--- a
+++ b/train.py
@@ -0,0 +1,36 @@
+# -*- coding: utf-8 -*-
+"""train.ipynb
+
+**
+ * This file is part of Hybrid CNN-LSTM for COVID-19 Severity Score Prediction paper.
+ *
+ * Written by Ankan Ghosh Dastider and Farhan Sadik.
+ *
+ * Copyright (c) by the authors under Apache-2.0 License. Some rights reserved, see LICENSE.
+ */
+
+"""
+
+#EPOCHS=70
+annealer = ReduceLROnPlateau(monitor='val_accuracy', factor=0.5, patience=5, verbose=1, min_lr=1e-3)
+checkpoint = ModelCheckpoint('Model.h5', verbose=1, save_best_only=True)
+# Generates batches of image data with data augmentationV
+datagen = ImageDataGenerator(rotation_range=360, # Degree range for random rotations
+                        width_shift_range=0.2, # Range for random horizontal shifts
+                        height_shift_range=0.2, # Range for random vertical shifts
+                        zoom_range=0.2, # Range for random zoom
+                        horizontal_flip=True, # Randomly flip inputs horizontally
+                        vertical_flip=True) # Randomly flip inputs vertically
+
+datagen.fit(X_train)
+# Fits the model on batches with real-time data augmentation
+hist = model.fit_generator(datagen.flow(X_train, Y_train, batch_size=BATCH_SIZE),
+               steps_per_epoch=X_train.shape[0] //BATCH_SIZE,
+               epochs=EPOCHS,
+               verbose=2,
+               callbacks=[annealer, checkpoint],
+               validation_data=(X_val, Y_val))
+
+#model.save("check.h5")
+#model.fit(X_train,Y_train,batch_size=BATCH_SIZE,steps_per_epoch=X_train.shape[0] // BATCH_SIZE, epochs=EPOCHS)
+