Welcome to the Bird Species Classification application! This app uses machine learning to classify bird species from images. It allows you to upload an image of a bird, get predictions, and explore a gallery of bird species.
- Upload Image: Upload an image of a bird for classification.
- Prediction: Get accurate predictions on the bird species using a trained model.
- Gallery: Explore a gallery with a wide variety of bird species.
- User-Friendly: Easy-to-use interface for anyone to try.
This application uses a pre-trained model that is based on the CUB-200-2011 dataset. The model has been trained to classify birds with high accuracy (around 90%!). 🦉
The CUB-200-2011 dataset can be accessed here.
- Python 3.x
- pip (Python package installer)
- Clone the Repository:
git clone https://github.com/Fizm00/AvianSense.git
- Clone the Repository:
pip install -r requirements.txt
- Clone the Repository:
streamlit run app.py
- Start Classifying Birds! 🦜
- Upload an image of a bird to the app. 📷
- Click on the Predict button to see the classification results. 🔍
- Explore the bird species in the Gallery section. 🖼️
A: The model has been trained on a diverse dataset and achieves high accuracy (around 90%). However, its performance may vary depending on the quality of the image. 🧐
A: Yes! We welcome contributions to enhance the app. Please reach out to us via the contact section for more details on how you can contribute to the development of the Streamlit web application. 🙌
A: This application can classify birds from the CUB-200-2011 dataset. You can explore a wide range of bird species through the gallery. For more details, check out the dataset on Kaggle. 🦅
For any questions, issues, or suggestions, feel free to reach out to us:
- Email: himawanfirza21@gmail.com 📧
- Streamlit: For building the web app interface. 🌐
- PyTorch: For the deep learning model. 🤖
- CUB-200-2011 Dataset: For bird species classification. 🦅
This project is licensed under the MIT License - see the LICENSE file for details. 📄