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infer.cc
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "fastdeploy/vision.h"
#ifdef WIN32
const char sep = '\\';
#else
const char sep = '/';
#endif
void InitAndInfer(const std::string& det_model_dir, const std::string& cls_model_dir, const std::string& rec_model_dir, const std::string& rec_label_file, const std::string& image_file, const fastdeploy::RuntimeOption& option) {
auto det_model_file = det_model_dir + sep + "inference.pdmodel";
auto det_params_file = det_model_dir + sep + "inference.pdiparams";
auto cls_model_file = cls_model_dir + sep + "inference.pdmodel";
auto cls_params_file = cls_model_dir + sep + "inference.pdiparams";
auto rec_model_file = rec_model_dir + sep + "inference.pdmodel";
auto rec_params_file = rec_model_dir + sep + "inference.pdiparams";
auto det_option = option;
auto cls_option = option;
auto rec_option = option;
// If use TRT backend, the dynamic shape will be set as follow.
det_option.SetTrtInputShape("x", {1, 3, 50, 50}, {1, 3, 640, 640},
{1, 3, 1536, 1536});
cls_option.SetTrtInputShape("x", {1, 3, 48, 10}, {1, 3, 48, 320}, {1, 3, 48, 1024});
rec_option.SetTrtInputShape("x", {1, 3, 48, 10}, {1, 3, 48, 320},
{1, 3, 48, 2304});
// Users could save TRT cache file to disk as follow.
// det_option.SetTrtCacheFile(det_model_dir + sep + "det_trt_cache.trt");
// cls_option.SetTrtCacheFile(cls_model_dir + sep + "cls_trt_cache.trt");
// rec_option.SetTrtCacheFile(rec_model_dir + sep + "rec_trt_cache.trt");
auto det_model = fastdeploy::vision::ocr::DBDetector(det_model_file, det_params_file, det_option);
auto cls_model = fastdeploy::vision::ocr::Classifier(cls_model_file, cls_params_file, cls_option);
auto rec_model = fastdeploy::vision::ocr::Recognizer(rec_model_file, rec_params_file, rec_label_file, rec_option);
assert(det_model.Initialized());
assert(cls_model.Initialized());
assert(rec_model.Initialized());
// The classification model is optional, so the PP-OCR can also be connected in series as follows
// auto ppocr_v3 = fastdeploy::pipeline::PPOCRv3(&det_model, &rec_model);
auto ppocr_v3 = fastdeploy::pipeline::PPOCRv3(&det_model, &cls_model, &rec_model);
if(!ppocr_v3.Initialized()){
std::cerr << "Failed to initialize PP-OCR." << std::endl;
return;
}
auto im = cv::imread(image_file);
auto im_bak = im.clone();
fastdeploy::vision::OCRResult result;
if (!ppocr_v3.Predict(&im, &result)) {
std::cerr << "Failed to predict." << std::endl;
return;
}
std::cout << result.Str() << std::endl;
auto vis_im = fastdeploy::vision::VisOcr(im_bak, result);
cv::imwrite("vis_result.jpg", vis_im);
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
}
int main(int argc, char* argv[]) {
if (argc < 7) {
std::cout << "Usage: infer_demo path/to/det_model path/to/cls_model "
"path/to/rec_model path/to/rec_label_file path/to/image "
"run_option, "
"e.g ./infer_demo ./ch_PP-OCRv3_det_infer "
"./ch_ppocr_mobile_v2.0_cls_infer ./ch_PP-OCRv3_rec_infer "
"./ppocr_keys_v1.txt ./12.jpg 0"
<< std::endl;
std::cout << "The data type of run_option is int, 0: run with cpu; 1: run "
"with gpu; 2: run with gpu and use tensorrt backend."
<< std::endl;
return -1;
}
fastdeploy::RuntimeOption option;
int flag = std::atoi(argv[6]);
if (flag == 0) {
option.UseCpu();
} else if (flag == 1) {
option.UseGpu();
} else if (flag == 2) {
option.UseGpu();
option.UseTrtBackend();
}
std::string det_model_dir = argv[1];
std::string cls_model_dir = argv[2];
std::string rec_model_dir = argv[3];
std::string rec_label_file = argv[4];
std::string test_image = argv[5];
InitAndInfer(det_model_dir, cls_model_dir, rec_model_dir, rec_label_file, test_image, option);
return 0;
}