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https://github.com/open-mmlab/mmdeploy.git
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a494a6f6ff
* sync SDK changes according to performance benchmarks * fix end-of-file lint * fix clang-format issue * fix clang-format by adding 'clang-format off' * remove useless casts * remove 'data' argument of 'operator()' * change 'Tensor2Img' to 'TensorToImg' according to spec * correct tensor's name according spec Co-authored-by: lvhan028 <lvhan_028@163.com>
41 lines
1.4 KiB
C++
41 lines
1.4 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 <iostream>
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#include "apis/c/detector.h"
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#include "opencv2/opencv.hpp"
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using namespace std;
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TEST_CASE("test detector's c api", "[detector]") {
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mm_handle_t handle{nullptr};
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auto model_path = "../../config/detector/retinanet_t4-cuda11.1-trt7.2-fp32";
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auto ret = mmdeploy_detector_create_by_path(model_path, "cuda", 0, &handle);
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REQUIRE(ret == MM_SUCCESS);
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cv::Mat mat = cv::imread("../../tests/data/images/dogs.jpg");
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vector<mm_mat_t> mats{{mat.data, mat.rows, mat.cols, mat.channels(), MM_BGR, MM_INT8}};
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mm_detect_t* results{nullptr};
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int* result_count{nullptr};
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ret = mmdeploy_detector_apply(handle, mats.data(), (int)mats.size(), &results, &result_count);
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REQUIRE(ret == MM_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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cout << "the " << i << "-th image has '" << result_count[i] << "' objects" << endl;
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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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cout << " >> bbox[" << bbox.left << ", " << bbox.top << ", " << bbox.right << ", "
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<< bbox.bottom << "], label_id " << result_ptr->label_id << ", score "
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<< result_ptr->score << endl;
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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(handle);
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}
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