def computeAngles(im):
''' Return an image that holds the angle of the smallest eigenvector of the structure tensor at each pixel.
If you have a 3 channel image as input, just set all three channels to be the same value theta.'''
out = np.zeros_like(im)
tensor = helper.computeTensor(im)
for y,x in imIter(tensor):
eigenVecs = np.linalg.eigh(tensor[y,x])[1]
out[y,x] = min(np.arctan2(eigenVecs[0][0], eigenVecs[0][1]), np.arctan2(eigenVecs[1][0], eigenVecs[1][1]))
return out
def computeAngles(im):
'''Return an image that holds the angle of the smallest eigenvector of the structure tensor at each pixel. If you have a 3 channel image as input, just set all three channels to be the same value theta.'''
thetas = np.zeros(im.shape)
tensors = helper.computeTensor(im, sigmaG=3, factor=5)
for y in xrange(im.shape[0]):
for x in xrange(im.shape[1]):
eigvals, eigvecs = np.linalg.eigh(tensors[y, x])
vec = eigvecs[:, np.argmin(eigvals)]
thetas[y, x] = np.arctan2(vec[0], vec[1]) + math.pi
return thetas
def computeAngles(im):
'''Return an image that holds the angle of the smallest eigenvector of the structure tensor at each pixel. If you have a 3 channel image as input, just set all three channels to be the same value theta.'''
out = im.copy()
tensor = helper.computeTensor(im, 3, 5)
for y,x in helper.imIter(tensor):
M = tensor[y,x]
w, v = np.linalg.eigh( M )
vLarge = v[:, np.argmax(np.abs(w))]
angle = np.arctan2( vLarge[1], vLarge[0]) + math.pi
out[y,x] = np.array([angle, angle, angle])
return out
def computeAngles(im):
'''Return an image that holds the angle of the smallest eigenvector of the structure tensor at each pixel. If you have a 3 channel image as input, just set all three channels to be the same value theta.'''
angles = np.zeros(im.shape)
# default function gives an error
tensor = helper.computeTensor(im, sigmaG=3, factor=5, debug=False)
# iterate through whole thing
for y in xrange(im.shape[0]):
for x in xrange(im.shape[1]):
eigenvalues, eigenvectors = np.linalg.eigh(tensor[y, x])
min_vec = eigenvectors[:, np.argmin(
eigenvalues)] # indexing syntax wonky!
# add pi here to offset negative angles
theta = np.arctan2(min_vec[0], min_vec[1]) + math.pi
angles[y, x] = theta
return angles
