This project was developed with the help of AI tools, using them as a guide, assistant, and for significant code generation. All final creative decisions and deployments reflect my own work and intentions.
X-Ray Image Classifier An intuitive and user-friendly web application developed using Python & TensorFlow to classify images and identify if they indicate the presence of pneumonia.
X-Ray Classifier Demo
Features
-
Upload & Visualize: Easily upload X-ray images and get a visual preview.
-
Instant Prediction: The app uses a trained deep learning model to make instant predictions on the uploaded images.
-
Feedback System: Users can provide feedback on the predictions, aiding in iterative improvement.
-
Feedback Summary: Users can view a summary of the feedback received for the application.
Live Demo The application is hosted on Streamlit. Check out the live app here: https://cmac-ml.streamlit.app
Python==3.11.4
streamlit==1.25.0
keras==2.13.1
numpy==1.24.3
Pillow==9.5.0
h5py==3.9.0
tensorflow-cpu==2.13.0
pandas==2.0.3
Usage Simply upload an X-ray image using the file uploader. The app will display the image, make a prediction, and present the results. Users are encouraged to provide feedback on the prediction. Built With
Streamlit - The web framework utilized.
TensorFlow/Keras - Employed for deep learning and predictions.
SQLite - Used for storing and summarizing user feedback.
License Distributed under MIT. See LICENSE for more information.
Contact
https://www.linkedin.com/in/cormac-farrelly-b080b9279/
https://www.instagram.com/cmac_987/
Project Repository: https://github.com/cmac-ire/machine-learning-app