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CarLens

CarLens is a mobile app that uses Augmented Reality and Machine Learning to detect different car models. It connects to your smartphone camera and enables you to verify cars around as you walk on the streets.

We currently support the newest versions of 4 cars in CarLens:

  • Honda Civic
  • Ford Fiesta
  • Nissan Qashqai
  • Volkswagen Passat

Discover car recognition together with CarLens!

Tools & Frameworks

Configuration

Prerequisites

Instalation

  1. Clone repository:

    # over https:
    git clone https://github.com/netguru/CarLens-iOS
    # or over SSH:
    git@github.com:netguru/CarLens-iOS.git
  2. Install required Gems:

    bundle install
  3. Run Carthage:

    carthage bootstrap --platform iOS --cache-builds
  4. Rename .env.sample to .env.

  5. Install pods through Bundler:

    bundle exec pod install
  6. Open CarLens.xcworkspace file and build the project.

CarLensCollectionViewLayout

As a part of CarLens we've launched another open source tool - CarLensCollectionViewLayout. Its an easy-to-use Collection View Layout for card-like animation 🎉. Make sure to check it out too!

About

This project is made with ❤️ by Netguru and maintained by Anna-Mariia Shkarlinska.

License

CarLens is licensed under the Apache License. See LICENSE for more info.

Contribution

All contributions are welcome! Feel free to create issues and PRs. Please, respect the following coding guidelines:

  • Respect Swift API Design Guidelines

  • The code must be readable and self-explanatory - full variable names, meaningful methods, etc.

  • Don't leave any commented-out code.

  • Write documentation for every method and property accessible outside the class. For example, well-documented method looks as follows:

     /// Tells the magician to perform a given trick.
     ///
     /// - Parameter trick: The magic trick to perform.
     /// - Returns: Whether the magician succeeded in performing the magic trick.
     func perform(magicTrick trick: MagicTrick) -> Bool {
     	// body
     }

Read More About CarLens

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