AI Image Classifier

🎓 Academic Project — developed as part of Programming intelligent systems at University of Economics in Cracow.

This is a web application for classifying images and finding similar images using the power of machine learning models. The application allows users to upload an image, classify it using a pre-trained model, and display similar images fetched from Google Custom Search API.

Features

• Image Classification: The application uses the Hugging Face API to classify images.
• Similar Images Search: Once the image is classified, it searches for similar images using Google Custom Search API.
• Responsive UI: The interface is modern and responsive, providing a smooth user experience on both desktop and mobile devices.

Technologies Used

• ASP.NET Core: The application is built using ASP.NET Core MVC for the backend.
• Hugging Face API: Used for image classification with the ResNet-50 model.
• Google Custom Search API: Used to search for similar images based on the classified image label.
• Bootstrap: Used for styling the frontend with a modern, responsive design.

Setup Instructions

Prerequisites

Ensure you have the following installed:

• .NET 8+ SDK
• Visual Studio Code or Visual Studio
• A Hugging Face API Token (for the classification service).
• A Google Custom Search API Key and a Search Engine ID (CX) (for fetching similar images).

Steps to Run

1. Clone the Repository

   git clone https://github.com/calKU0/AIImageClassifier.git
   cd AIImageClassifier
   

2. Install Dependencies

   Run the following command to restore the required packages:

   dotnet restore
   

3. Set up Configuration

   Add your API keys and configuration to the appsettings.json file:

   {
     "HuggingFace": {
       "ApiToken": "your_huggingface_api_token"
     },
     "Google": {
       "ApiKey": "your_google_api_key",
       "cx": "your_google_cx"
     }
   }
   

4. Run the Application

   Once everything is set up, you can run the application using the following command:

   dotnet run
   

   The application will be available at http://localhost:5000.

5. Upload an Image

   • Navigate to the homepage.
   • Upload an image, and the application will display:
     • The classified label of the image along with a confidence score.
     • A preview of the uploaded image.
     • A set of similar images fetched from the Google Custom Search API.

How It Works

1. Image Upload: The user uploads an image via a form. The image is sent to the server.

2. Image Classification: The server sends the image to the Hugging Face API (microsoft/resnet-50 model) to classify the image. The response contains a label for the image along with a confidence score.

3. Similar Image Search: Using the label of the classified image, the application makes a request to the Google Custom Search API to find similar images.

4. Display Results: The classified label, confidence score, image preview, and similar images are displayed to the user in a modern, responsive UI.

Folder Structure

AIImageClassifier/
├── Controllers/
│   └── HomeController.cs       # Handles image upload and classification logic
├── Models/
│   └── ImageInputModel.cs      # Model for handling the uploaded image and results
│   └── ClassificationResult.cs # Defines the classification result structure
├── Services/
│   └── IImageClassifier.cs     # Interface for image classification services
│   └── HuggingFaceImageClassifier.cs # Implements the classification logic using Hugging Face API
├── Views/
│   └── Home/
│       └── Index.cshtml        # View for image upload, preview, and results display
├── appsettings.json            # Application configuration (API Keys, etc.)
├── Startup.cs                  # Application configuration and middleware setup
├── Program.cs                  # Main entry point of the application
└── README.md                   # This file

Custom Search API

For searching similar images, the app uses Google Custom Search API. Ensure you set up your Google Custom Search Engine properly.

1. Go to Google Custom Search Engine and create a search engine.
2. Enable image search and set up the API.
3. Add the API key and the CX (Search Engine ID) to your appsettings.json.

Troubleshooting

Errors with Hugging Face API

• Make sure the API token is valid and has the required permissions.
• Check that the ResNet-50 model is available in Hugging Face's model hub.

Errors with Google Custom Search API

• Ensure that the API key and the cx value are correct.
• Double-check that image search is enabled in the Google Custom Search settings.

Contributions

If you would like to contribute to this project, feel free to fork the repository, make your changes, and submit a pull request. Any contributions are welcome!

License

This project is licensed under the MIT License – see the LICENSE file for details.