mmdeploy/demo/csrc/c/image_classification.cpp

49 lines
1.4 KiB
C++

#include <fstream>
#include <opencv2/imgcodecs/imgcodecs.hpp>
#include <string>
#include "mmdeploy/classifier.h"
int main(int argc, char* argv[]) {
if (argc != 4) {
fprintf(stderr, "usage:\n image_classification device_name dump_model_directory image_path\n");
return 1;
}
auto device_name = argv[1];
auto model_path = argv[2];
auto image_path = argv[3];
cv::Mat img = cv::imread(image_path);
if (!img.data) {
fprintf(stderr, "failed to load image: %s\n", image_path);
return 1;
}
mmdeploy_classifier_t classifier{};
int status{};
status = mmdeploy_classifier_create_by_path(model_path, device_name, 0, &classifier);
if (status != MMDEPLOY_SUCCESS) {
fprintf(stderr, "failed to create classifier, code: %d\n", (int)status);
return 1;
}
mmdeploy_mat_t mat{
img.data, img.rows, img.cols, 3, MMDEPLOY_PIXEL_FORMAT_BGR, MMDEPLOY_DATA_TYPE_UINT8};
mmdeploy_classification_t* res{};
int* res_count{};
status = mmdeploy_classifier_apply(classifier, &mat, 1, &res, &res_count);
if (status != MMDEPLOY_SUCCESS) {
fprintf(stderr, "failed to apply classifier, code: %d\n", (int)status);
return 1;
}
for (int i = 0; i < res_count[0]; ++i) {
fprintf(stderr, "label: %d, score: %.4f\n", res[i].label_id, res[i].score);
}
mmdeploy_classifier_release_result(res, res_count, 1);
mmdeploy_classifier_destroy(classifier);
return 0;
}