mmdeploy/tests/test_csrc/preprocess/test_crop.cpp

112 lines
3.8 KiB
C++

// 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 "opencv_utils.h"
#include "test_resource.h"
#include "test_utils.h"
using namespace mmdeploy;
using namespace framework;
using namespace std;
using namespace mmdeploy::test;
tuple<int, int, int, int> CenterCropArea(const cv::Mat& mat, int crop_height, int crop_width) {
auto img_height = mat.rows;
auto img_width = mat.cols;
auto y1 = max(0, int(round((img_height - crop_height) / 2.)));
auto x1 = max(0, int(round((img_width - crop_width) / 2.)));
auto y2 = min(img_height, y1 + crop_height) - 1;
auto x2 = min(img_width, x1 + crop_width) - 1;
return {y1, x1, y2, x2};
}
void TestCenterCrop(const Value& cfg, const cv::Mat& mat, int crop_height, int crop_width) {
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 [top, left, bottom, right] = CenterCropArea(mat, crop_height, crop_width);
auto ref_mat = mmdeploy::cpu::Crop(mat, top, left, bottom, right);
auto res = transform->Process({{"img", cpu::CVMat2Tensor(mat)}});
REQUIRE(!res.has_error());
auto res_tensor = res.value()["img"].get<Tensor>();
REQUIRE(res_tensor.device() == device);
REQUIRE(Shape(res.value(), "img_shape") ==
vector<int64_t>{1, ref_mat.rows, ref_mat.cols, ref_mat.channels()});
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 CenterCrop", "[crop]") {
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::imread(img_path, cv::IMREAD_GRAYSCALE);
cv::Mat bgr_float_mat;
cv::Mat gray_float_mat;
bgr_mat.convertTo(bgr_float_mat, CV_32FC3);
gray_mat.convertTo(gray_float_mat, CV_32FC1);
vector<cv::Mat> mats{bgr_mat, gray_mat, bgr_float_mat, gray_float_mat};
SECTION("crop_size: int; small size") {
constexpr int crop_size = 224;
Value cfg{{"type", "CenterCrop"}, {"crop_size", crop_size}};
for (auto& mat : mats) {
TestCenterCrop(cfg, mat, crop_size, crop_size);
}
}
SECTION("crop_size: int; oversize") {
constexpr int crop_size = 800;
Value cfg{{"type", "CenterCrop"}, {"crop_size", crop_size}};
for (auto& mat : mats) {
TestCenterCrop(cfg, mat, crop_size, crop_size);
}
}
SECTION("crop_size: tuple") {
constexpr int crop_height = 224;
constexpr int crop_width = 224;
Value cfg{{"type", "CenterCrop"}, {"crop_size", {crop_height, crop_width}}};
for (auto& mat : mats) {
TestCenterCrop(cfg, mat, crop_height, crop_width);
}
}
SECTION("crop_size: tuple;oversize in height") {
constexpr int crop_height = 640;
constexpr int crop_width = 224;
Value cfg{{"type", "CenterCrop"}, {"crop_size", {crop_height, crop_width}}};
for (auto& mat : mats) {
TestCenterCrop(cfg, mat, crop_height, crop_width);
}
}
SECTION("crop_size: tuple;oversize in width") {
constexpr int crop_height = 224;
constexpr int crop_width = 800;
Value cfg{{"type", "CenterCrop"}, {"crop_size", {crop_height, crop_width}}};
for (auto& mat : mats) {
TestCenterCrop(cfg, mat, crop_height, crop_width);
}
}
}