def __call__(self, sample):
from envmap import EnvironmentMap
image = EnvironmentMap(64, 'LatLong')
image.data = sample
rotation = self.random_direction()
img_hdr = image.rotate('DCM', rotation).data.astype('float32')
sample = img_hdr
return sample
def rotate_image(data, rotation):
"""
rotation images with skylibs
:param data: image data will be rotated, dimension is 4 [ x , width, height, 3]
:return : weather rotated the images
"""
if [0.0, 0.0] == rotation:
return False
rotation_matrix = np.zeros([3, 3])
spherical2dcm(rotation, rotation_matrix)
envmap = EnvironmentMap(data, format_='latlong')
new_image = envmap.rotate("DCM", rotation_matrix).data
data[:] = new_image.astype(np.uint8)
return True
def rotate_image(self, data):
"""
rotation images with skylibs
:param data: image data will be rotated, dimension is 4 [ x , width, height, 3]
:return : weather rotated the images
"""
if [0.0, 0.0] == self.rotation:
return data
rotation_matrix = np.zeros([3, 3])
self.spherical2dcm(self.rotation, rotation_matrix)
for i in range(0, np.shape(data)[0]):
if i % self.show_infor_interval == 0:
self.show_info(
"Rotating image with 'rotate_image' function, index is {}."
.format(i))
# show_image(image)
image = data[i]
envmap = EnvironmentMap(image, format_='latlong')
new_image = envmap.rotate("DCM", rotation_matrix).data
new_image = new_image.astype(np.uint8)
data[i] = new_image
return data
def rotate(self, rotation):
envmap = EnvironmentMap(self.img, 'latlong')
envmap.rotate('DCM', rotation.as_matrix())
self.img = envmap.data
