微软人脸识别SDK使用

JQuery Web

<!DOCTYPE html>
<html><head><title>Detect Faces Sample</title><!-- <script src="https://ajax.googleapis.com/ajax/libs/jquery/1.9.0/jquery.min.js"></script> -->
</head><body><h1>Detect Faces:</h1>Enter the URL to an image that includes a face or faces, then clickthe <strong>Analyze face</strong> button.<br><br><input type="file" id="localFile" name="localFile"/>Image to analyze: <input type="text" name="inputImage" id="inputImage"value="http://article-fd.zol-img.com.cn/t_s640x2000/g5/M00/08/07/ChMkJltn_xyIQOz4AABFFxqLxD4AAqcFgF5b28AAEUv569.jpg" /><button onclick="processImage()">Analyze face</button><br><br><div id="wrapper" style="width:1020px; display:table;"><div id="jsonOutput" style="width:600px; display:table-cell;">Response:<br><br><textarea id="responseTextArea" class="UIInput" style="width:580px; height:400px;"></textarea></div><div id="imageDiv" style="width:420px; display:table-cell;">Source image:<br><br><img id="sourceImage" width="400" /></div></div>
</body>
<script src="jquery-3.4.1.min.js"></script>
<script type="text/javascript">function processImage() {// Replace <Subscription Key> with your valid subscription key.var subscriptionKey = "******";var uriBase ="https://westcentralus.api.cognitive.microsoft.com/face/v1.0/detect";// Request parameters.var params = {"returnFaceId": "true","returnFaceLandmarks": "false","returnFaceAttributes": "age,gender,headPose,smile,facialHair,glasses,emotion," +"hair,makeup,occlusion,accessories,blur,exposure,noise"};// Display the image.var sourceImageUrl = document.getElementById("inputImage").value;document.querySelector("#sourceImage").src = sourceImageUrl;// Perform the REST API call.$.ajax({url: uriBase + "?" + $.param(params),// Request headers.beforeSend: function (xhrObj) {xhrObj.setRequestHeader("Content-Type", "application/json");xhrObj.setRequestHeader("Ocp-Apim-Subscription-Key", subscriptionKey);},type: "POST",// Request body.data: '{"url": ' + '"' + sourceImageUrl + '"}',}).done(function (data) {// Show formatted JSON on webpage.$("#responseTextArea").val(JSON.stringify(data, null, 2));}).fail(function (jqXHR, textStatus, errorThrown) {// Display error message.var errorString = (errorThrown === "") ?"Error. " : errorThrown + " (" + jqXHR.status + "): ";errorString += (jqXHR.responseText === "") ?"" : (jQuery.parseJSON(jqXHR.responseText).message) ?jQuery.parseJSON(jqXHR.responseText).message :jQuery.parseJSON(jqXHR.responseText).error.message;alert(errorString);});};
</script></html>

Node.js

'use strict';const request = require('request');// Replace <Subscription Key> with your valid subscription key.
const subscriptionKey = '*******';// You must use the same location in your REST call as you used to get your
// subscription keys. For example, if you got your subscription keys from
// westus, replace "westcentralus" in the URL below with "westus".
const uriBase = "https://westcentralus.api.cognitive.microsoft.com/face/v1.0/detect";const imageUrl ='https://upload.wikimedia.org/wikipedia/commons/3/37/Dagestani_man_and_woman.jpg';// Request parameters.
const params = {'returnFaceId': 'true','returnFaceLandmarks': 'false','returnFaceAttributes': 'age,gender,headPose,smile,facialHair,glasses,' +'emotion,hair,makeup,occlusion,accessories,blur,exposure,noise'
};const options = {uri: uriBase,qs: params,body: '{"url": ' + '"' + imageUrl + '"}',headers: {'Content-Type': 'application/json','Ocp-Apim-Subscription-Key' : subscriptionKey}
};request.post(options, (error, response, body) => {if (error) {console.log('Error: ', error);return;}let jsonResponse = JSON.stringify(JSON.parse(body), null, '  ');console.log('JSON Response\n');console.log(jsonResponse);
});

