V-Net in Keras and tensorflow

Keras.ipynb

Load data.ipynb

What dataset was your model used on?

It's the PROMISE12 dataset.

Hello,
Thanks for your implementation.

With;
model.fit(X, y, batch_size=4, epochs=5, verbose=1)
I have following exception;
InvalidArgumentError (see above for traceback): Incompatible shapes: [8388608] vs. [1048576]

• I am using same dataset with yours.
• Load data.ipynb works fine.
• I have tried with different batch_size, i.e. 4,5,10,50
• The model's summary is exactly same with yours.

I just wonder, do you have any idea, why I am getting this exception?

Thank you, regards.

• Hakan

hello,
I run U-Net using dice loss, but the predicted images are all white. Do you know what's wrong?
def dice_coef(y_true, y_pred):
smooth = 1
y_true_f = K.flatten(y_true)
y_pred_f = K.flatten(y_pred)
intersection = K.sum(y_true_f * y_pred_f)
return (2. * intersection +smooth) / (K.sum(y_true_f) + K.sum(y_pred_f) +smooth)

def dice_coef_loss(y_true, y_pred):
print("dice loss")
return 1-dice_coef(y_true, y_pred)
....
model.compile(optimizer = Adam(lr = 1e-5), loss = dice_coef_loss, metrics = ['accuracy'])