In keras fit function
model.fit(X_train, y_train, nb_epoch=20, batch_size=16)
How should I input the data when i have more columns?
I want to input image, and detect object of class 1 on it. So the output is (x, y, width, height)
The input image should be 416 x 416 x 3 and output matrix should be 13x13x4 so i want to detect up to 169 objects.
Should the
X_train
variable be loaded set of images ( so it will be 4 dimensional array of N x 416 x 416 x 3 )
and
y_train
be 2D array of N x 4 , where 4 represents ( x ,y , width, height ) ?
If so what do i have to pass in validation_data arguments?
I am really confused.