Numpy normalizuj
def normalize(v):
norm = np.linalg.norm(v)
if norm == 0:
return v
return v / norm
Ferry_Morris
def normalize(v):
norm = np.linalg.norm(v)
if norm == 0:
return v
return v / norm
norm = np.linalg.norm(an_array_to_normalize)
normal_array = an_array_to_normalize/norm
or for pixels to be obtained in my case. This can be used to map values to another scale from the current scale of values.
scaled_array = (array/np.float(np.max(array)) )*255.