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MutiImageInfer.cs
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MutiImageInfer.cs
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/*******************************************************************************
*
*Copyright (c) 2016-2023, Mech-Mind Robotics
*All rights reserved.
*
*Redistribution and use in source and binary forms, with or without
*modification, are permitted provided that the following conditions are met:
*
*1. Redistributions of source code must retain the above copyright notice, this
* list of conditions and the following disclaimer.
*
*2. Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
*3. Neither the name of the copyright holder nor the names of its
* contributors may be used to endorse or promote products derived from
* this software without specific prior written permission.
*
*THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
*AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
*IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
*DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
*FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
*DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS
*SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
*CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
*OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
*OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
******************************************************************************/
/*
This sample demonstrates how to use the defect segmentation model exported from
Mech-DLK for inference of multiple images.
*/
using System;
using System.Collections.Generic;
using MMind.DL;
class MutiImageInfer
{
static void Main()
{
const string kPackPath = "./resources/DefectSegmentation/defect_segmentation_model.dlkpack";
const string kImagePath = "./resources/DefectSegmentation/defect_segmentation_image.jpg";
const string kImagePath2 = "./resources/DefectSegmentation/defect_segmentation_image_2.jpg";
const string kImagePath3 = "./resources/DefectSegmentation/defect_segmentation_image_3.jpg";
const string kImagePath4 = "./resources/DefectSegmentation/defect_segmentation_image_4.jpg";
const int kDiviceId = 0;
MMindImage[] images = new MMindImage[4] { new MMindImage(), new MMindImage(), new MMindImage(), new MMindImage() };
images[0].CreateFromPath(kImagePath);
images[1].CreateFromPath(kImagePath2);
images[2].CreateFromPath(kImagePath3);
images[3].CreateFromPath(kImagePath4);
List<MMindImage> imageList = new List<MMindImage>(images);
InferEngine inferEngine = new InferEngine();
inferEngine.Create(kPackPath, BackendType.GpuDefault, kDiviceId);
inferEngine.SetBatchSizeAndFloatPrecision(4, FloatPrecisionType.FP32, 0);
inferEngine.Infer(imageList);
List<Result> results;
inferEngine.GetResults(out results);
inferEngine.ResultVisualization(imageList);
imageList[0].Show("result");
imageList[1].Show("result");
imageList[2].Show("result");
imageList[3].Show("result");
inferEngine.Release();
}
}