Function preprocess_image

lite/example/cpp_example/mge/cv/detect_yolox.cpp:29–78

namespace {

void preprocess_image(
        uint8_t* image, const int width, const int height, const int channel,
        std::shared_ptr<Tensor> tensor) {
    auto layout = tensor->get_layout();
    for (size_t i = 0; i < layout.ndim; i++) {
        printf("model input shape[%zu]=%zu \n", i, layout.shapes[i]);
    }

    //! resize to target shape
    float r = std::min(INPUT_W / (width * 1.0), INPUT_H / (height * 1.0));
    int unpad_w = r * width;
    int unpad_h = r * height;

    std::shared_ptr<std::vector<uint8_t>> resize_int8 =
            std::make_shared<std::vector<uint8_t>>(unpad_w * unpad_h * channel);
    stbir_resize_uint8(
            image, width, height, 0, resize_int8->data(), unpad_w, unpad_h, 0, channel);

    std::shared_ptr<std::vector<uint8_t>> padded;
    if (unpad_h != INPUT_H || unpad_w != INPUT_W) {
        padded = std::make_shared<std::vector<uint8_t>>(
                INPUT_H * INPUT_W * channel, 114);
        for (int h = 0; h < unpad_h; h++) {
            for (int w = 0; w < unpad_w; w++) {
                for (int c = 0; c < channel; c++) {
                    (*padded)[h * INPUT_W * channel + w * channel + c] =
                            (*resize_int8)[h * unpad_w * channel + w * channel + c];
                }
            }
        }
    } else {
        padded = resize_int8;
    }

    tensor->set_layout({{1, 3, 640, 640}, 4});

    std::vector<float> mean = {0.485, 0.456, 0.406};
    std::vector<float> std = {0.229, 0.224, 0.225};

    //! convert form rgb to bgr, relayout from hwc to chw, normalization copy to tensor
    float* in_data = static_cast<float*>(tensor->get_memory_ptr());
    size_t pixels = INPUT_H * INPUT_W;
    for (size_t i = 0; i < pixels; i++) {
        in_data[i] = (padded->at(i * channel + 0) / 255.0f - mean[0]) / std[0];
        in_data[i + 1 * pixels] =
                (padded->at(i * channel + 1) / 255.0f - mean[1]) / std[1];
        in_data[i + 2 * pixels] =
                (padded->at(i * channel + 2) / 255.0f - mean[2]) / std[2];
    }
}

struct Rect {
    float x;