目錄

介紹

效果?

模型信息

項目

代碼

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LaMa Image Inpainting 圖像修復 Onnx Demo

介紹

gihub地址：https://github.com/advimman/lama

🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

效果?

模型信息

Model?Properties
-------------------------
---------------------------------------------------------------

Inputs
-------------------------
name：image
tensor：Float[1,?3,?1000,?1504]
name：mask
tensor：Float[1,?1,?1000,?1504]
---------------------------------------------------------------

Outputs
-------------------------
name：inpainted
tensor：Float[1,?1000,?1504,?3]
---------------------------------------------------------------

項目

代碼

using Microsoft.ML.OnnxRuntime;
using Microsoft.ML.OnnxRuntime.Tensors;
using OpenCvSharp;
using System;
using System.Collections.Generic;
using System.Drawing;
using System.Linq;
using System.Text;
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 image_path_mask = "";
? ? ? ? DateTime dt1 = DateTime.Now;
? ? ? ? DateTime dt2 = DateTime.Now;
? ? ? ? string model_path;
? ? ? ? Mat image;
? ? ? ? Mat image_mask;

? ? ? ? SessionOptions options;
? ? ? ? InferenceSession onnx_session;
? ? ? ? Tensor<float> input_tensor;
? ? ? ? Tensor<float> input_tensor_mask;
? ? ? ? List<NamedOnnxValue> input_container;
? ? ? ? IDisposableReadOnlyCollection<DisposableNamedOnnxValue> result_infer;

? ? ? ? StringBuilder sb = new StringBuilder();

? ? ? ? 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 = "";

? ? ? ? ? ? image = new Mat(image_path);
? ? ? ? ? ? int w = image.Width;
? ? ? ? ? ? int h = image.Height;
? ? ? ? ? ? image_mask = new Mat(image_path_mask);

? ? ? ? ? ? Common.Preprocess(image, image_mask, input_tensor, input_tensor_mask);

? ? ? ? ? ? //將 input_tensor 放入一個輸入參數的容器，并指定名稱
? ? ? ? ? ? input_container.Add(NamedOnnxValue.CreateFromTensor("image", input_tensor));

? ? ? ? ? ? //將 input_tensor_mask 放入一個輸入參數的容器，并指定名稱
? ? ? ? ? ? input_container.Add(NamedOnnxValue.CreateFromTensor("mask", input_tensor_mask));

? ? ? ? ? ? dt1 = DateTime.Now;
? ? ? ? ? ? //運行 Inference 并獲取結果
? ? ? ? ? ? result_infer = onnx_session.Run(input_container);
? ? ? ? ? ? dt2 = DateTime.Now;

? ? ? ? ? ? Mat result = Common.Postprocess(result_infer);

? ? ? ? ? ? Cv2.Resize(result, result, new OpenCvSharp.Size(w, h));

? ? ? ? ? ? sb.AppendLine("推理耗時:" + (dt2 - dt1).TotalMilliseconds + "ms");

? ? ? ? ? ? pictureBox2.Image = new Bitmap(result.ToMemoryStream());
? ? ? ? ? ? textBox1.Text = sb.ToString();

? ? ? ? ? ? button2.Enabled = true;
? ? ? ? }

? ? ? ? private void Form1_Load(object sender, EventArgs e)
? ? ? ? {
? ? ? ? ? ? model_path = "model/big_lama_regular_inpaint.onnx";

? ? ? ? ? ? // 創建輸出會話，用于輸出模型讀取信息
? ? ? ? ? ? options = new SessionOptions();
? ? ? ? ? ? options.LogSeverityLevel = OrtLoggingLevel.ORT_LOGGING_LEVEL_INFO;
? ? ? ? ? ? options.AppendExecutionProvider_CPU(0);// 設置為CPU上運行

? ? ? ? ? ? // 創建推理模型類，讀取本地模型文件
? ? ? ? ? ? onnx_session = new InferenceSession(model_path, options);//model_path 為onnx模型文件的路徑

? ? ? ? ? ? // 輸入Tensor
? ? ? ? ? ? input_tensor = new DenseTensor<float>(new[] { 1, 3, 1000, 1504 });

? ? ? ? ? ? input_tensor_mask = new DenseTensor<float>(new[] { 1, 1, 1000, 1504 });

? ? ? ? ? ? // 創建輸入容器
? ? ? ? ? ? input_container = new List<NamedOnnxValue>();

? ? ? ? ? ? image_path = "test_img/test.jpg";
? ? ? ? ? ? pictureBox1.Image = new Bitmap(image_path);

