def rotate_im(im, theta):
grid = getGrid([28, 28])
grid = rotate_grid_2D(grid, theta)
grid += 13.5
data = linear_interpolation_2D(im, grid)
data = np.reshape(data, [28, 28])
return data.astype('float32')
def random_rotation(data):
rot = np.random.rand() * 360 # Random rotation
grid = getGrid([80, 80])
grid = rotate_grid_2D(grid, rot)
grid += 39.5
data = linear_interpolation_2D(data, grid)
data = np.reshape(data, [80, 80])
data = data / float(np.max(data))
return data.astype('float32')
def random_rotation(data, width = 28, height = 28, channels = 3):
rot = np.random.rand() * 360 # Random rotation
grid = getGrid([width, height])
grid = rotate_grid_2D(grid, rot)
grid += 13.5
if len(data.shape) > 1:
data = linear_interpolation_2D(data, grid)
data = np.reshape(data, [width, height, channels])
print('data.shape ', data.shape, 'data[0].shape', data[0].shape,
'data[:,:,0].shape', data[:,:,0].shape)
data[:, :, 0] = data[:, :, 0] / float(np.max(data[:, :, 0]))
data[:, :, 1] = data[:, :, 1] / float(np.max(data[:, :, 1]))
data[:, :, 2] = data[:, :, 2] / float(np.max(data[:, :, 2]))
return data.astype('float32')
def rotate_im(im, theta, width=28, height=28, channels=3):
grid = getGrid([width, height])
grid = rotate_grid_2D(grid, theta)
grid += 13.5
print('rotate_im: im.shape ', im.shape)
data = linear_interpolation_2D(im.T, grid)
print('rotate_im: data.shape ', data.shape)
data = np.reshape(data, [width, height, channels])
#print('data.shape ', data.shape, 'data[0].shape', data[0].shape,
# 'data[:,:,0].shape', data[:, :, 0].shape)
#data[:, :, 0] = data[:, :, 0] / float(np.max(data[:, :, 0]))
#data[:, :, 1] = data[:, :, 1] / float(np.max(data[:, :, 1]))
#data[:, :, 2] = data[:, :, 2] / float(np.max(data[:, :, 2]))
return data.T.astype('float32')