测试结果

C# WPF

MainWindow.xaml.cs

// <snippet_using>
using Microsoft.Azure.CognitiveServices.Vision.Face;
using Microsoft.Azure.CognitiveServices.Vision.Face.Models;using System;
using System.Collections.Generic;
using System.IO;
using System.Text;
using System.Threading.Tasks;
using System.Windows;
using System.Windows.Input;
using System.Windows.Media;
using System.Windows.Media.Imaging;
// </snippet_using>namespace FaceTutorial
{public partial class MainWindow : Window{// <snippet_mainwindow_fields>// Add your Face subscription key to your environment variables.private const string subscriptionKey = "690577240c594f1cae0b34018c15a207";// Environment.GetEnvironmentVariable("FACE_SUBSCRIPTION_KEY");// Add your Face endpoint to your environment variables.private const string faceEndpoint = "https://westcentralus.api.cognitive.microsoft.com/face";// Environment.GetEnvironmentVariable("FACE_ENDPOINT");private readonly IFaceClient faceClient = new FaceClient(new ApiKeyServiceClientCredentials(subscriptionKey),new System.Net.Http.DelegatingHandler[] { });// The list of detected faces.private IList<DetectedFace> faceList;// The list of descriptions for the detected faces.private string[] faceDescriptions;// The resize factor for the displayed image.private double resizeFactor;private const string defaultStatusBarText ="Place the mouse pointer over a face to see the face description.";// </snippet_mainwindow_fields>// <snippet_mainwindow_constructor>public MainWindow(){InitializeComponent();if (Uri.IsWellFormedUriString(faceEndpoint, UriKind.Absolute)){faceClient.Endpoint = faceEndpoint;}else{MessageBox.Show(faceEndpoint,"Invalid URI", MessageBoxButton.OK, MessageBoxImage.Error);Environment.Exit(0);}}// </snippet_mainwindow_constructor>// <snippet_browsebuttonclick_start>// Displays the image and calls UploadAndDetectFaces.private async void BrowseButton_Click(object sender, RoutedEventArgs e){// Get the image file to scan from the user.var openDlg = new Microsoft.Win32.OpenFileDialog();openDlg.Filter = "JPEG Image(*.jpg)|*.jpg";bool? result = openDlg.ShowDialog(this);// Return if canceled.if (!(bool)result){return;}// Display the image file.string filePath = openDlg.FileName;Uri fileUri = new Uri(filePath);BitmapImage bitmapSource = new BitmapImage();bitmapSource.BeginInit();bitmapSource.CacheOption = BitmapCacheOption.None;bitmapSource.UriSource = fileUri;bitmapSource.EndInit();FacePhoto.Source = bitmapSource;// </snippet_browsebuttonclick_start>// <snippet_browsebuttonclick_mid>// Detect any faces in the image.Title = "Detecting...";faceList = await UploadAndDetectFaces(filePath);Title = String.Format("Detection Finished. {0} face(s) detected", faceList.Count);if (faceList.Count > 0){// Prepare to draw rectangles around the faces.DrawingVisual visual = new DrawingVisual();DrawingContext drawingContext = visual.RenderOpen();drawingContext.DrawImage(bitmapSource,new Rect(0, 0, bitmapSource.Width, bitmapSource.Height));double dpi = bitmapSource.DpiX;// Some images don't contain dpi info.resizeFactor = (dpi == 0) ? 1 : 96 / dpi;faceDescriptions = new String[faceList.Count];for (int i = 0; i < faceList.Count; ++i){DetectedFace face = faceList[i];// Draw a rectangle on the face.drawingContext.DrawRectangle(Brushes.Transparent,new Pen(Brushes.Red, 2),new Rect(face.FaceRectangle.Left * resizeFactor,face.FaceRectangle.Top * resizeFactor,face.FaceRectangle.Width * resizeFactor,face.FaceRectangle.Height * resizeFactor));// Store the face description.faceDescriptions[i] = FaceDescription(face);}drawingContext.Close();// Display the image with the rectangle around the face.RenderTargetBitmap faceWithRectBitmap = new RenderTargetBitmap((int)(bitmapSource.PixelWidth * resizeFactor),(int)(bitmapSource.PixelHeight * resizeFactor),96,96,PixelFormats.Pbgra32);faceWithRectBitmap.Render(visual);FacePhoto.Source = faceWithRectBitmap;// Set the status bar text.faceDescriptionStatusBar.Text = defaultStatusBarText;}// </snippet_browsebuttonclick_mid>// <snippet_browsebuttonclick_end>}// </snippet_browsebuttonclick_end>// <snippet_mousemove_start>// Displays the face description when the mouse is over a face rectangle.private void FacePhoto_MouseMove(object sender, MouseEventArgs e){// </snippet_mousemove_start>// <snippet_mousemove_mid>// If the REST call has not completed, return.if (faceList == null)return;// Find the mouse position relative to the image.Point mouseXY = e.GetPosition(FacePhoto);ImageSource imageSource = FacePhoto.Source;BitmapSource bitmapSource = (BitmapSource)imageSource;// Scale adjustment between the actual size and displayed size.var scale = FacePhoto.ActualWidth / (bitmapSource.PixelWidth / resizeFactor);// Check if this mouse position is over a face rectangle.bool mouseOverFace = false;for (int i = 0; i < faceList.Count; ++i){FaceRectangle