You can find the complete code at this Github repo. Infinite Red's NSFW JS and React Native example.In a desktop application, it opens the file picker which allows us to choose an image file which is already stored in the device. This allows us to access the device camera and take snapshots in a mobile device. tfjs-react-native Github repo contain more examples using different pre-trained models capture environment: The outward-facing camera should be used.You should use this approach if you want to control how your users will see and select images. Once the user selects an image, we’ll use the Upload From Camera Roll Module to get the base64 image data from the selected image. Here are some resources that I find extremely useful. This approach uses the built-in React Native Camera Roll API to display existing camera roll images to the user. Since the TF.js for React Native is in alpha at the time of writing this post, we can hope to see many more advanced examples in the future to build real-time applications. I hope this post serves the purpose of giving you a head start in understanding how to implement a TesnorFlow.js model in a React Native app, as well as a better understanding of image classification, a core use case in computer vision-based machine learning. Here are the results of the previously selected image. Then, once the model is ready, it will display the text "Tap to choose image" inside the box. The first thing you’ll notice is that upon bootstrapping the app in the Expo client, it will ask for permissions. Run the application by executing the expo start command from a terminal window.
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