README.md

metadata

title: Car vs Bike Classification
emoji: 🏎️🏍️
colorFrom: blue
colorTo: indigo
sdk: docker
app_port: 7860
pinned: false

Car vs Bike Classifier

A high-performance, portable image classification system with a premium "Glassmorphism" interface.

🚀 Quick Start

1. Double-click RUN_PROJECT.bat in the C:\CNN folder.
2. The script will automatically:
   • Train the Scikit-learn model (if missing).
   • Start the Unified Flask Server.
3. Open your browser to: http://localhost:8000

✨ Features

• Integrated Architecture: Frontend and Backend served by a single Flask process.
• Premium Design: Modern, responsive UI with glassmorphism effects.
• Portable Environment: Includes Python 3.11 with all dependencies pre-installed.
• High Speed: Optimized Scikit-learn model for instant classification.

🤗 Hugging Face Space Deployment

This project is optimized for deployment as a Docker Space on Hugging Face.

1. Create a new Space on Hugging Face.
2. Select Docker as the SDK.
3. Push your project files to the Space:
   • Make sure Dockerfile, backend/, and car_bike_model.pkl are included.
4. The space will automatically build and deploy the app on port 7860.

Alternatively, use the included assistant for a standard upload (if not using Docker):

1. Open a terminal in the project folder.
2. Run: HF_ASSISTANT.bat auth login (you will need your HF Token).
3. Run: HF_ASSISTANT.bat upload Afnaan08/CarvsBike .

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