Advanced-Eye-Disease-Classification-using-EfficientNet-and-MobileNetV3

I predict 4 different eye diseases by machine learning.

1. Import Needed Modules 2 Define a function to print text in color
2. Define a function to plot the number of images in dataset classes 4 Define a function to return information on the dataset
3. Read in images and create a dataframe of image paths and class labels
4. Define a function that trims a dataset for the max number of class images
5. Balance the trainning set using augmentation
6. Create train, test and validation generators
7. Create a function to show Training Image Samples 10 Create a function to calculate the F1 score metric
8. Create the Model
9. Create a custom Keras callback to continue or halt training
10. Define a function to plot the training data
11. Define a function save the training data to a csv file
12. Define a function to make predictions on the test set
13. Make predictions on test set, create Confusion Matrix and Classification Report
14. Define a function to save the trained model 18 Define the run function which runs the classifier 19 Define the code to enable to initiate the run function
15. Evaluate Model Performance