UniApp implements image recognition and face recognition integration and usage guide

UniApp implements the integration and usage guide of image recognition and face recognition

Abstract: This article introduces how to use UniApp to integrate image recognition and face recognition functions, and provides relevant code examples to help developers Implement these functions quickly.

1. Foreword
With the continuous development of artificial intelligence, image recognition and face recognition have become important functions in modern applications. In order to meet user needs, we need to integrate these functions in UniApp. This article will lead readers step by step through the integration and use of image recognition and face recognition.

2. Image recognition
To implement the image recognition function in UniApp, we can use the image recognition API provided by Baidu AI open platform. First, we need to apply for an API key on the Baidu AI open platform to call related interfaces.

1. Introducing the SDK of Baidu AI Open Platform
   In the UniApp project, we need to introduce the SDK of a specific supplier to implement the image recognition function. After downloading and unzipping the SDK, place it in the directory of the UniApp project, and then add relevant configuration information to the uniConfig.js file.

Sample code:

<code>import BaiduSDK from './path/to/baidu-ai-sdk'</code></p>
<p>export default { <br> SDK: BaiduSDK,<br> APP_ID: 'your_app_id',<br> API_KEY: 'your_api_key',<br> SECRET_KEY: 'your_secret_key'<br>}

2. Call Image Recognition API
   In pages that require image recognition, we can use the uni.request method to call the interface of Baidu AI open platform. By passing in relevant parameters, we can implement the image recognition function.

Sample code:

<code>uni.getImageInfo({<br> success: res => {</code></p><div class="code" style="position:relative; padding:0px; margin:0px;"><pre class='brush:php;toolbar:false;'>uni.request({
  url: 'https://aip.baidubce.com/rest/2.0/image-classify/v2/advanced_general',
  method: 'POST',
  header: {
    'Content-Type': 'application/x-www-form-urlencoded'
  },
  data: {
    access_token: 'your_access_token',
    image: res.path
  },
  success: res => {
    console.log(res.data)
    // 解析接口返回的数据
  },
  fail: err => {
    console.error(err)
  }
})

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}
})

3. Face recognition
Similarly, we can use the face recognition function of Baidu AI open platform to implement face recognition in UniApp. The following are the specific implementation steps.

1. Introducing the SDK of Baidu AI Open Platform
   In the UniApp project, we need to introduce the supplier's SDK to implement the face recognition function. After downloading and unzipping the SDK, place it in the directory of the UniApp project and add relevant configuration information to the uniConfig.js file.

Sample code:

<code>import BaiduSDK from './path/to/baidu-ai-sdk'</p><p>export default { <br> SDK: BaiduSDK,<br> APP_ID: 'your_app_id',<br> API_KEY: 'your_api_key',<br> SECRET_KEY: 'your_secret_key'<br>}</code>

2. Call Face Recognition API
   In pages that require face recognition, we can use the uni.request method to call the interface of Baidu AI open platform. By passing in relevant parameters, we can implement the face recognition function.

Sample code:

<code>uni.chooseImage({<br> success: res => {</p><div class="code" style="position:relative; padding:0px; margin:0px;"><pre class='brush:php;toolbar:false;'>uni.uploadFile({
  url: 'https://aip.baidubce.com/rest/2.0/face/v3/detect',
  filePath: res.tempFilePaths[0],
  name: 'image_file',
  formData: {
    access_token: 'your_access_token',
    image_type: 'BASE64'
  },
  success: res => {
    console.log(res.data)
    // 解析接口返回的数据
  },
  fail: err => {
    console.error(err)
  }
})

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