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https://github.com/open-mmlab/mmdeploy.git
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14b2bfd524
* unify C API naming * fix demo and move apis/c/* -> apis/c/mmdeploy/* * fix lint * fix C# project * fix Java API
97 lines
3.5 KiB
C++
97 lines
3.5 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
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// clang-format off
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#include "catch.hpp"
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// clang-format on
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#include "mmdeploy/apis/c/mmdeploy/detector.h"
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#include "mmdeploy/core/logger.h"
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#include "mmdeploy/core/utils/formatter.h"
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#include "opencv2/opencv.hpp"
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#include "test_resource.h"
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using namespace std;
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TEST_CASE("test detector's c api", "[.detector][resource]") {
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MMDEPLOY_INFO("test detector");
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auto test = [](const string &device, const string &model_path, const vector<string> &img_list) {
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mmdeploy_detector_t detector{nullptr};
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auto ret = mmdeploy_detector_create_by_path(model_path.c_str(), device.c_str(), 0, &detector);
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REQUIRE(ret == MMDEPLOY_SUCCESS);
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vector<cv::Mat> cv_mats;
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vector<mmdeploy_mat_t> mats;
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for (auto &img_path : img_list) {
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cv::Mat mat = cv::imread(img_path);
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REQUIRE(!mat.empty());
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cv_mats.push_back(mat);
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mats.push_back({mat.data, mat.rows, mat.cols, mat.channels(), MMDEPLOY_PIXEL_FORMAT_BGR,
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MMDEPLOY_DATA_TYPE_UINT8});
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}
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mmdeploy_detection_t *results{nullptr};
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int *result_count{nullptr};
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ret = mmdeploy_detector_apply(detector, mats.data(), (int)mats.size(), &results, &result_count);
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REQUIRE(ret == MMDEPLOY_SUCCESS);
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auto result_ptr = results;
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for (auto i = 0; i < mats.size(); ++i) {
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MMDEPLOY_INFO("the '{}-th' image has '{}' objects", i, result_count[i]);
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for (auto j = 0; j < result_count[i]; ++j, ++result_ptr) {
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auto &bbox = result_ptr->bbox;
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MMDEPLOY_INFO(" >> bbox[{}, {}, {}, {}], label_id {}, score {}", bbox.left, bbox.top,
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bbox.right, bbox.bottom, result_ptr->label_id, result_ptr->score);
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}
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}
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mmdeploy_detector_release_result(results, result_count, (int)mats.size());
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mmdeploy_detector_destroy(detector);
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};
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MMDEPLOY_INFO("get test resources");
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auto &gResources = MMDeployTestResources::Get();
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MMDEPLOY_INFO("locate image resources");
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auto img_lists = gResources.LocateImageResources(fs::path{"mmdet"} / "images");
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MMDEPLOY_INFO("{}", img_lists.size());
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REQUIRE(!img_lists.empty());
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for (auto &backend : gResources.backends()) {
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MMDEPLOY_INFO("backend: {}", backend);
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DYNAMIC_SECTION("loop backend: " << backend) {
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auto model_list = gResources.LocateModelResources(fs::path{"mmdet"} / backend);
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REQUIRE(!model_list.empty());
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for (auto &model_path : model_list) {
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MMDEPLOY_INFO("model: {}", model_path);
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for (auto &device_name : gResources.device_names(backend)) {
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test(device_name, model_path, img_lists);
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}
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}
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}
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}
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}
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#if 0
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TEST_CASE("test detector's c api", "[detector]") {
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mm_model_t model{};
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// pretend the model is loaded
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mm_handle_t handle{};
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mmdeploy_async_detector_create(model, "cuda", 0, &handle);
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std::vector<mm_mat_t> imgs;
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std::vector<mmdeploy_sender_t> sndrs;
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for (const auto &img : imgs) {
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mmdeploy_value_t value = mmdeploy_async_detector_create_input(&img, 1);
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mmdeploy_sender_t input = mmdeploy_executor_just(value);
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mmdeploy_sender_t detect = mmdeploy_async_detector_apply(handle, input);
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mmdeploy_sender_t started = mmdeploy_executor_ensure_started(detect);
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sndrs.push_back(started);
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}
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for (int i = 0; i < imgs.size(); ++i) {
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mmdeploy_value_t output = mmdeploy_executor_sync_wait(sndrs[i]);
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mm_detect_t *dets{};
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int *count{};
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mmdeploy_async_detector_get_result(output, &dets, &count);
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mmdeploy_detector_release_result(dets, count, 1);
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}
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mmdeploy_async_detector_destroy(handle);
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}
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#endif
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