目录效果模型信息项目代码下载参考效果模型信息Model Properties----------------------------------------------------------------------------------------Inputs-------------------------namepixel_valuestensorFloat[-1, 3, -1, -1]---------------------------------------------------------------Outputs-------------------------namereconstructiontensorFloat[-1, 3, -1, -1]---------------------------------------------------------------项目代码using Microsoft.ML.OnnxRuntime;using Microsoft.ML.OnnxRuntime.Tensors;using OpenCvSharp;using System;using System.Collections.Generic;using System.Drawing;using System.Drawing.Imaging;using System.Linq;using System.Windows.Forms;namespace Onnx_Demo{public partial class Form1 : Form{public Form1(){InitializeComponent();}string fileFilter *.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png;string image_path ;string startupPath;DateTime dt1 DateTime.Now;DateTime dt2 DateTime.Now;string model_path;Mat image; // 原始图像BGRMat result_image; // 超分结果BGRSessionOptions options;InferenceSession onnx_session;Tensorfloat input_tensor;ListNamedOnnxValue input_container;IDisposableReadOnlyCollectionDisposableNamedOnnxValue result_infer;DisposableNamedOnnxValue[] results_onnxvalue;Tensorfloat result_tensor;private void button1_Click(object sender, EventArgs e){OpenFileDialog ofd new OpenFileDialog();ofd.Filter fileFilter;if (ofd.ShowDialog() ! DialogResult.OK) return;pictureBox1.Image null;image_path ofd.FileName;pictureBox1.Image new Bitmap(image_path);textBox1.Text ;image new Mat(image_path);pictureBox2.Image null;}private void button2_Click(object sender, EventArgs e){if (image_path ){return;}button2.Enabled false;pictureBox2.Image null;textBox1.Text ;Application.DoEvents();// 读取原始图像BGRimage new Mat(image_path);int originalWidth image.Cols;int originalHeight image.Rows;// ------------------ 预处理 ------------------// 1. 转换为RGBMat rgb new Mat();Cv2.CvtColor(image, rgb, ColorConversionCodes.BGR2RGB);// 2. 调整尺寸使宽高均为4的倍数APISR要求输入能被4整除int padHeight (int)Math.Ceiling((double)rgb.Height / 4) * 4;int padWidth (int)Math.Ceiling((double)rgb.Width / 4) * 4;Mat padded new Mat();Cv2.CopyMakeBorder(rgb, padded, 0, padHeight - rgb.Height, 0, padWidth - rgb.Width, BorderTypes.Constant, new Scalar(0, 0, 0));// 3. 归一化到 [0,1] 并转换为浮点padded.ConvertTo(padded, MatType.CV_32FC3, 1.0 / 255.0);// 4. 构建 CHW 张量int height padded.Height;int width padded.Width;Mat[] channels Cv2.Split(padded); // 顺序R, G, BListfloat dataList new Listfloat();for (int c 0; c 3; c){float[] channelData new float[height * width];System.Runtime.InteropServices.Marshal.Copy(channels[c].Data, channelData, 0, height * width);dataList.AddRange(channelData);}float[] inputData dataList.ToArray();input_tensor new DenseTensorfloat(inputData, new[] { 1, 3, height, width });// 输入容器清空并添加input_container.Clear();input_container.Add(NamedOnnxValue.CreateFromTensor(pixel_values, input_tensor)); // 修改输入名称// ------------------ 推理 ------------------dt1 DateTime.Now;result_infer onnx_session.Run(input_container);dt2 DateTime.Now;// 获取输出修改为 float 类型results_onnxvalue result_infer.ToArray();result_tensor results_onnxvalue[0].AsTensorfloat(); // 改为 floatint[] outShape result_tensor.Dimensions.ToArray();int outChannels outShape[1]; // 应为3int outHeight outShape[2];int outWidth outShape[3];float[] predFloat result_tensor.ToArray();// 创建 OpenCV Mat 存储输出图像RGB顺序Mat outputRgb new Mat(outHeight, outWidth, MatType.CV_32FC3);// 将 float 数组按 CHW 写入 Mat (OpenCV 是 HWC)int index 0;for (int h 0; h outHeight; h){for (int w 0; w outWidth; w){Vec3f pixel;pixel.Item0 predFloat[index]; // Rpixel.Item1 predFloat[index outHeight * outWidth]; // Gpixel.Item2 predFloat[index 2 * outHeight * outWidth]; // BoutputRgb.SetVec3f(h, w, pixel);index;}}// 将像素值从 [0,1] 转换到 [0,255] 并转为 8UC3outputRgb.ConvertTo(outputRgb, MatType.CV_8UC3, 255.0);// 裁剪掉之前填充的部分因为输出尺寸是填充后尺寸的4倍int