def map_to_input_space(self, scope):
patch_shape = T.cast(self.cropper.patch_shape, floatX)
image_shape = scope.x_shape
if isinstance(image_shape, tuple):
# for featurelevel_UCF101
image_shape = image_shape[1][:, 1:]
scope.true_location, scope.true_scale = static_map_to_input_space(
scope.raw_location, scope.raw_scale, patch_shape, image_shape)
# measure the extent to which raw_location is outside the image
scope.excursion = util.rectify(scope.raw_location**2 - 1)
def model(X, w_L1, w_L2, w_L3, w_L4, p_drop_conv, p_drop_hidden):
crossnormalizer = crossnorm(alpha=1e-4, k=2, beta=0.75, n=9)
l1b = rectify(cuconv(X, w_L1, border_mode=(5, 5)))
l1 = cupool(l1b, (3, 3), stride=(2, 2))
l1 = crossnormalizer(l1)
l1 = dropout(l1, p_drop_conv)
l2b = rectify(cuconv(l1, w_L2, border_mode='full'))
l2 = cupool(l2b, (3, 3), stride=(2, 2))
l2 = crossnormalizer(l2)
l2 = dropout(l2, p_drop_conv)
l3b = rectify(cuconv(l2, w_L3, border_mode='full'))
l3 = cupool(l3b, (3, 3), stride=(2, 2))
l3 = crossnormalizer(l3)
l4 = T.flatten(l3, outdim=2)
pyx = dropout(l4, p_drop_hidden)
pyx = softmax(T.dot(pyx, w_L4))
return l1, l2, l3, pyx
def get_approx_poly(card, do_rectify=True, image=None):
perimeter = cv2.arcLength(card, True)
approximated_poly = cv2.approxPolyDP(card, 0.1 * perimeter, True)
# TODO: deal with case where approximated_poly does not have 4 points (3 or 5)
# kl = len(approximated_poly)
# kif l != 4:
# kfor p in approximated_poly:
# kcv2.circle(image, (p[0][0], p[0][1]), 3, (255,0,0), 5)
# kutil.show(image)
# k# get rectified points in clockwise order
if do_rectify:
reapproximated_poly = util.rectify(approximated_poly)
if reapproximated_poly.all():
approximated_poly = reapproximated_poly
else:
# print 'Not rectified!'
return None
return approximated_poly
