// Copyright (c) OpenMMLab. All rights reserved. #include "catch.hpp" #include "mmdeploy/core/mat.h" #include "mmdeploy/core/utils/device_utils.h" #include "mmdeploy/preprocess/transform/transform.h" #include "opencv2/imgcodecs/imgcodecs.hpp" #include "opencv2/imgproc/imgproc.hpp" #include "opencv_utils.h" #include "test_resource.h" #include "test_utils.h" using namespace mmdeploy; using namespace framework; using namespace std; using namespace mmdeploy::test; // left, top, right, bottom tuple GetPadSize(const cv::Mat& mat, int dst_height, int dst_width) { return {0, 0, dst_width - mat.cols, dst_height - mat.rows}; } tuple GetPadSize(const cv::Mat& mat, bool square = true) { int size = std::max(mat.rows, mat.cols); return GetPadSize(mat, size, size); } tuple GetPadSize(const cv::Mat& mat, int divisor) { auto pad_h = int(ceil(mat.rows * 1.0 / divisor)) * divisor; auto pad_w = int(ceil(mat.cols * 1.0 / divisor)) * divisor; return GetPadSize(mat, pad_h, pad_w); } void TestPad(const Value& cfg, const cv::Mat& mat, int top, int left, int bottom, int right, int border_type, float val) { auto gResource = MMDeployTestResources::Get(); for (auto const& device_name : gResource.device_names()) { Device device{device_name.c_str()}; Stream stream{device}; auto transform = CreateTransform(cfg, device, stream); REQUIRE(transform != nullptr); auto ref_mat = mmdeploy::cpu::Pad(mat, top, left, bottom, right, border_type, val); auto res = transform->Process({{"img", cpu::CVMat2Tensor(mat)}}); REQUIRE(!res.has_error()); auto res_tensor = res.value()["img"].get(); REQUIRE(res_tensor.device() == device); REQUIRE(Shape(res.value(), "pad_shape") == vector{1, ref_mat.rows, ref_mat.cols, ref_mat.channels()}); REQUIRE(Shape(res.value(), "pad_fixed_size") == std::vector{ref_mat.rows, ref_mat.cols}); const Device kHost{"cpu"}; auto host_tensor = MakeAvailableOnDevice(res_tensor, kHost, stream); REQUIRE(stream.Wait()); auto res_mat = mmdeploy::cpu::Tensor2CVMat(host_tensor.value()); REQUIRE(mmdeploy::cpu::Compare(ref_mat, res_mat)); } } TEST_CASE("transform 'Pad'", "[pad]") { auto gResource = MMDeployTestResources::Get(); auto img_list = gResource.LocateImageResources("transform"); REQUIRE(!img_list.empty()); auto img_path = img_list.front(); cv::Mat bgr_mat = cv::imread(img_path, cv::IMREAD_COLOR); cv::Mat gray_mat; cv::Mat float_bgr_mat; cv::Mat float_gray_mat; cv::cvtColor(bgr_mat, gray_mat, cv::COLOR_BGR2GRAY); bgr_mat.convertTo(float_bgr_mat, CV_32FC3); gray_mat.convertTo(float_gray_mat, CV_32FC1); vector mats{bgr_mat, gray_mat, float_bgr_mat, float_gray_mat}; vector modes{"constant", "edge", "reflect", "symmetric"}; map border_map{{"constant", cv::BORDER_CONSTANT}, {"edge", cv::BORDER_REPLICATE}, {"reflect", cv::BORDER_REFLECT_101}, {"symmetric", cv::BORDER_REFLECT}}; SECTION("pad to square") { bool square{true}; float val = 255.0f; for (auto& mat : mats) { for (auto& mode : modes) { Value cfg{ {"type", "Pad"}, {"pad_to_square", square}, {"padding_mode", mode}, {"pad_val", val}}; auto [pad_left, pad_top, pad_right, pad_bottom] = GetPadSize(mat, square); TestPad(cfg, mat, pad_top, pad_left, pad_bottom, pad_right, border_map[mode], 255); } } } SECTION("pad with size_divisor") { constexpr int divisor = 32; float val = 255.0f; for (auto& mat : mats) { for (auto& mode : modes) { Value cfg{ {"type", "Pad"}, {"size_divisor", divisor}, {"padding_mode", mode}, {"pad_val", val}}; auto [pad_left, pad_top, pad_right, pad_bottom] = GetPadSize(mat, divisor); TestPad(cfg, mat, pad_top, pad_left, pad_bottom, pad_right, border_map[mode], 255); } } } SECTION("pad with size") { constexpr int height = 600; constexpr int width = 800; for (auto& mat : mats) { for (auto& mode : modes) { Value cfg{{"type", "Pad"}, {"size", {width, height}}, {"padding_mode", mode}}; auto [pad_left, pad_top, pad_right, pad_bottom] = GetPadSize(mat, height, width); TestPad(cfg, mat, pad_top, pad_left, pad_bottom, pad_right, border_map[mode], 0); } } } }