Im in python, I have a list with a length 784 (which i extracted from a 28x28 image ) and now i want to arrange it in a way i can use it in tensor-flow to be used with a trained model but the problem is that the NN needs to have a 28,28 shaped array but my current array is of shape (784,)
I tried to use some for loops for this but i have no luck in successfully creating a system to carry this out , please help
i figured out that i need to use this structure
for i in range(res):
for a in range(0,res):
mnistFormat.append(grascalePix[a]) #mnistFormat is an innitially empty list
#and grascale has my 784 grayscale pixles
but i cant figure out what should go in the range function of the for loop to make this possible
For example lets say i have a sample 4x4 image's pixel list >
grayscalePix = [255,255,255,255,255,100,83,200,255,50,60,255,30,1,46,255]
this is a Row by Row representation , which means the first 4 elements are the first ---- row
i want to arrange them into a list of shape (4,4)
mnistFormat = [255,255,255,255],[255,100,83,200],[255,50,60,255],[30,1,46,255]
Just keep in mind this is sample , the real data is 784 elements long and i dont have much experince in numpy