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UniApp implements image recognition and face recognition integration and usage guide

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WBOYOriginal
2023-07-05 15:25:073460browse

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:

e03b848252eb9375d56be284e690e873import BaiduSDK from './path/to/baidu-ai-sdk'

export default {
SDK: BaiduSDK,
APP_ID: 'your_app_id',
API_KEY: 'your_api_key',
SECRET_KEY: 'your_secret_key'
}bc5574f69a0cba105bc93bd3dc13c4ec

  1. 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:
e03b848252eb9375d56be284e690e873uni.getImageInfo({<br> success: res => {

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)
  }
})

}
}) bc5574f69a0cba105bc93bd3dc13c4ec

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:

e03b848252eb9375d56be284e690e873import BaiduSDK from './path/to/baidu-ai-sdk'

export default {
SDK: BaiduSDK,
APP_ID: 'your_app_id',
API_KEY: 'your_api_key',
SECRET_KEY: 'your_secret_key'
}bc5574f69a0cba105bc93bd3dc13c4ec

  1. 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:

e03b848252eb9375d56be284e690e873uni.chooseImage({<br> success: res => {

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)
  }
})

}
})bc5574f69a0cba105bc93bd3dc13c4ec

Through the above code examples, we can integrate image recognition and face recognition functions in UniApp. Developers can call different API interfaces according to specific needs to achieve richer functions. I hope this article can help you implement image recognition and face recognition functions in the UniApp project.

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