109 lines
4.3 KiB
C++
109 lines
4.3 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 "preprocess/cpu/opencv_utils.h"
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#include "preprocess/transform/transform.h"
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#include "preprocess/transform/transform_utils.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 TestCpuLoad(const Value& cfg, const cv::Mat& mat, PixelFormat src_format,
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PixelFormat dst_format) {
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Device device{"cpu"};
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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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auto res_mat = mmdeploy::cpu::Tensor2CVMat(res_tensor);
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cv::imwrite("ref.bmp", ref_mat);
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cv::imwrite("res.bmp", res_mat);
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REQUIRE(mmdeploy::cpu::Compare(ref_mat, res_mat));
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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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}
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void TestCudaLoad(const Value& cfg, const cv::Mat& mat, PixelFormat src_format,
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PixelFormat dst_format) {
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Device device{"cuda"};
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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 src_mat = cpu::CVMat2Mat(mat, PixelFormat(src_format));
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auto res = transform->Process({{"ori_img", src_mat}});
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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().is_device());
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Device _device{"cpu"};
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auto host_tensor = MakeAvailableOnDevice(res_tensor, _device, 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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// cv::imwrite("ref.bmp", ref_mat);
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// cv::imwrite("res.bmp", res_mat);
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REQUIRE(mmdeploy::cpu::Compare(ref_mat, res_mat));
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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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}
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TEST_CASE("prepare image, that is LoadImageFromFile transform", "[load]") {
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const char* img_path = "../../tests/preprocess/data/imagenet_banner.jpeg";
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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(lvhan): make up yuv nv12/nv21 mat
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// cv::Mat nv12_mat;
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// cv::Mat 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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TestCpuLoad(cfg, mat.first, mat.second,
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condition.first == "color" ? PixelFormat::kBGR : PixelFormat::kGRAYSCALE);
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TestCudaLoad(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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