The following are code examples for showing how to use . They are extracted from open source Python projects. You can vote up the examples you like or vote down the exmaples you don’t like. You can also save this page to your account.
Example 1
def dsplit(ary, indices_or_sections):
"""Splits an array into multiple sub arrays along the third axis.
This is equivalent to ``split`` with ``axis=2``.
.. seealso:: :func:`cupy.split` for more detail, :func:`numpy.dsplit`
"""
if ary.ndim <= 2:
raise ValueError('Cannot dsplit an array with less than 3 dimensions')
return split(ary, indices_or_sections, 2) Example 2
def vsplit(ary, indices_or_sections):
"""Splits an array into multiple sub arrays along the first axis.
This is equivalent to ``split`` with ``axis=0``.
.. seealso:: :func:`cupy.split` for more detail, :func:`numpy.dsplit`
"""
if ary.ndim <= 1:
raise ValueError('Cannot vsplit an array with less than 2 dimensions')
return split(ary, indices_or_sections, 0) Example 3
def char2wordBB(self, charBB, text):
"""
Converts character bounding-boxes to word-level
bounding-boxes.
charBB : 2x4xn matrix of BB coordinates
text : the text string
output : 2x4xm matrix of BB coordinates,
where, m == number of words.
"""
wrds = text.split()
bb_idx = np.r_[0, np.cumsum([len(w) for w in wrds])]
wordBB = np.zeros((2,4,len(wrds)), 'float32')
for i in xrange(len(wrds)):
cc = charBB[:,:,bb_idx[i]:bb_idx[i+1]]
# fit a rotated-rectangle:
# change shape from 2x4xn_i -> (4*n_i)x2
cc = np.squeeze(np.concatenate(np.dsplit(cc,cc.shape[-1]),axis=1)).T.astype('float32')
rect = cv2.minAreaRect(cc.copy())
box = np.array(cv2.cv.BoxPoints(rect))
# find the permutation of box-coordinates which
# are "aligned" appropriately with the character-bb.
# (exhaustive search over all possible assignments):
cc_tblr = np.c_[cc[0,:],
cc[-3,:],
cc[-2,:],
cc[3,:]].T
perm4 = np.array(list(itertools.permutations(np.arange(4))))
dists = []
for pidx in xrange(perm4.shape[0]):
d = np.sum(np.linalg.norm(box[perm4[pidx],:]-cc_tblr,axis=1))
dists.append(d)
wordBB[:,:,i] = box[perm4[np.argmin(dists)],:].T
return wordBB Example 4
def dsplit(ary, indices_or_sections):
"""Splits an array into multiple sub arrays along the third axis.
This is equivalent to ``split`` with ``axis=2``.
.. seealso:: :func:`cupy.split` for more detail, :func:`numpy.dsplit`
"""
if ary.ndim <= 2:
raise ValueError('Cannot dsplit an array with less than 3 dimensions')
return split(ary, indices_or_sections, 2) Example 5
def vsplit(ary, indices_or_sections):
"""Splits an array into multiple sub arrays along the first axis.
This is equivalent to ``split`` with ``axis=0``.
.. seealso:: :func:`cupy.split` for more detail, :func:`numpy.dsplit`
"""
if ary.ndim <= 1:
raise ValueError('Cannot vsplit an array with less than 2 dimensions')
return split(ary, indices_or_sections, 0) Example 6
def _ros_read_images(self, stream_buffer, number, staleness_limit = 10.):
""" Reads images from a stream buffer
Parameters
----------
stream_buffer : string
absolute path to the image buffer service
number : int
The number of frames to get. Must be less than the image buffer service's
current buffer size
staleness_limit : float, optional
Max value of how many seconds old the oldest image is. If the oldest image
grabbed is older than this value, a RuntimeError is thrown.
If None, staleness is ignored.
Returns
-------
List of nump.ndarray objects, each one an image
Images are in reverse chronological order (newest first)
"""
rospy.wait_for_service(stream_buffer, timeout = self.timeout)
ros_image_buffer = rospy.ServiceProxy(stream_buffer, ImageBuffer)
ret = ros_image_buffer(number, 1)
if not staleness_limit == None:
if ret.timestamps[-1] > staleness_limit:
raise RuntimeError("Got data {0} seconds old, more than allowed {1} seconds"
.format(ret.timestamps[-1], staleness_limit))
data = ret.data.reshape(ret.data_dim1, ret.data_dim2, ret.data_dim3).astype(ret.dtype)
# Special handling for 1 element, since dstack's behavior is different
if number == 1:
return [data]
return np.dsplit(data, number) Example 7
def _rpc(self, x):
L, P, H = np.dsplit(x, 3)
return np.dstack([np.ones((x.shape[0], x.shape[1]), dtype=np.float32), L, P, H, L*P, L*H, P*H, L**2, P**2, H**2,
L*P*H, L**3, L*(P**2), L*(H**2), (L**2)*P, P**3, P*(H**2),
(L**2)*H, (P**2)*H, H**3]) 