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🐾 Animal Intelligence AI Classifier

A deep learning-based web application that identifies animal species from uploaded images. Powered by FastAPI and PyTorch (ResNet18).

πŸš€ Features

  • Instant Identification: Upload an image and get predictions in milliseconds.
  • Dynamic Learning: Supports any number of animal classes based on your training data.
  • Modern UI: Clean, responsive interface with drag-and-drop support and visual feedback.
  • Confidence Scoring: High-accuracy predictions with visual indicators for low-confidence results.

πŸ› οΈ Setup & Installation

1. Clone the Project

git clone <your-repo-url>
cd FastAPI_Pet_Classifier

2. Create a Virtual Environment

python -m venv venv
# On Windows
.\venv\Scripts\Activate.ps1
# On Mac/Linux
source venv/bin/activate

3. Install Dependencies

pip install -r requirements.txt

πŸ‹οΈ Training for Other Animals

You can easily extend this model to identify any animal.

  1. Prepare Data:
    • Create a folder for the animal in data/train/ (e.g., data/train/elephant).
    • Create the same folder in data/val/.
    • Add images of that animal to both folders.
  2. Run Training:
    python train.py --data_dir ./data --epochs 10
    
  3. The model will automatically detect the new folders and update itself!

πŸ–₯️ Running the App

Start the web server:

python -m uvicorn app:app --reload

Open your browser and navigate to: http://127.0.0.1:8000


πŸ“¦ Deployment

This app is ready for deployment on Hugging Face Spaces or Render.

  • Ensure models/model.pth is included in your upload.
  • The app uses CPU-only inference for maximum compatibility with free hosting tiers.

πŸ‘₯ Credits

Developed by Group 6 Deep Learning. Powered by PyTorch ResNet18.

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