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71 lines
2.0 KiB
71 lines
2.0 KiB
5 years ago
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// Copyright (c) 2020 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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#pragma once
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#include "opencv2/core.hpp"
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#include "opencv2/imgcodecs.hpp"
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#include "opencv2/imgproc.hpp"
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#include "paddle_api.h"
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#include "paddle_inference_api.h"
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#include <chrono>
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#include <iomanip>
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#include <iostream>
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#include <ostream>
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#include <vector>
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#include <cstring>
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#include <fstream>
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#include <numeric>
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#include <include/postprocess_op.h>
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#include <include/preprocess_op.h>
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namespace PaddleOCR {
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class DBDetector {
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public:
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explicit DBDetector(const std::string &model_dir, bool use_gpu = false,
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const int gpu_id = 0, const int max_side_len = 960) {
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LoadModel(model_dir, use_gpu);
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this->max_side_len_ = max_side_len;
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}
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// Load Paddle inference model
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void LoadModel(const std::string &model_dir, bool use_gpu,
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const int min_subgraph_size = 3, const int batch_size = 1,
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const int gpu_id = 0);
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// Run predictor
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void Run(cv::Mat &img, std::vector<std::vector<std::vector<int>>> &boxes);
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private:
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std::shared_ptr<PaddlePredictor> predictor_;
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int max_side_len_ = 960;
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std::vector<float> mean_ = {0.485f, 0.456f, 0.406f};
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std::vector<float> scale_ = {1 / 0.229f, 1 / 0.224f, 1 / 0.225f};
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bool is_scale_ = true;
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// pre-process
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ResizeImgType0 resize_op_;
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Normalize normalize_op_;
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Permute permute_op_;
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// post-process
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PostProcessor post_processor_;
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};
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} // namespace PaddleOCR
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