I have an image as a 2D numpy array that i wish to calculate gradient of
gx = np.zeros((frame.shape[0]-2, frame.shape[1]-2), dtype='int8')
gy = np.zeros((frame.shape[0]-2, frame.shape[1]-2), dtype='int8')
for i in range(1, frame.shape[0]-1):
for j in range(1, frame.shape[1]-1):
gx[i-1][j-1] = int(frame[i+1][j]) - int(frame[i-1][j])
gy[i-1][j-1] = int(frame[i][j+1]) - int(frame[i][j-1])
is there a way to use numpy.vectorize
function for faster calculation of the above snippet in python 3?
question from:
https://stackoverflow.com/questions/65916621/inter-array-operations-in-python-using-numpy 与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…