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130 lines
4.6 KiB
130 lines
4.6 KiB
// 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 <include/utility.h>
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namespace PaddleOCR {
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class DBPostProcessor {
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public:
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void GetContourArea(const std::vector<std::vector<float>> &box,
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float unclip_ratio, float &distance) noexcept;
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cv::RotatedRect UnClip(const std::vector<std::vector<float>> &box,
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const float &unclip_ratio) noexcept;
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float **Mat2Vec(const cv::Mat &mat) noexcept;
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std::vector<std::vector<int>>
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OrderPointsClockwise(const std::vector<std::vector<int>> &pts) noexcept;
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std::vector<std::vector<float>> GetMiniBoxes(const cv::RotatedRect &box,
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float &ssid) noexcept;
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float BoxScoreFast(const std::vector<std::vector<float>> &box_array,
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const cv::Mat &pred) noexcept;
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float PolygonScoreAcc(const std::vector<cv::Point> &contour,
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const cv::Mat &pred) noexcept;
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std::vector<std::vector<std::vector<int>>>
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BoxesFromBitmap(const cv::Mat &pred, const cv::Mat &bitmap,
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const float &box_thresh, const float &det_db_unclip_ratio,
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const std::string &det_db_score_mode) noexcept;
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void FilterTagDetRes(std::vector<std::vector<std::vector<int>>> &boxes,
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float ratio_h, float ratio_w,
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const cv::Mat &srcimg) noexcept;
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private:
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static bool XsortInt(const std::vector<int> &a,
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const std::vector<int> &b) noexcept;
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static bool XsortFp32(const std::vector<float> &a,
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const std::vector<float> &b) noexcept;
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std::vector<std::vector<float>> Mat2Vector(const cv::Mat &mat) noexcept;
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inline int _max(int a, int b) const noexcept { return a >= b ? a : b; }
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inline int _min(int a, int b) const noexcept { return a >= b ? b : a; }
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template <class T> inline T clamp(T x, T min, T max) const noexcept {
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if (x > max)
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return max;
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if (x < min)
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return min;
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return x;
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}
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inline float clampf(float x, float min, float max) const noexcept {
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if (x > max)
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return max;
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if (x < min)
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return min;
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return x;
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}
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};
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class TablePostProcessor {
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public:
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void init(const std::string &label_path,
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bool merge_no_span_structure = true) noexcept;
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void Run(const std::vector<float> &loc_preds,
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const std::vector<float> &structure_probs,
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std::vector<float> &rec_scores,
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const std::vector<int> &loc_preds_shape,
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const std::vector<int> &structure_probs_shape,
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std::vector<std::vector<std::string>> &rec_html_tag_batch,
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std::vector<std::vector<std::vector<int>>> &rec_boxes_batch,
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const std::vector<int> &width_list,
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const std::vector<int> &height_list) noexcept;
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private:
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std::vector<std::string> label_list_;
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const std::string end = "eos";
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const std::string beg = "sos";
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};
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class PicodetPostProcessor {
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public:
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void init(const std::string &label_path, const double score_threshold = 0.4,
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const double nms_threshold = 0.5,
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const std::vector<int> &fpn_stride = {8, 16, 32, 64}) noexcept;
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void Run(std::vector<StructurePredictResult> &results,
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const std::vector<std::vector<float>> &outs,
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const std::vector<int> &ori_shape,
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const std::vector<int> &resize_shape, int eg_max) noexcept;
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inline size_t fpn_stride_size() const noexcept { return fpn_stride_.size(); }
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private:
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StructurePredictResult disPred2Bbox(const std::vector<float> &bbox_pred,
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int label, float score, int x, int y,
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int stride,
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const std::vector<int> &im_shape,
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int reg_max) noexcept;
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void nms(std::vector<StructurePredictResult> &input_boxes,
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float nms_threshold) noexcept;
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std::vector<int> fpn_stride_ = {8, 16, 32, 64};
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std::vector<std::string> label_list_;
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double score_threshold_ = 0.4;
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double nms_threshold_ = 0.5;
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int num_class_ = 5;
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};
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} // namespace PaddleOCR
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