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    Label Images Securely with Cloud Vision using Firebase Auth and Functions on Apple platforms

    In order to call a Google Cloud API from your app, you need to create an intermediate REST API that handles authorization and protects secret values such as API keys. You then need to write code in your mobile app to authenticate to and communicate with this intermediate service.

    One way to create this REST API is by using Firebase Authentication and Functions, which gives you a managed, serverless gateway to Google Cloud APIs that handles authentication and can be called from your mobile app with pre-built SDKs.

    This guide demonstrates how to use this technique to call the Cloud Vision API from your app. This method will allow all authenticated users to access Cloud Vision billed services through your Cloud project, so consider whether this auth mechanism is sufficient for your use case before proceeding.

    Before you begin

    Configure your project

    If you have not already added Firebase to your app, do so by following the steps in the getting started guide .

    Use Swift Package Manager to install and manage Firebase dependencies.

    1. In Xcode, with your app project open, navigate to File > Add Packages .
    2. When prompted, add the Firebase Apple platforms SDK repository:
      3. https://github.com/firebase/firebase-ios-sdk.git
    3. Choose the Firebase ML library.
    4. Add the -ObjC flag to the Other Linker Flags section of your target's build settings.
    5. When finished, Xcode will automatically begin resolving and downloading your dependencies in the background.

    Next, perform some in-app setup:

    1. In your app, import Firebase:

      Swift

       import 
  
 FirebaseMLModelDownloader

      Objective-C

       @import 
  
 FirebaseMLModelDownloader 
 ;

    A few more configuration steps, and we're ready to go:

    1. If you haven't already enabled Cloud-based APIs for your project, do so now:

      1. Open the Firebase ML APIs page in the Firebase console.

      2. If you haven't already upgraded your project to the pay-as-you-go Blaze pricing plan , click Upgrade to do so. (You'll be prompted to upgrade only if your project isn't on the Blaze pricing plan.)

        Only projects on the Blaze pricing plan can use Cloud-based APIs.

      3. If Cloud-based APIs aren't already enabled, click Enable Cloud-based APIs .
    2. Configure your existing Firebase API keys to disallow access to the Cloud Vision API:
      1. Open the Credentials page of the Cloud console.
      2. For each API key in the list, open the editing view, and in the Key Restrictions section, add all of the available APIs except the Cloud Vision API to the list.

    Deploy the callable function

    Next, deploy the Cloud Function you will use to bridge your app and the Cloud Vision API. The functions-samples repository contains an example you can use.

    By default, accessing the Cloud Vision API through this function will allow only authenticated users of your app access to the Cloud Vision API. You can modify the function for different requirements.

    To deploy the function:

    1. Clone or download the functions-samples repo and change to the Node-1st-gen/vision-annotate-image directory: 
       git clone https://github.com/firebase/functions-samples 
 cd Node-1st-gen/vision-annotate-image
    2. Install dependencies: 
       cd functions 
 npm install 
 cd ..
    3. If you don't have the Firebase CLI, install it .
    4. Initialize a Firebase project in the vision-annotate-image directory. When prompted, select your project in the list. 
      firebase init
    5. Deploy the function: 
      firebase deploy --only functions:annotateImage

    Add Firebase Auth to your app

    The callable function deployed above will reject any request from non-authenticated users of your app. If you have not already done so, you will need to add Firebase Auth to your app.

    Add necessary dependencies to your app

    Use Swift Package Manager to install the Cloud Functions for Firebase library.

    Now you are ready to label images.

    1. Prepare the input image

    In order to call Cloud Vision, the image must be formatted as a base64-encoded string. To process a UIImage :

    Swift

     guard 
  
 let 
  
 imageData 
  
 = 
  
 uiImage 
 . 
 jpegData 
 ( 
 compressionQuality 
 : 
  
 1.0 
 ) 
  
 else 
  
 { 
  
 return 
  
 } 
 let 
  
 base64encodedImage 
  
 = 
  
 imageData 
 . 
 base64EncodedString 
 ()

    Objective-C

     NSData 
  
 * 
 imageData 
  
 = 
  
 UIImageJPEGRepresentation 
 ( 
 uiImage 
 , 
  
 1.0f 
 ); 
 NSString 
  
 * 
 base64encodedImage 
  
 = 
  
 [ 
 imageData 
  
 base64EncodedStringWithOptions 
 : 
 NSDataBase64Encoding76CharacterLineLength 
 ];

    2. Invoke the callable function to label the image

    To label objects in an image, invoke the callable function passing a JSON Cloud Vision request .

