def derajat2(gray, type):
result = np.zeros(gray.shape, dtype=np.float)
if type == 'kirsch':
kernel = [
[5, 5, 5],
[-3, 0, -3],
[-3, -3, -3],
]
elif type == 'prewitt':
kernel = [
[-1, 0, 1],
[-1, 0, 1],
[-1, 0, 1],
]
results = []
for i in range(0, 8):
results.append(convolve(gray, kernel))
kernel[:] = nph.rot45(np.array(kernel))
for i in range(0, 8):
result[:] = np.maximum(result, results[i])
result[:] = normalize(result)
return result.round().astype(np.uint8)
def kirsch(gray):
dummy = [[0, 0, 0], [0, 0, 0], [0, 0, 0]]
kernel = np.array([[5, 5, 5,],
[-3, 0, -3],
[-3, -3, -3]])
results = []
for i in range(0, 8):
results.append(operate(gray, kernel, dummy))
kernel[:] = nph.rot45(kernel)
result = results[0]
for i in range(1, 8):
result[:] = np.maximum(result, results[i])
return normalize(result).round().astype(np.uint8)