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https://github.com/PaddlePaddle/FastDeploy.git
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f36f9324de
* Pick PPOCR fastdeploy docs from PaddleOCR * improve ppocr * improve readme * remove old PP-OCRv2 and PP-OCRv3 folfers * rename kunlun to kunlunxin * improve readme * improve readme * improve readme --------- Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
83 lines
2.7 KiB
C++
83 lines
2.7 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "fastdeploy/vision.h"
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#ifdef WIN32
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const char sep = '\\';
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#else
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const char sep = '/';
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#endif
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void InitAndInfer(const std::string &det_model_dir,
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const std::string &image_file,
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const fastdeploy::RuntimeOption &option) {
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auto det_model_file = det_model_dir + sep + "inference.pdmodel";
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auto det_params_file = det_model_dir + sep + "inference.pdiparams";
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auto det_option = option;
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auto det_model = fastdeploy::vision::ocr::DBDetector(
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det_model_file, det_params_file, det_option);
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assert(det_model.Initialized());
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// Parameters settings for pre and post processing of Det Model.
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det_model.GetPreprocessor().SetMaxSideLen(960);
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det_model.GetPostprocessor().SetDetDBThresh(0.3);
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det_model.GetPostprocessor().SetDetDBBoxThresh(0.6);
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det_model.GetPostprocessor().SetDetDBUnclipRatio(1.5);
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det_model.GetPostprocessor().SetDetDBScoreMode("slow");
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det_model.GetPostprocessor().SetUseDilation(0);
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auto im = cv::imread(image_file);
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auto im_bak = im.clone();
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fastdeploy::vision::OCRResult result;
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if (!det_model.Predict(im, &result)) {
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std::cerr << "Failed to predict." << std::endl;
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return;
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}
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std::cout << result.Str() << std::endl;
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auto vis_im = fastdeploy::vision::VisOcr(im_bak, result);
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cv::imwrite("vis_result.jpg", vis_im);
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std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
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}
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int main(int argc, char *argv[]) {
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if (argc < 4) {
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std::cout << "Usage: infer_demo path/to/det_model path/to/image "
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"run_option, "
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"e.g ./infer_demo ./ch_PP-OCRv3_det_infer ./12.jpg 0"
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<< std::endl;
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std::cout << "The data type of run_option is int, 0: run with cpu; 1: run "
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"with gpu;."
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<< std::endl;
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return -1;
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}
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fastdeploy::RuntimeOption option;
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int flag = std::atoi(argv[3]);
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if (flag == 0) {
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option.UseCpu();
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} else if (flag == 1) {
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option.UseGpu();
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}
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std::string det_model_dir = argv[1];
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std::string test_image = argv[2];
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InitAndInfer(det_model_dir, test_image, option);
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return 0;
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}
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