Amartya Kalapahar amartya-k

## dice_loss_for_keras.py
"""
Here is a dice loss for keras which is smoothed to approximate a linear (L1) loss.
It ranges from 1 to 0 (no error), and returns results similar to binary crossentropy
"""

# define custom loss and metric functions

from keras import backend as K

def dice_coef(y_true, y_pred, smooth=1):
	"""
	Here is a dice loss for keras which is smoothed to approximate a linear (L1) loss.
	It ranges from 1 to 0 (no error), and returns results similar to binary crossentropy
	"""

	# define custom loss and metric functions

	from keras import backend as K

	def dice_coef(y_true, y_pred, smooth=1):