public class ImageInfo
{
    public Mat Image { set; get; }
    public int ImageGroupId { set; get; }
    public int ImageId { set; get; }
}

public IList<ImageInfo> ReadTrainingImages(string path, string ext)
{
    var images = new List<ImageInfo>();
 
    var imageId = 1;
    foreach (var dir in new DirectoryInfo(path).GetDirectories())
    {
        var groupId = int.Parse(dir.Name);
        foreach (var imageFile in dir.GetFiles(ext))
        {
            var image = processTrainingImage(new Mat(imageFile.FullName, LoadMode.GrayScale));
            if (image == null)
            {
                continue;
            }
 
            images.Add(new ImageInfo
            {
                Image = image,
                ImageId = imageId++,
                ImageGroupId = groupId
            });
        }
    }
 
    return images;
}

private static Mat processTrainingImage(Mat gray)
{
    var threshImage = new Mat();
    Cv2.Threshold(gray, threshImage, Thresh, ThresholdMaxVal, ThresholdType.BinaryInv); // Threshold to find contour
 
    Point[][] contours;
    HiearchyIndex[] hierarchyIndexes;
    Cv2.FindContours(
        threshImage,
        out contours,
        out hierarchyIndexes,
        mode: ContourRetrieval.CComp,
        method: ContourChain.ApproxSimple);
 
    if (contours.Length == 0)
    {
        return null;
    }
 
    Mat result = null;
 
    var contourIndex = 0;
    while ((contourIndex >= 0))
    {
        var contour = contours[contourIndex];
 
        var boundingRect = Cv2.BoundingRect(contour); //Find bounding rect for each contour
        var roi = new Mat(threshImage, boundingRect); //Crop the image
 
        //Cv2.ImShow("src", gray);
        //Cv2.ImShow("roi", roi);
        //Cv.WaitKey(0);
 
        var resizedImage = new Mat();
        var resizedImageFloat = new Mat();
        Cv2.Resize(roi, resizedImage, new Size(10, 10)); //resize to 10X10
        resizedImage.ConvertTo(resizedImageFloat, MatType.CV_32FC1); //convert to float
        result = resizedImageFloat.Reshape(1, 1);
 
        contourIndex = hierarchyIndexes[contourIndex].Next;
    }
 
    return result;
}

public CvKNearest TrainData(IList<ImageInfo> trainingImages)
{
    var samples = new Mat();
    foreach (var trainingImage in trainingImages)
    {
        samples.PushBack(trainingImage.Image);
    }
 
    var labels = trainingImages.Select(x => x.ImageGroupId).ToArray();
    var responses = new Mat(labels.Length, 1, MatType.CV_32SC1, labels);
    var tmp = responses.Reshape(1, 1); //make continuous
    var responseFloat = new Mat();
    tmp.ConvertTo(responseFloat, MatType.CV_32FC1); // Convert  to float
 
 
    var kNearest = new CvKNearest();
    kNearest.Train(samples, responseFloat); // Train with sample and responses
    return kNearest;
}

public void DoOCR(CvKNearest kNearest, string path)
{
    var src = Cv2.ImRead(path);
    Cv2.ImShow("Source", src);
 
    var gray = new Mat();
    Cv2.CvtColor(src, gray, ColorConversion.BgrToGray);
 
    var threshImage = new Mat();
    Cv2.Threshold(gray, threshImage, Thresh, ThresholdMaxVal, ThresholdType.BinaryInv); // Threshold to find contour
 
 
    Point[][] contours;
    HiearchyIndex[] hierarchyIndexes;
    Cv2.FindContours(
        threshImage,
        out contours,
        out hierarchyIndexes,
        mode: ContourRetrieval.CComp,
        method: ContourChain.ApproxSimple);
 
    if (contours.Length == 0)
    {
        throw new NotSupportedException("Couldn't find any object in the image.");
    }
 
    //Create input sample by contour finding and cropping
    var dst = new Mat(src.Rows, src.Cols, MatType.CV_8UC3, Scalar.All(0));
 
    var contourIndex = 0;
    while ((contourIndex >= 0))
    {
        var contour = contours[contourIndex];
 
        var boundingRect = Cv2.BoundingRect(contour); //Find bounding rect for each contour
 
        Cv2.Rectangle(src,
            new Point(boundingRect.X, boundingRect.Y),
            new Point(boundingRect.X + boundingRect.Width, boundingRect.Y + boundingRect.Height),
            new Scalar(0, 0, 255),
            2);
 
        var roi = new Mat(threshImage, boundingRect); //Crop the image
 
        var resizedImage = new Mat();
        var resizedImageFloat = new Mat();
        Cv2.Resize(roi, resizedImage, new Size(10, 10)); //resize to 10X10
        resizedImage.ConvertTo(resizedImageFloat, MatType.CV_32FC1); //convert to float
        var result = resizedImageFloat.Reshape(1, 1);
 
 
        var results = new Mat();
        var neighborResponses = new Mat();
        var dists = new Mat();
        var detectedClass = (int)kNearest.FindNearest(result, 1, results, neighborResponses, dists);
 