cropHeight originalHeight * 4;int cropWidth originalWidth * 4;Rect roi new Rect(0, 0, cropWidth, cropHeight);Mat cropped new Mat(outputRgb, roi);// 将 RGB 转换为 BGR 以便 OpenCV 显示Mat resultBgr new Mat();Cv2.CvtColor(cropped, resultBgr, ColorConversionCodes.RGB2BGR);result_image resultBgr.Clone();// 显示结果pictureBox2.Image new Bitmap(result_image.ToMemoryStream());textBox1.Text $推理耗时:{(dt2 - dt1).TotalMilliseconds:F2}ms 输出尺寸:{cropWidth}x{cropHeight};button2.Enabled true;}private void Form1_Load(object sender, EventArgs e){startupPath System.Windows.Forms.Application.StartupPath;model_path model/4x_APISR_GRL_GAN_generator.onnx;// 创建会话使用 CPU可根据需要改为 CUDAoptions new SessionOptions();options.LogSeverityLevel OrtLoggingLevel.ORT_LOGGING_LEVEL_INFO;options.AppendExecutionProvider_CPU(0);// 如需 GPU取消下面注释并安装 Microsoft.ML.OnnxRuntime.Gpu// options.AppendExecutionProvider_CUDA(0);onnx_session new InferenceSession(model_path, options);input_container new ListNamedOnnxValue();// 测试图片路径可选image_path test_img/test01.png;if (System.IO.File.Exists(image_path)){pictureBox1.Image new Bitmap(image_path);image new Mat(image_path);}}private void pictureBox1_DoubleClick(object sender, EventArgs e){Common.ShowNormalImg(pictureBox1.Image);}private void pictureBox2_DoubleClick(object sender, EventArgs e){Common.ShowNormalImg(pictureBox2.Image);}SaveFileDialog sdf new SaveFileDialog();private void button3_Click(object sender, EventArgs e){if (result_image null || result_image.Empty()){MessageBox.Show(请先进行推理);return;}sdf.Title 保存超分图像;sdf.Filter PNG图片 (*.png)|*.png|JPEG图片 (*.jpg)|*.jpg|BMP图片 (*.bmp)|*.bmp;sdf.FilterIndex 1;if (sdf.ShowDialog() DialogResult.OK){string ext System.IO.Path.GetExtension(sdf.FileName).ToLower();ImageFormat format ImageFormat.Png;if (ext .jpg || ext .jpeg)format ImageFormat.Jpeg;else if (ext .bmp)format ImageFormat.Bmp;using (var stream result_image.ToMemoryStream())using (var bitmap new Bitmap(stream)){bitmap.Save(sdf.FileName, format);}MessageBox.Show(保存成功位置 sdf.FileName);}}}}using Microsoft.ML.OnnxRuntime; using Microsoft.ML.OnnxRuntime.Tensors; using OpenCvSharp; using System; using System.Collections.Generic; using System.Drawing; using System.Drawing.Imaging; using System.Linq; using System.Windows.Forms; namespace Onnx_Demo { public partial class Form1 : Form { public Form1() { InitializeComponent(); } string fileFilter *.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png; string image_path ; string startupPath; DateTime dt1 DateTime.Now; DateTime dt2 DateTime.Now; string model_path; Mat image; // 原始图像BGR Mat result_image; // 超分结果BGR SessionOptions options; InferenceSession onnx_session; Tensorfloat input_tensor; ListNamedOnnxValue input_container; IDisposableReadOnlyCollectionDisposableNamedOnnxValue result_infer; DisposableNamedOnnxValue[] results_onnxvalue; Tensorfloat result_tensor; private void button1_Click(object sender, EventArgs e) { OpenFileDialog ofd new OpenFileDialog(); ofd.Filter fileFilter; if (ofd.ShowDialog() ! DialogResult.OK) return; pictureBox1.Image null; image_path ofd.FileName; pictureBox1.Image new Bitmap(image_path); textBox1.Text ; image new Mat(image_path); pictureBox2.Image null; } private void button2_Click(object sender, EventArgs e) { if (image_path ) { return; } button2.Enabled false; pictureBox2.Image null; textBox1.Text ; Application.DoEvents(); // 读取原始图像BGR image new Mat(image_path); int originalWidth image.Cols; int originalHeight image.Rows; // ------------------ 预处理 ------------------ // 1. 转换为RGB Mat rgb new Mat(); Cv2.CvtColor(image, rgb, ColorConversionCodes.BGR2RGB); // 2. 调整尺寸使宽高均为4的倍数APISR要求输入能被4整除 int padHeight (int)Math.Ceiling((double)rgb.Height / 4) * 4; int padWidth (int)Math.Ceiling((double)rgb.Width / 4) * 4; Mat padded new Mat(); Cv2.CopyMakeBorder(rgb, padded, 0, padHeight - rgb.Height, 0, padWidth - rgb.Width, BorderTypes.Constant, new Scalar(0, 0, 0)); // 3. 