Cloud Vision Swift Sample

This app demonstrates how to use the Cloud Vision API to run label and face detection on an image.

Prerequisites

• An API key for the Cloud Vision API (See the docs to learn more)
• An OSX machine or emulator
• Xcode 7
• Install CocoaPods if you don't have it already by running the command sudo gem install cocoapods.
  • You'll need to have RubyGems installed in order to install CocoaPods.

Quickstart

• Clone this repo and cd into the Swift directory.
• In ImagePickerViewController.swift, replace YOUR_API_KEY with the API key obtained above.
• cd into the Swift directory and install the SwiftyJSON pod by running pod install.
• Open the project by running open imagepicker.xcworkspace.
• Build and run the app.

Running the app

• As with all Google Cloud APIs, every call to the Vision API must be associated with a project within the Google Cloud Console that has the Vision API enabled. This is described in more detail in the getting started doc, but in brief:

  • Create a project (or use an existing one) in the Cloud Console
  • Enable billing and the Vision API.
  • Create an API key, and save this for later.

• Clone this cloud-vision repository on GitHub. If you have git installed, you can do this by executing the following command:

    $ git clone https://github.com/GoogleCloudPlatform/cloud-vision.git
  

  This will download the repository of samples into the directory cloud-vision.

  Otherwise, GitHub offers an auto-generated zip file of the master branch, which you can download and extract. Either method will include the desired directory at cloud-vision/ios/Swift.

• cd into the cloud-vision/ios/Swift directory you just cloned. The app uses the SwiftyJSON pod to parse the JSON response. This pod is defined in the Podfile, and you can install it by running pod install.

• Run the command open imagepicker.xcworkspace to open this project in Xcode. Be sure to open the xcworkspace version of the project.

• In Xcode's Project Navigator, open the ImagePickerViewController.swift file within the imagepicker directory.

• Find the line where the API_KEY is set. Replace the string value with the API key obtained from the Cloud console above. This key is the credential used in the createRequest method to authenticate all requests to the Vision API. Calls to the API are thus associated with the project you created above, for access and billing purposes.

• You are now ready to build and run the project. In Xcode you can do this by clicking the 'Play' button in the top left. This will launch the app on the simulator or on the device you've selected.

• Click the Choose an image to analyze button. This calls the loadImageButtonTapped action to load the device's photo library.

• Select an image from your device. If you're using the simulator, you can drag and drop an image from your computer into the simulator using Finder.

  • This executes the imagePickerController, which saves the selected image and calls the base64EncodeImage function. This function base64 encodes the image and resizes it if it's too large to send to the API.
  • The createRequest method creates and executes a label and face detection request to the Cloud Vision API.
  • When the API responds, the analyzeResults function is called. This method constructs a string of the labels returned from the API. If there are faces detected in the photo, it analyzes the emotions detected. It then displays the label and face results in the UI by populating the labelResults and faceResults UITextView with the data returned from the API.