Open Source Computer Vision Library https://opencv.org/
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import cv2 as cv
import numpy as np
class Warper:
WARP_TYPE_CHOICES = ('spherical', 'plane', 'affine', 'cylindrical',
'fisheye', 'stereographic', 'compressedPlaneA2B1',
'compressedPlaneA1.5B1',
'compressedPlanePortraitA2B1',
'compressedPlanePortraitA1.5B1',
'paniniA2B1', 'paniniA1.5B1', 'paniniPortraitA2B1',
'paniniPortraitA1.5B1', 'mercator',
'transverseMercator')
DEFAULT_WARP_TYPE = 'spherical'
def __init__(self, warper_type=DEFAULT_WARP_TYPE, scale=1):
self.warper_type = warper_type
self.warper = cv.PyRotationWarper(warper_type, scale)
self.scale = scale
def warp_images_and_image_masks(self, imgs, cameras, scale=None, aspect=1):
self.update_scale(scale)
for img, camera in zip(imgs, cameras):
yield self.warp_image_and_image_mask(img, camera, scale, aspect)
def warp_image_and_image_mask(self, img, camera, scale=None, aspect=1):
self.update_scale(scale)
corner, img_warped = self.warp_image(img, camera, aspect)
mask = 255 * np.ones((img.shape[0], img.shape[1]), np.uint8)
_, mask_warped = self.warp_image(mask, camera, aspect, mask=True)
return img_warped, mask_warped, corner
def warp_image(self, image, camera, aspect=1, mask=False):
if mask:
interp_mode = cv.INTER_NEAREST
border_mode = cv.BORDER_CONSTANT
else:
interp_mode = cv.INTER_LINEAR
border_mode = cv.BORDER_REFLECT
corner, warped_image = self.warper.warp(image,
Warper.get_K(camera, aspect),
camera.R,
interp_mode,
border_mode)
return corner, warped_image
def warp_roi(self, width, height, camera, scale=None, aspect=1):
self.update_scale(scale)
roi = (width, height)
K = Warper.get_K(camera, aspect)
return self.warper.warpRoi(roi, K, camera.R)
def update_scale(self, scale):
if scale is not None and scale != self.scale:
self.warper = cv.PyRotationWarper(self.warper_type, scale) # setScale not working: https://docs.opencv.org/4.x/d5/d76/classcv_1_1PyRotationWarper.html#a90b000bb75f95294f9b0b6ec9859eb55
self.scale = scale
@staticmethod
def get_K(camera, aspect=1):
K = camera.K().astype(np.float32)
""" Modification of intrinsic parameters needed if cameras were
obtained on different scale than the scale of the Images which should
be warped """
K[0, 0] *= aspect
K[0, 2] *= aspect
K[1, 1] *= aspect
K[1, 2] *= aspect
return K