? ? ? ? ? ? image_path_mask = "test_img/mask.jpg";
? ? ? ? ? ? pictureBox3.Image = new Bitmap(image_path_mask);
? ? ? ? }
? ? }
}

using Microsoft.ML.OnnxRuntime;
using Microsoft.ML.OnnxRuntime.Tensors;
using OpenCvSharp;
using System;
using System.Collections.Generic;
using System.Drawing;
using System.Linq;
using System.Text;
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 image_path_mask = "";DateTime dt1 = DateTime.Now;DateTime dt2 = DateTime.Now;string model_path;Mat image;Mat image_mask;SessionOptions options;InferenceSession onnx_session;Tensor<float> input_tensor;Tensor<float> input_tensor_mask;List<NamedOnnxValue> input_container;IDisposableReadOnlyCollection<DisposableNamedOnnxValue> result_infer;StringBuilder sb = new StringBuilder();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 = "";image = new Mat(image_path);int w = image.Width;int h = image.Height;image_mask = new Mat(image_path_mask);Common.Preprocess(image, image_mask, input_tensor, input_tensor_mask);//將 input_tensor 放入一個輸入參數的容器，并指定名稱input_container.Add(NamedOnnxValue.CreateFromTensor("image", input_tensor));//將 input_tensor_mask 放入一個輸入參數的容器，并指定名稱input_container.Add(NamedOnnxValue.CreateFromTensor("mask", input_tensor_mask));dt1 = DateTime.Now;//運行 Inference 并獲取結果result_infer = onnx_session.Run(input_container);dt2 = DateTime.Now;Mat result = Common.Postprocess(result_infer);Cv2.Resize(result, result, new OpenCvSharp.Size(w, h));sb.AppendLine("推理耗時:" + (dt2 - dt1).TotalMilliseconds + "ms");pictureBox2.Image = new Bitmap(result.ToMemoryStream());textBox1.Text = sb.ToString();button2.Enabled = true;}private void Form1_Load(object sender, EventArgs e){model_path = "model/big_lama_regular_inpaint.onnx";// 創建輸出會話，用于輸出模型讀取信息options = new SessionOptions();options.LogSeverityLevel = OrtLoggingLevel.ORT_LOGGING_LEVEL_INFO;options.AppendExecutionProvider_CPU(0);// 設置為CPU上運行// 創建推理模型類，讀取本地模型文件onnx_session = new InferenceSession(model_path, options);//model_path 為onnx模型文件的路徑// 輸入Tensorinput_tensor = new DenseTensor<float>(new[] { 1, 3, 1000, 1504 });input_tensor_mask = new DenseTensor<float>(new[] { 1, 1, 1000, 1504 });// 創建輸入容器input_container = new List<NamedOnnxValue>();image_path = "test_img/test.jpg";pictureBox1.Image = new Bitmap(image_path);image_path_mask = "test_img/mask.jpg";pictureBox3.Image = new Bitmap(image_path_mask);}}
}

Common.cs

using Microsoft.ML.OnnxRuntime;
using Microsoft.ML.OnnxRuntime.Tensors;
using OpenCvSharp;
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;namespace Onnx_Demo
{internal class Common{public static void Preprocess(Mat image, Mat image_mask,  Tensor<float> input_tensor, Tensor<float> input_tensor_mask){Cv2.Resize(image, image, new OpenCvSharp.Size(1504, 1000));// 輸入Tensorfor (int y = 0; y < image.Height; y++){for (int x = 0; x < image.Width; x++){input_tensor[0, 0, y, x] = image.At<Vec3b>(y, x)[0] / 255.0f;input_tensor[0, 1, y, x] = image.At<Vec3b>(y, x)[1] / 255.0f;input_tensor[0, 2, y, x] = image.At<Vec3b>(y, x)[2] / 255.0f;}}Cv2.Resize(image_mask, image_mask, new OpenCvSharp.Size(1504, 1000));//膨脹核函數Mat element1 = new Mat();OpenCvSharp.Size size1 = new OpenCvSharp.Size(11, 11);element1 = Cv2.GetStructuringElement(MorphShapes.Rect, size1);//膨脹一次，讓輪廓突出Mat dilation = new Mat();Cv2.Dilate(image_mask, image_mask, element1);//輸入Tensorfor (int y = 0; y < image_mask.Height; y++){for (int x = 0; x < image_mask.Width; x++){float v = image_mask.At<Vec3b>(y, x)[0];if (v > 127){input_tensor_mask[0, 0, y, x] = 1.0f;}else{input_tensor_mask[0, 0, y, x] = 0.0f;}}}}public static Mat Postprocess(IDisposableReadOnlyCollection<DisposableNamedOnnxValue> result_infer){// 將輸出結果轉為DisposableNamedOnnxValue數組DisposableNamedOnnxValue[] results_onnxvalue = result_infer.ToArray();// 讀取第一個節點輸出并轉為Tensor數據Tensor<float> result_tensors = results_onnxvalue[0].AsTensor<float>();float[] result_array = result_tensors.ToArray();for (int i = 0; i < result_array.Length; i++){result_array[i] = Math.Max(0, Math.Min(255, result_array[i]));}Mat result = new Mat(1000, 1504, MatType.CV_32FC3, result_array);return result;}}
}

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