# Copyright (C) 2019 Titus Cieslewski, RPG, University of Zurich, Switzerland
# You can contact the author at <titus at ifi dot uzh dot ch>
# Copyright (C) 2019 Michael Bloesch,
# Dept. of Computing, Imperial College London, United Kingdom
# Copyright (C) 2019 Davide Scaramuzza, RPG, University of Zurich, Switzerland
#
# This file is part of imips_open.
#
# imips_open is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# imips_open is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with imips_open. If not, see <http:#www.gnu.org/licenses/>.
import copy
import cv2
import math
import numpy as np
import matplotlib.pyplot as plt
def generateHomography(debug_plot=False, ang_range=1., sc_range=1.):
angle = ang_range * (np.random.random() - 0.5) * 2 * math.pi
scale = 2 ** ((np.random.random() - 0.5) * sc_range)
if debug_plot:
print('Angle %f scale %f' % (np.rad2deg(angle), scale))
R = scale * np.array([[np.cos(angle), -np.sin(angle)],
[np.sin(angle), np.cos(angle)]])
result = np.eye(3)
result[:2, :2] = R
return result
def shiftHomography(shift_xy):
result = np.eye(3)
result [:2, 2] = shift_xy
return result
def applyHomographyAtCenter(image, origin_homography):
center_rc = np.array(image.shape) / 2
center_xy = np.flip(center_rc, axis=0)
shift = shiftHomography(-center_xy)
unshift = shiftHomography(center_xy)
H = np.dot(unshift, np.dot(origin_homography, shift))
return cv2.warpPerspective(
image, H, dsize=tuple([image.shape[1], image.shape[0]])), H
def augmentHpatchPair(pair, ang_range=1., sc_range=1.):
result = copy.deepcopy(pair)
origin_H = generateHomography(ang_range=ang_range, sc_range=sc_range)
result.im[1], H = applyHomographyAtCenter(result.im[1], origin_H)
result.H = np.dot(H, result.H)
return result
def testHpatchPair(pair):
plt.figure()
plt.imshow(pair.im[1])
plt.figure()
plt.imshow(cv2.warpPerspective(
pair.im[0], pair.H, dsize=tuple(
[pair.im[1].shape[1], pair.im[1].shape[0]])))
