This application leverages artificial intelligence to enhance the user experience with advanced functionalities. Below, we detail the main features and technologies utilized.

AI Lens is a mobile application designed to:

• Detect objects in images: Use machine learning models to identify and classify objects.
• Perform product searches: Based on object detection, the application allows you to search for similar products online.
• Augmented Reality (AR): Shows the name of the detected objects in the real-time view.
• Google Maps: Integrate maps to show the user's location and provide a contextualized AR experience.

• Image upload: Allows the user to upload an image from the gallery for object detection.
• Photo capture: Allows the user to take a photo using the camera to detect objects in real time.

• Object-based results: Uses object detection to suggest products similar to those identified.

• Integration with online search services: Make it easy to find relevant products using search engines.

  

• Real time view: Shows the names of detected objects overlaid on the camera view.

• Intuitive interaction: Allows the user to explore detected objects with augmented reality.

  

• Location display: Shows the user's location on a map.
• Contextual AR: Overlay location in augmented reality to improve navigation and interaction.

• TensorFlow Lite: For the object detection model and inference on mobile devices.
• Google AI Vertex: For training machine learning models. Google Cloud
• Google Maps: For the integration of maps and AR functionality.
• Android: Mobile platform for the implementation of the application.
• Programmable Search Engine: A customizable search engine that allows users to create and control their own web search experience. Search Engine

1. Clone this repository.

2. Install the necessary dependencies using gradle.

3. Configure the necessary Google APIs for Maps and AI Vertex.

   • Cloud Vision API
   • Custom Search API
   • Vertex AI API
   • Maps SDK for Android
   • Places API

Location where the credential.json file should be placed

 path : res/raw/credential.json

Credential structure example:

{
  "type": "service_account",
  "project_id": "xxxxxxxxxxxx",
  "private_key_id": "xxxxxxxxxxxxxx",
  "private_key": "-----BEGIN PRIVATE KEY-----\xxxxx\n-----END PRIVATE KEY-----\n",
  "client_email": "xxxxxxxxxx.iam.gserviceaccount.com",
  "client_id": "xxxxxxxxxxxxxxx",
  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
  "token_uri": "https://oauth2.googleapis.com/token",
  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
  "client_x509_cert_url": "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx.iam.gserviceaccount.com",
  "universe_domain": "googleapis.com"
}

Contributions are welcome. To contribute, follow the steps to clone the repository and make a pull request. 🚀