归一化到 [0,1] 并转换为浮点 padded.ConvertTo(padded, MatType.CV_32FC3, 1.0 / 255.0); // 4. 构建 CHW 张量 int height padded.Height; int width padded.Width; Mat[] channels Cv2.Split(padded); // 顺序R, G, B Listfloat dataList new Listfloat(); for (int c 0; c 3; c) { float[] channelData new float[height * width]; System.Runtime.InteropServices.Marshal.Copy(channels[c].Data, channelData, 0, height * width); dataList.AddRange(channelData); } float[] inputData dataList.ToArray(); input_tensor new DenseTensorfloat(inputData, new[] { 1, 3, height, width }); // 输入容器清空并添加 input_container.Clear(); input_container.Add(NamedOnnxValue.CreateFromTensor(pixel_values, input_tensor)); // 修改输入名称 // ------------------ 推理 ------------------ dt1 DateTime.Now; result_infer onnx_session.Run(input_container); dt2 DateTime.Now; // 获取输出修改为 float 类型 results_onnxvalue result_infer.ToArray(); result_tensor results_onnxvalue[0].AsTensorfloat(); // 改为 float int[] outShape result_tensor.Dimensions.ToArray(); int outChannels outShape[1]; // 应为3 int outHeight outShape[2]; int outWidth outShape[3]; float[] predFloat result_tensor.ToArray(); // 创建 OpenCV Mat 存储输出图像RGB顺序 Mat outputRgb new Mat(outHeight, outWidth, MatType.CV_32FC3); // 将 float 数组按 CHW 写入 Mat (OpenCV 是 HWC) int index 0; for (int h 0; h outHeight; h) { for (int w 0; w outWidth; w) { Vec3f pixel; pixel.Item0 predFloat[index]; // R pixel.Item1 predFloat[index outHeight * outWidth]; // G pixel.Item2 predFloat[index 2 * outHeight * outWidth]; // B outputRgb.SetVec3f(h, w, pixel); index; } } // 将像素值从 [0,1] 转换到 [0,255] 并转为 8UC3 outputRgb.ConvertTo(outputRgb, MatType.CV_8UC3, 255.0); // 裁剪掉之前填充的部分因为输出尺寸是填充后尺寸的4倍 int cropHeight originalHeight * 4; int cropWidth originalWidth * 4; Rect roi new Rect(0, 0, cropWidth, cropHeight); Mat cropped new Mat(outputRgb, roi); // 将 RGB 转换为 BGR 以便 OpenCV 显示 Mat resultBgr new Mat(); Cv2.CvtColor(cropped, resultBgr, ColorConversionCodes.RGB2BGR); result_image resultBgr.Clone(); // 显示结果 pictureBox2.Image new Bitmap(result_image.ToMemoryStream()); textBox1.Text $推理耗时:{(dt2 - dt1).TotalMilliseconds:F2}ms 输出尺寸:{cropWidth}x{cropHeight}; button2.Enabled true; } private void Form1_Load(object sender, EventArgs e) { startupPath System.Windows.Forms.Application.StartupPath; model_path model/4x_APISR_GRL_GAN_generator.onnx; // 创建会话使用 CPU可根据需要改为 CUDA options new SessionOptions(); options.LogSeverityLevel OrtLoggingLevel.ORT_LOGGING_LEVEL_INFO; options.AppendExecutionProvider_CPU(0); // 如需 GPU取消下面注释并安装 Microsoft.ML.OnnxRuntime.Gpu // options.AppendExecutionProvider_CUDA(0); onnx_session new InferenceSession(model_path, options); input_container new ListNamedOnnxValue(); // 测试图片路径可选 image_path test_img/test01.png; if (System.IO.File.Exists(image_path)) { pictureBox1.Image new Bitmap(image_path); image new Mat(image_path); } } private void pictureBox1_DoubleClick(object sender, EventArgs e) { Common.ShowNormalImg(pictureBox1.Image); } private void pictureBox2_DoubleClick(object sender, EventArgs e) { Common.ShowNormalImg(pictureBox2.Image); } SaveFileDialog sdf new SaveFileDialog(); private void button3_Click(object sender, EventArgs e) { if (result_image null || result_image.Empty()) { MessageBox.Show(请先进行推理); return; } sdf.Title 保存超分图像; sdf.Filter PNG图片 (*.png)|*.png|JPEG图片 (*.jpg)|*.jpg|BMP图片 (*.bmp)|*.bmp; sdf.FilterIndex 1; if (sdf.ShowDialog() DialogResult.OK) { string ext System.IO.Path.GetExtension(sdf.FileName).ToLower(); ImageFormat format ImageFormat.Png; if (ext .jpg || ext .jpeg) format ImageFormat.Jpeg; else if (ext .bmp) format ImageFormat.Bmp; using (var stream result_image.ToMemoryStream()) using (var bitmap new Bitmap(stream)) { bitmap.Save(sdf.FileName, format); } MessageBox.Show(保存成功位置 sdf.FileName); } } } }下载源码下载参考https://github.com/Kiteretsu77/APISR