mmdeploy/demo/csrc/object_detection.cpp

55 lines
1.6 KiB
C++
Raw Normal View History

Merge sdk (#251) * check in cmake * move backend_ops to csrc/backend_ops * check in preprocess, model, some codebase and their c-apis * check in CMakeLists.txt * check in parts of test_csrc * commit everything else * add readme * update core's BUILD_INTERFACE directory * skip codespell on third_party * update trt_net and ort_net's CMakeLists * ignore clion's build directory * check in pybind11 * add onnx.proto. Remove MMDeploy's dependency on ncnn's source code * export MMDeployTargets only when MMDEPLOY_BUILD_SDK is ON * remove useless message * target include directory is wrong * change target name from mmdeploy_ppl_net to mmdeploy_pplnn_net * skip install directory * update project's cmake * remove useless code * set CMAKE_BUILD_TYPE to Release by force if it isn't set by user * update custom ops CMakeLists * pass object target's source lists * fix lint end-of-file * fix lint: trailing whitespace * fix codespell hook * remove bicubic_interpolate to csrc/backend_ops/ * set MMDEPLOY_BUILD_SDK OFF * change custom ops build command * add spdlog installation command * update docs on how to checkout pybind11 * move bicubic_interpolate to backend_ops/tensorrt directory * remove useless code * correct cmake * fix typo * fix typo * fix install directory * correct sdk's readme * set cub dir when cuda version < 11.0 * change directory where clang-format will apply to * fix build command * add .clang-format * change clang-format style from google to file * reformat csrc/backend_ops * format sdk's code * turn off clang-format for some files * add -Xcompiler=-fno-gnu-unique * fix trt topk initialize * check in config for sdk demo * update cmake script and csrc's readme * correct config's path * add cuda include directory, otherwise compile failed in case of tensorrt8.2 * clang-format onnx2ncnn.cpp Co-authored-by: zhangli <lzhang329@gmail.com> Co-authored-by: grimoire <yaoqian@sensetime.com>
2021-12-07 10:57:55 +08:00
#include "detector.h"
#include <fstream>
#include <string>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
int main(int argc, char *argv[]) {
if (argc != 3) {
fprintf(stderr, "usage:\n object_detection model_path image_path\n");
return 1;
}
auto model_path = argv[1];
auto image_path = argv[2];
cv::Mat img = cv::imread(argv[2]);
if (!img.data) {
fprintf(stderr, "failed to load image: %s\n", image_path);
return 1;
}
mm_handle_t detector{};
int status{};
status = mmdeploy_detector_create_by_path(model_path, "cpu", 0, &detector);
if (status != MM_SUCCESS) {
fprintf(stderr, "failed to create detector, code: %d\n", (int) status);
return 1;
}
mm_mat_t mat{img.data, img.rows, img.cols, 3, MM_BGR, MM_INT8};
mm_detect_t *bboxes{};
int *res_count{};
status = mmdeploy_detector_apply(detector, &mat, 1, &bboxes, &res_count);
if (status != MM_SUCCESS) {
fprintf(stderr, "failed to apply detector, code: %d\n", (int) status);
return 1;
}
fprintf(stderr, "bbox_count=%d\n", *res_count);
for (int i = 0; i < *res_count; ++i) {
const auto &box = bboxes[i].bbox;
fprintf(stderr, "box %d, left=%d, top=%d, right=%d, bottom=%d, label=%d, score=%.4f\n",
i, box.left, box.top, box.right, box.bottom, bboxes[i].label_id, bboxes[i].score);
cv::rectangle(img, cv::Point{box.left, box.top}, cv::Point{box.right, box.bottom}, cv::Scalar{0, 255, 0});
}
cv::imwrite("out.png", img);
mmdeploy_detector_release_result(bboxes, res_count, 1);
mmdeploy_detector_destroy(detector);
return 0;
}