This project implements neural networks for flower classification and lung segmentation using TensorFlow.
- Flower Species: 1678 RGB images across 10 classes
- Lungs X-Rays: The dataset contains 704 X-rays and corresponding lung segmentation masks. Each image is grayscale and of shape 512×512.
training2.ipynb
: Train the flower classifier and lung segmentation networks. Includes data loading, model definition, hyperparameter tuning, and evaluation.testing.ipynb
: Evaluate the trained model on the test sets.
- Install TensorFlow and required libraries.
- Open
training.ipynb
in Jupyter Notebook and run cells sequentially. - After training, open
test.ipynb
to evaluate the model.
Some more files are also included:
- report.pdf
- model_cnn.keras
- model_mlp.keras