LattePanda Face Recognize


Introduction: LattePanda Face Recognize

About: Green hand in arduino

These days, I found an interesting API on the Microsoft website that can detect your face and tell you your age, gender according to your photo. Today, I will try to build this simple demo on my Lattepanda. That's funny to see how old I am! Let's wait and see!

You can also try to run the demo on your computer.


Microsoft Cognitive Services are a set of APIs, SDKs and services available to developers to make their applications more intelligent, engaging and discoverable.It let you build apps with powerful algorithms using just a few lines of code. They work across devices and platforms such as iOS, Android, and Windows, keep improving, and are easy to set up.

Step 1: Configure the System Environment

Step 2: Get the Key of Face API

Face API is a cloud-based API that provides the most advanced algorithms for face detection and recognition. The main functionality of Face API can be divided into two categories: face detection with attributes extraction and face recognition.

First, Click "Get started for free", sign in your account then you will have your APIkey.

You can check your key in your account.

Step 3: Install Visual Studio 2017

I recommend you install the latest version of the Visual Studio.

Step 4: Run the Program

Open the Visual Studio, creat a new Console Application Project.

File→New→project→Choose Console Application

Copy the following code to your program, replace the example key with your valid key. You can get more example code from here.

using System;
using System.IO; using System.Net.Http.Headers; using System.Net.Http;

namespace CSHttpClientSample { static class Program { static void Main() { Console.Write("Enter the location of your picture:"); string imageFilePath = Console.ReadLine();


Console.WriteLine("\n\n\nWait for the result below, then hit ENTER to exit...\n\n\n"); Console.ReadLine(); }

static byte[] GetImageAsByteArray(string imageFilePath) { FileStream fileStream = new FileStream(imageFilePath, FileMode.Open, FileAccess.Read); BinaryReader binaryReader = new BinaryReader(fileStream); return binaryReader.ReadBytes((int)fileStream.Length); }

static async void MakeAnalysisRequest(string imageFilePath) { var client = new HttpClient();

// Request headers - replace this example key with your valid key. client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", "Enter your apikey here");

// Request parameters and URI string. string queryString = "returnFaceId=true&returnFaceLandmarks=false&returnFaceAttributes=age,gender"; string uri = "" + queryString;

HttpResponseMessage response; string responseContent;

// Request body. Try this sample with a locally stored JPEG image. byte[] byteData = GetImageAsByteArray(imageFilePath);

using (var content = new ByteArrayContent(byteData)) { // This example uses content type "application/octet-stream". // The other content types you can use are "application/json" and "multipart/form-data". content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream"); response = await client.PostAsync(uri, content); responseContent = response.Content.ReadAsStringAsync().Result; }

//A peak at the JSON response. Console.WriteLine(responseContent); } } }

Step 5: Test

Press Start. Enter the path of the picture.Let's see how cool is the response!

A successful response will be returned in JSON.

It shows that I looks like 30 years old :-) . How about you?

Step 6: Some Problems I Met

Step 7: ​Solution: ​

Please update your .NET Framework to the latest version, or there will be some error.

This is just a simple example to show how to use the API, I hope that this tutorial is useful for you. Have fun!



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    That is really cool. It is kind of crazy just how good computers are getting at recognizing stuff.