This project demonstrates the implementation of a ResNet50-based deep learning model for dual output image classification. The model is designed to classify images into two distinct categories simultaneously: CDI and Pneumonia. The model is trained and validated using custom data generators, and the implementation includes steps for preprocessing, training, validating, and testing the model.

Requirements To run the code, you need the following libraries installed in your Python environment:

tensorflow == 1.4 keras == 2.1.5 sklearn == 0.22.2 matplotlib == 3.0.3 cv2 numpy pandas pathlib

you can install them using pip

pip install tensorflow==1.4 keras==2.1.5 scikit-learn==0.22.2 matplotlib==3.0.3 opencv-python numpy pandas