// Copyright (c) OpenMMLab. All rights reserved. // clang-format off #include "catch.hpp" // clang-format on #include "apis/c/text_recognizer.h" #include "core/logger.h" #include "core/utils/formatter.h" #include "opencv2/opencv.hpp" #include "test_resource.h" using namespace std; TEST_CASE("test text recognizer's c api", "[text-recognizer]") { auto test = [](const string& device, const string& model_path, const vector& img_list) { mm_handle_t handle{nullptr}; auto ret = mmdeploy_text_recognizer_create_by_path(model_path.c_str(), device.c_str(), 0, &handle); REQUIRE(ret == MM_SUCCESS); vector cv_mats; vector mats; for (auto& img_path : img_list) { cv::Mat mat = cv::imread(img_path); REQUIRE(!mat.empty()); cv_mats.push_back(mat); mats.push_back({mat.data, mat.rows, mat.cols, mat.channels(), MM_BGR, MM_INT8}); } mm_text_recognize_t* results{}; ret = mmdeploy_text_recognizer_apply_bbox(handle, mats.data(), (int)mats.size(), nullptr, nullptr, &results); REQUIRE(ret == MM_SUCCESS); for (auto i = 0; i < mats.size(); ++i) { std::vector score(results[i].score, results[i].score + results[i].length); INFO("image {}, text = {}, score = {}", i, results[i].text, score); } mmdeploy_text_recognizer_release_result(results, (int)mats.size()); mmdeploy_text_recognizer_destroy(handle); }; auto& gResources = MMDeployTestResources::Get(); auto img_list = gResources.LocateImageResources("mmocr/images"); REQUIRE(!img_list.empty()); for (auto& backend : gResources.backends()) { DYNAMIC_SECTION("loop backend: " << backend) { auto model_list = gResources.LocateModelResources("mmocr/textreg/" + backend); REQUIRE(!model_list.empty()); for (auto& model_path : model_list) { for (auto& device_name : gResources.device_names(backend)) { test(device_name, model_path, img_list); } } } } } TEST_CASE("test text detector-recognizer combo", "[text-detector-recognizer]") { auto test = [](const std::string& device, const string& det_model_path, const string& reg_model_path, std::vector& img_list) { mm_handle_t detector{}; REQUIRE(mmdeploy_text_detector_create_by_path(det_model_path.c_str(), device.c_str(), 0, &detector) == MM_SUCCESS); mm_handle_t recognizer{}; REQUIRE(mmdeploy_text_recognizer_create_by_path(reg_model_path.c_str(), device.c_str(), 0, &recognizer) == MM_SUCCESS); vector cv_mats; vector mats; for (const auto& img_path : img_list) { cv::Mat mat = cv::imread(img_path); REQUIRE(!mat.empty()); cv_mats.push_back(mat); mats.push_back({mat.data, mat.rows, mat.cols, mat.channels(), MM_BGR, MM_INT8}); } mm_text_detect_t* bboxes{}; int* bbox_count{}; REQUIRE(mmdeploy_text_detector_apply(detector, mats.data(), mats.size(), &bboxes, &bbox_count) == MM_SUCCESS); mm_text_recognize_t* texts{}; REQUIRE(mmdeploy_text_recognizer_apply_bbox(recognizer, mats.data(), (int)mats.size(), bboxes, bbox_count, &texts) == MM_SUCCESS); int offset = 0; for (auto i = 0; i < mats.size(); ++i) { for (int j = 0; j < bbox_count[i]; ++j) { auto& text = texts[offset + j]; std::vector score(text.score, text.score + text.length); INFO("image {}, text = {}, score = {}", i, text.text, score); } offset += bbox_count[i]; } mmdeploy_text_recognizer_release_result(texts, offset); mmdeploy_text_detector_release_result(bboxes, bbox_count, offset); mmdeploy_text_recognizer_destroy(recognizer); mmdeploy_text_detector_destroy(detector); }; auto& gResources = MMDeployTestResources::Get(); auto img_list = gResources.LocateImageResources("mmocr/images"); REQUIRE(!img_list.empty()); for (auto& backend : gResources.backends()) { DYNAMIC_SECTION("loop backend: " << backend) { auto det_model_list = gResources.LocateModelResources("/mmocr/textdet/" + backend); auto reg_model_list = gResources.LocateModelResources("/mmocr/textreg/" + backend); REQUIRE(!det_model_list.empty()); REQUIRE(!reg_model_list.empty()); auto det_model_path = det_model_list.front(); auto reg_model_path = reg_model_list.front(); for (auto& device_name : gResources.device_names(backend)) { test(device_name, det_model_path, reg_model_path, img_list); } } } }