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https://github.com/open-mmlab/mmdeploy.git
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* minor changes * support windows * fix GCC build * fix lint * reformat * fix Windows build * fix GCC build * search backend ops for onnxruntime * fix lint * fix lint * code clean-up * code clean-up * fix clang build * fix trt support * fix cmake for ncnn * fix cmake for openvino * fix SDK Python API * handle ops for other backends (ncnn, trt) * handle SDK Python API library location * robustify linkage * fix cuda * minor fix for openvino & ncnn * use CMAKE_CUDA_ARCHITECTURES if set * fix cuda preprocessor * fix misc * fix pplnn & pplcv, drop support for pplcv<0.6.0 * robustify cmake * update build.md (#2) * build dynamic modules as module library & fix demo (partially) * fix candidate path for mmdeploy_python * move "enable CUDA" to cmake config for demo * refine demo cmake * add comment * fix ubuntu build * revert docs/en/build.md * fix C API * fix lint * Windows build doc (#3) * check in docs related to mmdeploy build on windows * update build guide on windows platform * update build guide on windows platform * make path of thirdparty libraries consistent * make path consistency * correct build command for custom ops * correct build command for sdk * update sdk build instructions * update doc * correct build command * fix lint * correct build command and fix lint Co-authored-by: lvhan <lvhan@pjlab.org> * trailing whitespace (#4) * minor fix * fix sr sdk model * fix type deduction * fix cudaFree after driver shutting down * update ppl.cv installation warning (#5) * fix device allocator threshold & fix lint * update doc (#6) * update ppl.cv installation warning * missing 'git clone' Co-authored-by: chenxin <chenxin2@sensetime.com> Co-authored-by: zhangli <zhangli@sensetime.com> Co-authored-by: lvhan028 <lvhan_028@163.com> Co-authored-by: lvhan <lvhan@pjlab.org>
82 lines
3.1 KiB
C++
82 lines
3.1 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
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#include "catch.hpp"
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#include "core/mat.h"
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#include "core/tensor.h"
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#include "core/utils/device_utils.h"
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#include "opencv_utils.h"
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#include "preprocess/transform/transform.h"
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#include "test_resource.h"
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#include "test_utils.h"
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using namespace mmdeploy;
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using namespace std;
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using namespace mmdeploy::test;
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void TestLoad(const Value& cfg, const cv::Mat& mat, PixelFormat src_format,
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PixelFormat dst_format) {
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auto gResource = MMDeployTestResources::Get();
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for (auto const& device_name : gResource.device_names()) {
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Device device{device_name.c_str()};
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Stream stream{device};
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auto transform = CreateTransform(cfg, device, stream);
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REQUIRE(transform != nullptr);
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auto ref_mat = mmdeploy::cpu::ColorTransfer(mat, src_format, dst_format);
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auto res = transform->Process({{"ori_img", cpu::CVMat2Mat(mat, PixelFormat(src_format))}});
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REQUIRE(!res.has_error());
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auto res_tensor = res.value()["img"].get<Tensor>();
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REQUIRE(res_tensor.device() == device);
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REQUIRE(Shape(res.value(), "img_shape") ==
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vector<int64_t>{1, ref_mat.rows, ref_mat.cols, ref_mat.channels()});
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REQUIRE(Shape(res.value(), "ori_shape") ==
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vector<int64_t>{1, mat.rows, mat.cols, mat.channels()});
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REQUIRE(res.value().contains("img_fields"));
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REQUIRE(res.value()["img_fields"].is_array());
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REQUIRE(res.value()["img_fields"].size() == 1);
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REQUIRE(res.value()["img_fields"][0].get<string>() == "img");
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const Device kHost{"cpu"};
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auto host_tensor = MakeAvailableOnDevice(res_tensor, kHost, stream);
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REQUIRE(stream.Wait());
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auto res_mat = mmdeploy::cpu::Tensor2CVMat(host_tensor.value());
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REQUIRE(mmdeploy::cpu::Compare(ref_mat, res_mat));
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}
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}
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TEST_CASE("prepare image, that is LoadImageFromFile transform", "[load]") {
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auto gResource = MMDeployTestResources::Get();
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auto img_list = gResource.LocateImageResources("transform");
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REQUIRE(!img_list.empty());
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auto img_path = img_list.front();
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cv::Mat bgr_mat = cv::imread(img_path, cv::IMREAD_COLOR);
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cv::Mat gray_mat = cv::imread(img_path, cv::IMREAD_GRAYSCALE);
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cv::Mat rgb_mat;
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cv::Mat bgra_mat;
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// TODO: make up yuv nv12/nv21 mat
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cv::cvtColor(bgr_mat, rgb_mat, cv::COLOR_BGR2RGB);
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cv::cvtColor(bgr_mat, bgra_mat, cv::COLOR_BGR2BGRA);
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vector<pair<cv::Mat, PixelFormat>> mats{{bgr_mat, PixelFormat::kBGR},
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{rgb_mat, PixelFormat::kRGB},
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{gray_mat, PixelFormat::kGRAYSCALE},
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{bgra_mat, PixelFormat::kBGRA}};
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// pair is <color_type, to_float32>
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vector<pair<std::string, bool>> conditions{
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{"color", true}, {"color", false}, {"grayscale", true}, {"grayscale", false}};
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for (auto& condition : conditions) {
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Value cfg{{"type", "LoadImageFromFile"},
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{"to_float32", condition.second},
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{"color_type", condition.first}};
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for (auto& mat : mats) {
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TestLoad(cfg, mat.first, mat.second,
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condition.first == "color" ? PixelFormat::kBGR : PixelFormat::kGRAYSCALE);
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}
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}
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}
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