https://github.com/faisalsayed10/no-ghibli
No Ghibli on Twitter
https://github.com/faisalsayed10/no-ghibli
Last synced: about 1 month ago
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No Ghibli on Twitter
- Host: GitHub
- URL: https://github.com/faisalsayed10/no-ghibli
- Owner: faisalsayed10
- Created: 2025-03-28T03:27:30.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2025-03-28T08:18:10.000Z (about 1 month ago)
- Last Synced: 2025-03-28T08:22:26.610Z (about 1 month ago)
- Language: Jupyter Notebook
- Size: 85.9 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-ccamel - faisalsayed10/no-ghibli - No Ghibli on Twitter (Jupyter Notebook)
README
# No Ghibli Chrome Extension
A Chrome extension that helps you identify and filter out Studio Ghibli-related content from Twitter. This project consists of a Flask backend service that performs image classification and a Chrome extension that integrates with it.
## Simplest Setup
- Download the `extension` directory from the [release page](https://github.com/faisalsayed10/no-ghibli/releases)
- Go to `chrome://extensions/`
- Enable "Developer mode" in the top right corner
- Click "Load unpacked" and select the `extension` directory
## Project Structure
```
.
├── flask/ # Backend Flask application
│ ├── app.py # Main Flask application
│ ├── requirements.txt # Python dependencies
│ ├── model.keras # Trained Keras model
│ └── ghibli/ # Additional Ghibli-related files
└── extension/ # Chrome extension
├── manifest.json # Extension configuration
├── popup.html # Extension popup interface
├── popup.js # Popup functionality
├── popup.css # Popup styling
├── content.js # Content script for webpage interaction
└── images/ # Extension icons and images
```
## Features
- Real-time detection of Studio Ghibli-related images on Twitter
- Hides the entire tweet if it contains a Studio Ghibli-related image / video
- User-friendly popup interface for controlling the extension
- Efficient image classification using a trained Keras model
## Prerequisites
- Python 3.8 or higher
- Chrome browser
- Node.js and npm (for development)
## Installation
### Backend Setup
1. Navigate to the Flask directory:
```bash
cd flask
```
2. Create a virtual environment (recommended):
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```
4. Start the Flask server:
```bash
python app.py
```
The backend server will start on `http://localhost:5000` by default.
### Chrome Extension Setup
1. Open Chrome and navigate to `chrome://extensions/`
2. Enable "Developer mode" in the top right corner
3. Click "Load unpacked" and select the `extension` directory from this project
4. The extension icon should appear in your Chrome toolbar
## Usage
1. Click the extension icon in your Chrome toolbar to open the popup interface
2. Use the toggle switch to enable/disable Ghibli content detection
3. Browse Twitter as usual - the extension will automatically detect and handle Ghibli-related content
## Development
### Backend Development
The Flask backend uses:
- Flask for the web server
- TensorFlow/Keras for image classification
- Flask-CORS for handling cross-origin requests
- Gunicorn for production deployment
### Extension Development
The Chrome extension is built with:
- Vanilla JavaScript
- Chrome Extension APIs
- HTML/CSS for the popup interface
## API Endpoints
The Flask backend provides the following endpoints:
- `POST /predict`: Accepts image data and returns classification results
- `GET /health`: Health check endpoint
## Contributing
1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request