PaddleOCR MCP Server

// Copyright (c) 2025 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. #pragma once #include <functional> #include <iostream> #include <string> #include <vector> #include "absl/status/status.h" #include "absl/status/statusor.h" #include "absl/types/optional.h" #include "src/base/base_pipeline.h" #include "src/common/image_batch_sampler.h" #include "src/common/processors.h" #include "src/modules/image_classification/predictor.h" #include "src/modules/text_detection/predictor.h" #include "src/modules/text_recognition/predictor.h" #include "src/pipelines/doc_preprocessor/pipeline.h" #include "src/utils/ilogger.h" #include "src/utils/utility.h" struct TextDetParams { int text_det_limit_side_len = -1; std::string text_det_limit_type = ""; int text_det_max_side_limit = -1; float text_det_thresh = -1; float text_det_box_thresh = -1; float text_det_unclip_ratio = -1; }; struct OCRPipelineResult { std::string input_path = ""; DocPreprocessorPipelineResult doc_preprocessor_res; std::vector<std::vector<cv::Point2f>> dt_polys = {}; std::unordered_map<std::string, bool> model_settings = {}; TextDetParams text_det_params; std::string text_type = ""; float text_rec_score_thresh = 0.0; std::vector<std::string> rec_texts = {}; std::vector<float> rec_scores = {}; std::vector<int> textline_orientation_angles = {}; std::vector<std::vector<cv::Point2f>> rec_polys = {}; std::vector<std::array<float, 4>> rec_boxes = {}; std::string vis_fonts = ""; }; struct OCRPipelineParams { absl::optional<std::string> doc_orientation_classify_model_name = absl::nullopt; absl::optional<std::string> doc_orientation_classify_model_dir = absl::nullopt; absl::optional<std::string> doc_unwarping_model_name = absl::nullopt; absl::optional<std::string> doc_unwarping_model_dir = absl::nullopt; absl::optional<std::string> text_detection_model_name = absl::nullopt; absl::optional<std::string> text_detection_model_dir = absl::nullopt; absl::optional<std::string> textline_orientation_model_name = absl::nullopt; absl::optional<std::string> textline_orientation_model_dir = absl::nullopt; absl::optional<int> textline_orientation_batch_size = absl::nullopt; absl::optional<std::string> text_recognition_model_name = absl::nullopt; absl::optional<std::string> text_recognition_model_dir = absl::nullopt; absl::optional<int> text_recognition_batch_size = absl::nullopt; absl::optional<bool> use_doc_orientation_classify = absl::nullopt; absl::optional<bool> use_doc_unwarping = absl::nullopt; absl::optional<bool> use_textline_orientation = absl::nullopt; absl::optional<int> text_det_limit_side_len = absl::nullopt; absl::optional<std::string> text_det_limit_type = absl::nullopt; absl::optional<float> text_det_thresh = absl::nullopt; absl::optional<float> text_det_box_thresh = absl::nullopt; absl::optional<float> text_det_unclip_ratio = absl::nullopt; absl::optional<std::vector<int>> text_det_input_shape = absl::nullopt; absl::optional<float> text_rec_score_thresh = absl::nullopt; absl::optional<std::vector<int>> text_rec_input_shape = absl::nullopt; absl::optional<std::string> lang = absl::nullopt; absl::optional<std::string> ocr_version = absl::nullopt; absl::optional<std::string> vis_font_dir = absl::nullopt; absl::optional<std::string> device = absl::nullopt; bool enable_mkldnn = true; int mkldnn_cache_capacity = 10; std::string precision = "fp32"; int cpu_threads = 8; int thread_num = 1; absl::optional<Utility::PaddleXConfigVariant> paddlex_config = absl::nullopt; }; class _OCRPipeline : public BasePipeline { public: explicit _OCRPipeline(const OCRPipelineParams &params); virtual ~_OCRPipeline() = default; _OCRPipeline() = delete; std::vector<std::unique_ptr<BaseCVResult>> Predict(const std::vector<std::string> &input) override; std::vector<OCRPipelineResult> PipelineResult() const { return pipeline_result_vec_; }; static absl::StatusOr<std::vector<cv::Mat>> RotateImage(const std::vector<cv::Mat> &image_array_list, const std::vector<int> &rotate_angle_list); std::unordered_map<std::string, bool> GetModelSettings() const; TextDetParams GetTextDetParams() const { return text_det_params_; }; void OverrideConfig(); private: OCRPipelineParams params_; YamlConfig config_; std::unique_ptr<BaseBatchSampler> batch_sampler_ptr_; std::vector<OCRPipelineResult> pipeline_result_vec_; bool use_doc_preprocessor_ = false; bool use_doc_orientation_classify_ = false; bool use_doc_unwarping_ = false; std::unique_ptr<BasePipeline> doc_preprocessors_pipeline_; bool use_textline_orientation_ = false; std::unique_ptr<BasePredictor> textline_orientation_model_; std::unique_ptr<BasePredictor> text_det_model_; std::unique_ptr<BasePredictor> text_rec_model_; std::unique_ptr<CropByPolys> crop_by_polys_; std::function<std::vector<std::vector<cv::Point2f>>( const std::vector<std::vector<cv::Point2f>> &)> sort_boxes_; float text_rec_score_thresh_ = 0.0; std::string text_type_; TextDetParams text_det_params_; }; class OCRPipeline : public AutoParallelSimpleInferencePipeline< _OCRPipeline, OCRPipelineParams, std::vector<std::string>, std::vector<std::unique_ptr<BaseCVResult>>> { public: OCRPipeline(const OCRPipelineParams &params) : AutoParallelSimpleInferencePipeline(params), thread_num_(params.thread_num) { if (thread_num_ == 1) { infer_ = std::unique_ptr<BasePipeline>(new _OCRPipeline(params)); } }; std::vector<std::unique_ptr<BaseCVResult>> Predict(const std::vector<std::string> &input) override; private: int thread_num_; std::unique_ptr<BasePipeline> infer_; std::unique_ptr<BaseBatchSampler> batch_sampler_ptr_; };