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a6c1d67584
* add c sharp apis for yolo serial models * fix * fix --------- Co-authored-by: heliqi <1101791222@qq.com>
58 lines
2.1 KiB
C#
58 lines
2.1 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 TestYOLOv5
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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 < 3) {
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Console.WriteLine(
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"Usage: infer_demo path/to/model path/to/image run_option, " +
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"e.g ./infer_model ./yolov5.onnx ./test.jpeg 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 model_path = args[0];
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string image_path = args[1];
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RuntimeOption runtimeoption = new RuntimeOption();
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int device_option = Int32.Parse(args[2]);
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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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fastdeploy.vision.detection.YOLOv5 model = new fastdeploy.vision.detection.YOLOv5(model_path, "", runtimeoption, ModelFormat.ONNX);
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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.DetectionResult res = model.Predict(image);
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Console.WriteLine(res.ToString());
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Mat res_img = fastdeploy.vision.Visualize.VisDetection(image, res, 0, 1, 0.5f);
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Cv2.ImShow("result.png", res_img);
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Cv2.WaitKey(0);
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}
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}
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} |