    1. First, initialize an instance of Cloud Functions:

      Swift

        lazy 
  
 var 
  
 functions 
  
 = 
  
 Functions 
 . 
 functions 
 ()

      Objective-C

        @property 
 ( 
 strong 
 , 
  
 nonatomic 
 ) 
  
 FIRFunctions 
  
 * 
 functions 
 ;

    2. Create a request with Type set to LABEL_DETECTION :

      Swift

        let 
  
 requestData 
  
 = 
  
 [ 
  
 "image" 
 : 
  
 [ 
 "content" 
 : 
  
 base64encodedImage 
 ], 
  
 "features" 
 : 
  
 [ 
 "maxResults" 
 : 
  
 5 
 , 
  
 "type" 
 : 
  
 "LABEL_DETECTION" 
 ] 
 ]

      Objective-C

        NSDictionary 
  
 * 
 requestData 
  
 = 
  
 @{ 
  
 @"image" 
 : 
  
 @{ 
 @"content" 
 : 
  
 base64encodedImage 
 } 
 , 
  
 @"features" 
 : 
  
 @{ 
 @"maxResults" 
 : 
  
 @5 
 , 
  
 @"type" 
 : 
  
 @"LABEL_DETECTION" 
 } 
 } 
 ;

    3. Finally, invoke the function:

      Swift

        do 
  
 { 
  
 let 
  
 result 
  
 = 
  
 try 
  
 await 
  
 functions 
 . 
 httpsCallable 
 ( 
 "annotateImage" 
 ). 
 call 
 ( 
 requestData 
 ) 
  
 print 
 ( 
 result 
 ) 
 } 
  
 catch 
  
 { 
  
 if 
  
 let 
  
 error 
  
 = 
  
 error 
  
 as 
  
 NSError 
 ? 
  
 { 
  
 if 
  
 error 
 . 
 domain 
  
 == 
  
 FunctionsErrorDomain 
  
 { 
  
 let 
  
 code 
  
 = 
  
 FunctionsErrorCode 
 ( 
 rawValue 
 : 
  
 error 
 . 
 code 
 ) 
  
 let 
  
 message 
  
 = 
  
 error 
 . 
 localizedDescription 
  
 let 
  
 details 
  
 = 
  
 error 
 . 
 userInfo 
 [ 
 FunctionsErrorDetailsKey 
 ] 
  
 } 
  
 // ... 
  
 } 
 }

      Objective-C

        [[ 
 _functions 
  
 HTTPSCallableWithName 
 : 
 @"annotateImage" 
 ] 
  
 callWithObject 
 : 
 requestData 
  
 completion 
 : 
 ^ 
 ( 
 FIRHTTPSCallableResult 
  
 * 
  
 _Nullable 
  
 result 
 , 
  
 NSError 
  
 * 
  
 _Nullable 
  
 error 
 ) 
  
 { 
  
 if 
  
 ( 
 error 
 ) 
  
 { 
  
 if 
  
 ([ 
 error 
 . 
 domain 
  
 isEqualToString 
 : 
 @"com.firebase.functions" 
 ]) 
  
 { 
  
 FIRFunctionsErrorCode 
  
 code 
  
 = 
  
 error 
 . 
 code 
 ; 
  
 NSString 
  
 * 
 message 
  
 = 
  
 error 
 . 
 localizedDescription 
 ; 
  
 NSObject 
  
 * 
 details 
  
 = 
  
 error 
 . 
 userInfo 
 [ 
 @"details" 
 ]; 
  
 } 
  
 // ... 
  
 } 
  
 // Function completed succesfully 
  
 // Get information about labeled objects 
  
 }];

    3. Get information about labeled objects

    If the image labeling operation succeeds, a JSON response of BatchAnnotateImagesResponse will be returned in the task's result. Each object in the labelAnnotations array represents something that was labeled in the image. For each label, you can get the label's text description, its Knowledge Graph entity ID (if available), and the confidence score of the match. For example:

    Swift

      if 
  
 let 
  
 labelArray 
  
 = 
  
 ( 
 result 
 ?. 
 data 
  
 as 
 ? 
  
 [ 
 String 
 : 
  
 Any 
 ])?[ 
 "labelAnnotations" 
 ] 
  
 as 
 ? 
  
 [[ 
 String 
 : 
 Any 
 ]] 
  
 { 
  
 for 
  
 labelObj 
  
 in 
  
 labelArray 
  
 { 
  
 let 
  
 text 
  
 = 
  
 labelObj 
 [ 
 "description" 
 ] 
  
 let 
  
 entityId 
  
 = 
  
 labelObj 
 [ 
 "mid" 
 ] 
  
 let 
  
 confidence 
  
 = 
  
 labelObj 
 [ 
 "score" 
 ] 
  
 } 
 }

    Objective-C

      NSArray 
  
 * 
 labelArray 
  
 = 
  
 result 
 . 
 data 
 [ 
 @"labelAnnotations" 
 ]; 
 for 
  
 ( 
 NSDictionary 
  
 * 
 labelObj 
  
 in 
  
 labelArray 
 ) 
  
 { 
  
 NSString 
  
 * 
 text 
  
 = 
  
 labelObj 
 [ 
 @"description" 
 ]; 
  
 NSString 
  
 * 
 entityId 
  
 = 
  
 labelObj 
 [ 
 @"mid" 
 ]; 
  
 NSNumber 
  
 * 
 confidence 
  
 = 
  
 labelObj 
 [ 
 @"score" 
 ]; 
 }
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