// 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 "preprocess_op.h"
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#include "utility.h"
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using namespace paddle_infer;
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namespace PaddleOCR {
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class Classifier {
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public:
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explicit Classifier(const std::string &model_dir) {
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LoadModel(model_dir);
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}
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double cls_thresh = 0.9;
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// Load Paddle inference model
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void LoadModel(const std::string &model_dir);
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void Run(std::vector<cv::Mat> img_list, std::vector<int> &cls_labels,
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std::vector<float> &cls_scores, std::vector<double> ×);
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private:
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std::shared_ptr<Predictor> predictor_;
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bool use_gpu_ = true;
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int gpu_id_ = 0;
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int gpu_mem_ = 4000;
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int cpu_math_library_num_threads_ = 4;
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bool use_mkldnn_ = false;
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std::vector<float> mean_ = {0.5f, 0.5f, 0.5f};
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std::vector<float> scale_ = {1 / 0.5f, 1 / 0.5f, 1 / 0.5f};
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bool is_scale_ = true;
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bool use_tensorrt_ = false;
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std::string precision_ = "fp32";
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int cls_batch_num_ = 1;
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// pre-process
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ClsResizeImg resize_op_;
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Normalize normalize_op_;
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PermuteBatch permute_op_;
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}; // class Classifier
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} // namespace PaddleOCR
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