69 lines
2.4 KiB
C++
69 lines
2.4 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
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#include "catch.hpp"
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#include "core/tensor.h"
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#include "core/utils/device_utils.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 "test_resource.h"
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#include "test_utils.h"
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using namespace mmdeploy;
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using namespace mmdeploy::test;
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using namespace std;
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void TestImage2Tensor(const Value& cfg, const cv::Mat& mat) {
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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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vector<cv::Mat> channel_mats(mat.channels());
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for (auto i = 0; i < mat.channels(); ++i) {
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cv::extractChannel(mat, channel_mats[i], i);
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}
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auto res = transform->Process({{"img", cpu::CVMat2Tensor(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() == device);
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auto shape = res_tensor.desc().shape;
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REQUIRE(shape == std::vector<int64_t>{1, mat.channels(), mat.rows, mat.cols});
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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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// mat's shape is {h, w, c}, while res_tensor's shape is {1, c, h, w}
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// compare each channel between `res_tensor` and `mat`
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auto step = shape[2] * shape[3] * mat.elemSize1();
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auto data = host_tensor.value().data<uint8_t>();
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for (auto i = 0; i < mat.channels(); ++i) {
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cv::Mat _mat{mat.rows, mat.cols, CV_MAKETYPE(mat.depth(), 1), data};
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REQUIRE(::mmdeploy::cpu::Compare(channel_mats[i], _mat));
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data += step;
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}
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}
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}
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TEST_CASE("transform ImageToTensor", "[img2tensor]") {
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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 bgr_float_mat;
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cv::Mat gray_float_mat;
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bgr_mat.convertTo(bgr_float_mat, CV_32FC3);
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gray_mat.convertTo(gray_float_mat, CV_32FC1);
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Value cfg{{"type", "ImageToTensor"}, {"keys", {"img"}}};
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vector<cv::Mat> mats{bgr_mat, gray_mat, bgr_float_mat, gray_float_mat};
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for (auto& mat : mats) {
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TestImage2Tensor(cfg, mat);
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}
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}
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