【转载】神奇的图像修复技术：C# LaMa Image Inpainting Demo，让你轻松移除万物！

效果

原项目

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

项目核心就是使用big_lama_regular_inpaint.onnx模型+mask.jpg从test.jpg中将人移除，是不是很神奇。

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]
---------------------------------------------------------------

项目源代码

using Microsoft.ML.OnnxRuntime;
using Microsoft.ML.OnnxRuntime.Tensors;
using OpenCvSharp;
using System;
using System.Collections.Generic;
using System.Drawing;
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);

            //将 input_tensor 放入一个输入参数的容器，并指定名称
            input_container.Add(NamedOnnxValue.CreateFromTensor("image", input_tensor));

            //将 input_tensor_mask 放入一个输入参数的容器，并指定名称
            input_container.Add(NamedOnnxValue.CreateFromTensor("mask", input_tensor_mask));

            dt1 = DateTime.Now;
            //运行 Inference 并获取结果
            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("推理耗时:" + (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";

            // 创建输出会话，用于输出模型读取信息
            options = new SessionOptions();
            options.LogSeverityLevel = OrtLoggingLevel.ORT_LOGGING_LEVEL_INFO;
            options.AppendExecutionProvider_CPU(0);// 设置为CPU上运行

            // 创建推理模型类，读取本地模型文件
            onnx_session = new InferenceSession(model_path, options);//model_path 为onnx模型文件的路径

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

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

            // 创建输入容器
            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);
        }
    }
}

From 公众号:天天代码码天天