fr = faceList[i].FaceRectangle;double left = fr.Left * scale;double top = fr.Top * scale;double width = fr.Width * scale;double height = fr.Height * scale;// Display the face description if the mouse is over this face rectangle.if (mouseXY.X >= left && mouseXY.X <= left + width &&mouseXY.Y >= top && mouseXY.Y <= top + height){faceDescriptionStatusBar.Text = faceDescriptions[i];mouseOverFace = true;break;}}// String to display when the mouse is not over a face rectangle.if (!mouseOverFace) faceDescriptionStatusBar.Text = defaultStatusBarText;// </snippet_mousemove_mid>// <snippet_mousemove_end>}// </snippet_mousemove_end>// <snippet_uploaddetect>// Uploads the image file and calls DetectWithStreamAsync.private async Task<IList<DetectedFace>> UploadAndDetectFaces(string imageFilePath){// The list of Face attributes to return.IList<FaceAttributeType> faceAttributes =new FaceAttributeType[]{FaceAttributeType.Gender, FaceAttributeType.Age,FaceAttributeType.Smile, FaceAttributeType.Emotion,FaceAttributeType.Glasses, FaceAttributeType.Hair};// Call the Face API.try{using (Stream imageFileStream = File.OpenRead(imageFilePath)){// The second argument specifies to return the faceId, while// the third argument specifies not to return face landmarks.IList<DetectedFace> faceList =await faceClient.Face.DetectWithStreamAsync(imageFileStream, true, false, faceAttributes);return faceList;}}// Catch and display Face API errors.catch (APIErrorException f){MessageBox.Show(f.Message);return new List<DetectedFace>();}// Catch and display all other errors.catch (Exception e){MessageBox.Show(e.Message, "Error");return new List<DetectedFace>();}}// </snippet_uploaddetect>// <snippet_facedesc>// Creates a string out of the attributes describing the face.private string FaceDescription(DetectedFace face){StringBuilder sb = new StringBuilder();sb.Append("Face: ");// Add the gender, age, and smile.sb.Append(face.FaceAttributes.Gender);sb.Append(", ");sb.Append(face.FaceAttributes.Age);sb.Append(", ");sb.Append(String.Format("smile {0:F1}%, ", face.FaceAttributes.Smile * 100));// Add the emotions. Display all emotions over 10%.sb.Append("Emotion: ");Emotion emotionScores = face.FaceAttributes.Emotion;if (emotionScores.Anger >= 0.1f) sb.Append(String.Format("anger {0:F1}%, ", emotionScores.Anger * 100));if (emotionScores.Contempt >= 0.1f) sb.Append(String.Format("contempt {0:F1}%, ", emotionScores.Contempt * 100));if (emotionScores.Disgust >= 0.1f) sb.Append(String.Format("disgust {0:F1}%, ", emotionScores.Disgust * 100));if (emotionScores.Fear >= 0.1f) sb.Append(String.Format("fear {0:F1}%, ", emotionScores.Fear * 100));if (emotionScores.Happiness >= 0.1f) sb.Append(String.Format("happiness {0:F1}%, ", emotionScores.Happiness * 100));if (emotionScores.Neutral >= 0.1f) sb.Append(String.Format("neutral {0:F1}%, ", emotionScores.Neutral * 100));if (emotionScores.Sadness >= 0.1f) sb.Append(String.Format("sadness {0:F1}%, ", emotionScores.Sadness * 100));if (emotionScores.Surprise >= 0.1f) sb.Append(String.Format("surprise {0:F1}%, ", emotionScores.Surprise * 100));// Add glasses.sb.Append(face.FaceAttributes.Glasses);sb.Append(", ");// Add hair.sb.Append("Hair: ");// Display baldness confidence if over 1%.if (face.FaceAttributes.Hair.Bald >= 0.01f)sb.Append(String.Format("bald {0:F1}% ", face.FaceAttributes.Hair.Bald * 100));// Display all hair color attributes over 10%.IList<HairColor> hairColors = face.FaceAttributes.Hair.HairColor;foreach (HairColor hairColor in hairColors){if (hairColor.Confidence >= 0.1f){sb.Append(hairColor.Color.ToString());sb.Append(String.Format(" {0:F1}% ", hairColor.Confidence * 100));}}// Return the built string.return sb.ToString();}// </snippet_facedesc>}
}

2.MainWindow.xaml

<!-- <snippet_xaml> -->
<Window x:Class="FaceTutorial.MainWindow"xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation"xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml"Title="MainWindow" Height="700" Width="960"><Grid x:Name="BackPanel"><Image x:Name="FacePhoto" Stretch="Uniform" Margin="0,0,0,50" MouseMove="FacePhoto_MouseMove" /><DockPanel DockPanel.Dock="Bottom"><Button x:Name="BrowseButton" Width="72" Height="20" VerticalAlignment="Bottom" HorizontalAlignment="Left"Content="Browse..."Click="BrowseButton_Click" /><StatusBar VerticalAlignment="Bottom"><StatusBarItem><TextBlock Name="faceDescriptionStatusBar" /></StatusBarItem></StatusBar></DockPanel></Grid>
</Window>
<!-- </snippet_xaml> -->

参考链接

1.https://github.com/Azure/azure-sdk-for-net/tree/master/sdk

2.https://github.com/Microsoft/Cognitive-Face-Windows

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人脸识别应用初探-微软人脸识别在线SDK使用

微软人脸识别SDK使用

官方教程

document

JQuery Web

Node.js

C# WPF

参考链接

人脸识别应用初探-微软人脸识别在线SDK使用相关推荐

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