 
    } 
    float* float_data = (float*)(data); 

    size_t i; 
    for (i = 0; i < *result_size; ++i) { 
        results[i].class_id = i; 
        results[i].probability = float_data[i]; 
    } 

    ov_shape_free(&output_shape); 
    return results; 
} 

/** * @brief Print results of infer
 * @param results of the infer results
 * @param result_size of the struct of classification results
 * @param img_path image path
 * @return none
 */ 
void print_infer_result(struct infer_result* results, size_t result_size, const char* img_path) { 
    printf("\nImage %s\n", img_path); 
    printf("\nclassid probability\n"); 
    printf("------- -----------\n"); 
    size_t i; 
    for (i = 0; i < result_size; ++i) { 
        printf("%zu %f\n", results[i].class_id, results[i].probability); 
    } 
} 

void print_model_input_output_info(ov_model_t* model) { 
    char* friendly_name = NULL; 
    ov_model_get_friendly_name(model, &friendly_name); 
    printf("[INFO] model name: %s \n", friendly_name); 
    ov_free(friendly_name); 
} 

#define CHECK_STATUS(return_status) \ 
    if (return_status != OK) { \ 
        fprintf(stderr, "[ERROR] return status %d, line %d\n", return_status, __LINE__); \ 
        goto err; \ 
    } 

int main(int argc, char** argv) { 
    // -------- 入力パラメーターの確認 -------- 
    if (argc != 4) { 
        printf("Usage : ./hello_classification_c <path_to_model> <path_to_image> 「 
              "<device_name>\n"); 
        return EXIT_FAILURE; 
} 

    ov_core_t* core = NULL; 
    ov_model_t* model = NULL; 
    ov_tensor_t* tensor = NULL; 
    ov_preprocess_prepostprocessor_t* preprocess = NULL; 
    ov_preprocess_input_info_t* input_info = NULL; 
    ov_model_t* new_model = NULL; 
    ov_preprocess_input_tensor_info_t* input_tensor_info = NULL; 
    ov_preprocess_preprocess_steps_t* input_process = NULL; 
    ov_preprocess_input_model_info_t* p_input_model = NULL; 
    ov_preprocess_output_info_t* output_info = NULL; 
    ov_preprocess_output_tensor_info_t* output_tensor_info = NULL; 
    ov_compiled_model_t* compiled_model = NULL; 
    ov_infer_request_t* infer_request = NULL; 
    ov_tensor_t* output_tensor = NULL; 
    struct infer_result* results = NULL; 
    ov_layout_t* input_layout = NULL; 
    ov_layout_t* model_layout = NULL; 
    ov_shape_t input_shape; ov_output_const_port_t* output_port = NULL; 
    ov_output_const_port_t* input_port = NULL; 

    // -------- OpenVINO ランタイムのバージョンを取得 -------- 
    ov_version_t version; 
    CHECK_STATUS(ov_get_openvino_version(&version)); 
    printf("---- OpenVINO INFO----\n"); 
    printf("Description : %s \n", version.description); 
    printf("Build number: %s \n", version.buildNumber); 
    ov_version_free(&version); 

    // -------- 入力引数の解析と検証 -------- 
    const char* input_model = argv[1]; 
    const char* input_image_path = argv[2]; 
    const char* device_name = argv[3]; 

    // -------- ステップ 1. OpenVINO ランタイムコアを初期化 -------- 
    CHECK_STATUS(ov_core_create(&core)); 

    // -------- ステップ 2. モデルの読み取り -------- 
printf("[INFO] Loading model files: %s\n", input_model); 
    CHECK_STATUS(ov_core_read_model(core, input_model, NULL, &model)); 
    print_model_input_output_info(model); 
    CHECK_STATUS(ov_model_const_output(model, &output_port)); 
    if (!output_port) { 
        fprintf(stderr, "[ERROR] Sample supports models with 1 output only %d\n", __LINE__); 
        goto err; 
    } 

    CHECK_STATUS(ov_model_const_input(model, &input_port)); 
    if (!input_port) { 
        fprintf(stderr, "[ERROR] Sample supports models with 1 input only %d\n", __LINE__); 
        goto err; 
    } 

    // -------- ステップ 3. 入力をセットアップ 
    c_mat_t img; 
    image_read(input_image_path, &img); 
    ov_element_type_e input_type = U8; 
    int64_t dims[4] = {1, (size_t)img.mat_height, (size_t)img.mat_width, 3}; 
    ov_shape_create(4, dims, &input_shape); 
    CHECK_STATUS(ov_tensor_create_from_host_ptr(input_type, input_shape, img.mat_data, &tensor)); 

