80 lines
3.5 KiB
C#
80 lines
3.5 KiB
C#
// Copyright (c) 2023 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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using System;
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using System.IO;
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using System.Runtime.InteropServices;
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using OpenCvSharp;
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using fastdeploy;
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namespace Test
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{
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public class TestPPOCRv3
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{
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public static void Main(string[] args)
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{
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if (args.Length < 6) {
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Console.WriteLine(
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"Usage: infer_demo path/to/det_model path/to/cls_model " +
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"path/to/rec_model path/to/rec_label_file path/to/image " +
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"run_option, " +
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"e.g ./infer_demo ./ch_PP-OCRv2_det_infer " +
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"./ch_ppocr_mobile_v2.0_cls_infer ./ch_PP-OCRv2_rec_infer " +
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"./ppocr_keys_v1.txt ./12.jpg 0"
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);
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Console.WriteLine( "The data type of run_option is int, 0: run with cpu; 1: run with gpu");
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return;
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}
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string det_model_dir = args[0];
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string cls_model_dir = args[1];
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string rec_model_dir = args[2];
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string rec_label_file = args[3];
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string image_path = args[4];
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RuntimeOption runtimeoption = new RuntimeOption();
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int device_option = Int32.Parse(args[5]);
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if(device_option==0){
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runtimeoption.UseCpu();
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}else{
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runtimeoption.UseGpu();
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}
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string sep = "\\";
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string det_model_file = det_model_dir + sep + "inference.pdmodel";
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string det_params_file = det_model_dir + sep + "inference.pdiparams";
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string cls_model_file = cls_model_dir + sep + "inference.pdmodel";
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string cls_params_file = cls_model_dir + sep + "inference.pdiparams";
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string rec_model_file = rec_model_dir + sep + "inference.pdmodel";
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string rec_params_file = rec_model_dir + sep + "inference.pdiparams";
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fastdeploy.vision.ocr.DBDetector dbdetector = new fastdeploy.vision.ocr.DBDetector(det_model_file, det_params_file, runtimeoption, ModelFormat.PADDLE);
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fastdeploy.vision.ocr.Classifier classifier = new fastdeploy.vision.ocr.Classifier(cls_model_file, cls_params_file, runtimeoption, ModelFormat.PADDLE);
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fastdeploy.vision.ocr.Recognizer recognizer = new fastdeploy.vision.ocr.Recognizer(rec_model_file, rec_params_file, rec_label_file, runtimeoption, ModelFormat.PADDLE);
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fastdeploy.pipeline.PPOCRv3 model = new fastdeploy.pipeline.PPOCRv3(dbdetector, classifier, recognizer);
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if(!model.Initialized()){
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Console.WriteLine("Failed to initialize.\n");
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}
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Mat image = Cv2.ImRead(image_path);
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fastdeploy.vision.OCRResult res = model.Predict(image);
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Console.WriteLine(res.ToString());
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Mat res_img = fastdeploy.vision.Visualize.VisOcr(image, res);
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Cv2.ImShow("result.png", res_img);
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Cv2.ImWrite("result.png", res_img);
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Cv2.WaitKey(0);
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}
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}
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}
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