--- a
+++ b/Segmentation/config.py
@@ -0,0 +1,29 @@
+import numpy as np
+import os
+from sklearn.model_selection import KFold
+import tensorflow as tf
+
+
+file_list = np.asarray(os.listdir("Submission_segmentation/data/WCEBleedGen/WCEBleedGen/bleeding/Images"))
+image_path = "Submission_segmentation/data/WCEBleedGen/WCEBleedGen/bleeding/Images/" 
+mask_path = "Submission_segmentation/data/WCEBleedGen/WCEBleedGen/bleeding/Annotations/"
+
+batchsize = 30
+data_size = len(file_list)
+num_epoch = 5
+splits = 10
+kf = KFold(n_splits=splits)
+valsize = data_size // splits
+trainsize = data_size - valsize
+
+my_model = "efficientnetb1"
+data_num = np.arange(data_size)
+
+img_size = (256, 256)
+num_classes = 3
+
+reduce_lr = tf.keras.callbacks.ReduceLROnPlateau(
+    monitor='val_loss', factor=0.1, patience=3, verbose=0, mode='min',
+    min_delta=0.0001, cooldown=4, min_lr=0
+)
+print(file_list)
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