    // -------- ステップ 4. 前処理を構成 -------- 
    CHECK_STATUS(ov_preprocess_prepostprocessor_create(model, &preprocess)); 
    CHECK_STATUS(ov_preprocess_prepostprocessor_get_input_info_by_index(preprocess, 0, &input_info)); 
    CHECK_STATUS(ov_preprocess_input_info_get_tensor_info(input_info, &input_tensor_info)); 
    CHECK_STATUS(ov_preprocess_input_tensor_info_set_from(input_tensor_info, tensor));

    const char* input_layout_desc = "NHWC"; 
    CHECK_STATUS(ov_layout_create(input_layout_desc, &input_layout)); 
    CHECK_STATUS(ov_preprocess_input_tensor_info_set_layout(input_tensor_info, input_layout)); 
    CHECK_STATUS(ov_preprocess_input_info_get_preprocess_steps(input_info, &input_process)); 
    CHECK_STATUS(ov_preprocess_preprocess_steps_resize(input_process, RESIZE_LINEAR)); 
    CHECK_STATUS(ov_preprocess_input_info_get_model_info(input_info, &p_input_model)); 

    const char* model_layout_desc = "NCHW"; 
    CHECK_STATUS(ov_layout_create(model_layout_desc, &model_layout)); 
    CHECK_STATUS(ov_preprocess_input_model_info_set_layout(p_input_model, model_layout)); 
    CHECK_STATUS(ov_preprocess_prepostprocessor_get_output_info_by_index(preprocess, 0, &output_info)); 
    CHECK_STATUS(ov_preprocess_output_info_get_tensor_info(output_info, &output_tensor_info)); 
    CHECK_STATUS(ov_preprocess_output_set_element_type(output_tensor_info, F32)); 
    CHECK_STATUS(ov_preprocess_prepostprocessor_build(preprocess, &new_model)); 

    // -------- ステップ 5. モデルをデバイスにロード -------- 
CHECK_STATUS(ov_core_compile_model(core, new_model, device_name, 0, &compiled_model)); 

    // -------- ステップ 6. 推論要求を作成 -------- 
    CHECK_STATUS(ov_compiled_model_create_infer_request(compiled_model, &infer_request)); 

    // -------- ステップ 7. 入力の準備 -------- 
    CHECK_STATUS(ov_infer_request_set_input_tensor_by_index(infer_request, 0, tensor)); 

    // -------- ステップ 8. 推論を同期的に行う -------- 
    CHECK_STATUS(ov_infer_request_infer(infer_request)); 

    // -------- ステップ 9. 出力処理 
    CHECK_STATUS(ov_infer_request_get_output_tensor_by_index(infer_request, 0, &output_tensor)); 
    // 分類結果をプリント 
    size_t results_num; 
    results = tensor_to_infer_result(output_tensor, &results_num); 
    infer_result_sort(results, results_num); 
    size_t top = 10; 
    if (top > results_num) { 
        top = results_num; 
    } 
    printf("\nTop %zu results:\n", top); 
    print_infer_result(results, top, input_image_path); 

    // -------- 割り当てられたリソースを解放 --------
err: 
    free(results); 
    image_free(&img); 
    ov_shape_free(&input_shape); 
    ov_output_const_port_free(output_port); 
    ov_output_const_port_free(input_port); if (output_tensor) ov_tensor_free(output_tensor); 
    if (infer_request) 
        ov_infer_request_free(infer_request); 
    if (compiled_model) 
        ov_compiled_model_free(compiled_model); 
    if (input_layout) 
        ov_layout_free(input_layout); 
    if (model_layout) 
        ov_layout_free(model_layout); 
    if (output_tensor_info) 
        ov_preprocess_output_tensor_info_free(output_tensor_info); 
    if (output_info) 
        ov_preprocess_output_info_free(output_info); 
    if (p_input_model) 
        ov_preprocess_input_model_info_free(p_input_model); 
    if (input_process) 
        ov_preprocess_preprocess_steps_free(input_process); 
    if (input_tensor_info) 
        ov_preprocess_input_tensor_info_free(input_tensor_info); 
    if (input_info) 
        ov_preprocess_input_info_free(input_info); 
    if (preprocess) 
        ov_preprocess_prepostprocessor_free(preprocess); 
    if (new_model) 
        ov_model_free(new_model); 
    if (tensor) 
        ov_tensor_free(tensor); 
    if (model) 
        ov_model_free(model); 
    if (core) 
        ov_core_free(core); 
    return EXIT_SUCCESS; 
}