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πΎ Animal Intelligence AI Classifier
A deep learning-based web application that identifies animal species from uploaded images. Powered by FastAPI and PyTorch (ResNet18).
π 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.
π 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
ποΈ Training for Other Animals
You can easily extend this model to identify any animal.
- 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.
- Create a folder for the animal in
- Run Training:
python train.py --data_dir ./data --epochs 10 - The model will automatically detect the new folders and update itself!
π₯οΈ 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
π¦ Deployment
This app is ready for deployment on Hugging Face Spaces or Render.
- Ensure
models/model.pthis included in your upload. - The app uses CPU-only inference for maximum compatibility with free hosting tiers.
π₯ Credits
Developed by Group 6 Deep Learning. Powered by PyTorch ResNet18.
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