loss.py

import tensorflow.keras.backend as K                                        

def dice_coef(y_true, y_pred):
    y_truef=K.flatten(y_true)
    y_predf=K.flatten(y_pred)
    And=K.sum(y_truef* y_predf)
    return((2* And + 100) / (K.sum(y_truef) + K.sum(y_predf) + 100))

def dice_coef_loss(y_true, y_pred):
    return 1-dice_coef(y_true, y_pred)

def iou(y_true, y_pred):
    intersection = K.sum(y_true * y_pred)
    sum_ = K.sum(y_true + y_pred)
    jac = (intersection + 100) / (sum_ - intersection + 100)
    return jac