2D_to_3D_Image.py

# from skimage import transform
from skimage.transform import warp, ProjectiveTransform
import matplotlib.pyplot as plt
import cv2
import numpy as np

f1 = plt.figure(1)
img = cv2.imread('DisparityL.jpg', 0)
plt.imshow(img,'gray')

theta = np.deg2rad(20)
tx = 0
ty = 0

S, C = np.sin(theta), np.cos(theta)

# Rotation matrix, angle theta, translation tx, ty
H = np.array([[C, -S, tx],
              [S,  C, ty],
              [0,  0, 1]])

# Translation matrix to shift the image center to the origin
print(img.shape)
r, c = img.shape
T = np.array([[1, 0, -c / 2.],
               [0, 1, -r / 2.],
              [0, 0, 1]])

# Skew, for perspective
S = np.array([[1, 0, 0],
              [0, 1.3, 0],
              [0, 1e-3, 1]])

trans = ProjectiveTransform(T)
img_rot = warp(img, H)
img_rot_center_skew = warp(img, S.dot(np.linalg.inv(T).dot(H).dot(T)))

index = 2
for i in [img, img_rot, img_rot_center_skew]:
	f1 = plt.figure(index)
	f, ax = plt.subplots(figsize=(20,20))
	ax.imshow(i, cmap=plt.cm.gray, interpolation='nearest')
	index = index + 1
plt.show()