        //Console.WriteLine("DetectedClass: {0}", detectedClass);
        //Cv2.ImShow("roi", roi);
        //Cv.WaitKey(0);
 
        //Cv2.ImWrite(string.Format("det_{0}_{1}.png",detectedClass, contourIndex), roi);
 
        Cv2.PutText(
            dst,
            detectedClass.ToString(CultureInfo.InvariantCulture),
            new Point(boundingRect.X, boundingRect.Y + boundingRect.Height),
            0,
            1,
            new Scalar(0, 255, 0),
            2);
 
        contourIndex = hierarchyIndexes[contourIndex].Next;
    }
 
    Cv2.ImShow("Segmented Source", src);
    Cv2.ImShow("Detected", dst);
 
    Cv2.ImWrite("dest.jpg", dst);
 
    Cv2.WaitKey();
}

> dotnet new react

spa.UseReactDevelopmentServer(npmScript: "start");

spa.UseProxyToSpaDevelopmentServer("http://localhost:3000");

> create-react-app clientapp

> cd clientapp
> npm install --save bootstrap axios

 import "bootstrap/dist/css/bootstrap.css";

using Microsoft.AspNetCore.Mvc;

namespace DownloadFilesSample.Controllers
{
    [Route("api/[controller]")]
    public class ReportsController : Controller
    {
        [HttpGet("[action]")]
        public IActionResult GetPdfReport()
        {
            return File(virtualPath: "~/app_data/sample.pdf",
                        contentType: "application/pdf",
                        fileDownloadName: "sample.pdf");
        }
    }
}

  const getResults = async () => {
      const { headers, data } = await axios.get(apiUrl, {
        responseType: "blob"
      });
  }

import axios from "axios";
import React, { useEffect, useState } from "react";

export default function DisplayPdf() {
  const apiUrl = "https://localhost:5001/api/Reports/GetPdfReport";

  const [blobInfo, setBlobInfo] = useState({
    blobUrl: "",
    fileName: ""
  });

  useEffect(() => {
    getResults();
  }, []);

  const getResults = async () => {
    try {
      const { headers, data } = await axios.get(apiUrl, {
        responseType: "blob"
      });
      console.log("headers", headers);

      const pdfBlobUrl = window.URL.createObjectURL(data);
      console.log("pdfBlobUrl", pdfBlobUrl);

      const fileName = headers["content-disposition"]
        .split(";")
        .find(n => n.includes("filename="))
        .replace("filename=", "")
        .trim();
      console.log("filename", fileName);

      setBlobInfo({
        blobUrl: pdfBlobUrl,
        fileName: fileName
      });
    } catch (error) {
      console.log(error);
    }
  };

ontent-disposition: "attachment; filename=sample.pdf; filename*=UTF-8''sample.pdf"

import axios from "axios";
import React, { useEffect, useState } from "react";

export default function DisplayPdf() {

  // ...

  const { blobUrl } = blobInfo;

  return (
    <>
      <h1>Display PDF Files</h1>
      <button className="btn btn-info" onClick={handlePrintPdf}>
        Print PDF
      </button>
      <button className="btn btn-primary ml-2" onClick={handleShowPdfInNewTab}>
        Show PDF in a new tab
      </button>
      <button className="btn btn-success ml-2" onClick={handleDownloadPdf}>
        Download PDF
      </button>

      <section className="card mb-5 mt-3">
        <div className="card-header">
          <h4>using iframe</h4>
        </div>
        <div className="card-body">
          <iframe
            title="PDF Report"
            width="100%"
            height="600"
            src={blobUrl}
            type="application/pdf"
          ></iframe>
        </div>
      </section>

      <section className="card mb-5">
        <div className="card-header">
          <h4>using object</h4>
        </div>
        <div className="card-body">
          <object
            data={blobUrl}
            aria-label="PDF Report"
            type="application/pdf"
            width="100%"
            height="100%"
          ></object>
        </div>
      </section>

      <section className="card mb-5">
        <div className="card-header">
          <h4>using embed</h4>
        </div>
        <div className="card-body">
          <embed
            aria-label="PDF Report"
            src={blobUrl}
            type="application/pdf"
            width="100%"
            height="100%"
          ></embed>
        </div>
      </section>
    </>
  );
}

  const handlePrintPdf = () => {
    const { blobUrl } = blobInfo;
    if (!blobUrl) {
      throw new Error("pdfBlobUrl is null");
    }

    const iframe = document.createElement("iframe");
    iframe.style.display = "none";
    iframe.src = blobUrl;
    document.body.appendChild(iframe);
    if (iframe.contentWindow) {
      iframe.contentWindow.print();
    }
  };

const handleShowPdfInNewTab = () => {
    const { blobUrl } = blobInfo;
    if (!blobUrl) {
      throw new Error("pdfBlobUrl is null");
    }

    window.open(blobUrl);
  };

  const handleDownloadPdf = () => {
    const { blobUrl, fileName } = blobInfo;
    if (!blobUrl) {
      throw new Error("pdfBlobUrl is null");
    }

    const anchor = document.createElement("a");
    anchor.style.display = "none";
    anchor.href = blobUrl;
    anchor.download = fileName;
    document.body.appendChild(anchor);
    anchor.click();
  };