80 lines
3 KiB
Python
80 lines
3 KiB
Python
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from statistics import median
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import cv2 as cv
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import numpy as np
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class Warper:
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WARP_TYPE_CHOICES = ('spherical', 'plane', 'affine', 'cylindrical',
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'fisheye', 'stereographic', 'compressedPlaneA2B1',
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'compressedPlaneA1.5B1',
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'compressedPlanePortraitA2B1',
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'compressedPlanePortraitA1.5B1',
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'paniniA2B1', 'paniniA1.5B1', 'paniniPortraitA2B1',
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'paniniPortraitA1.5B1', 'mercator',
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'transverseMercator')
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DEFAULT_WARP_TYPE = 'spherical'
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def __init__(self, warper_type=DEFAULT_WARP_TYPE):
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self.warper_type = warper_type
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self.scale = None
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def set_scale(self, cameras):
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focals = [cam.focal for cam in cameras]
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self.scale = median(focals)
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def warp_images(self, imgs, cameras, aspect=1):
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for img, camera in zip(imgs, cameras):
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yield self.warp_image(img, camera, aspect)
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def warp_image(self, img, camera, aspect=1):
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warper = cv.PyRotationWarper(self.warper_type, self.scale*aspect)
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_, warped_image = warper.warp(img,
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Warper.get_K(camera, aspect),
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camera.R,
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cv.INTER_LINEAR,
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cv.BORDER_REFLECT)
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return warped_image
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def create_and_warp_masks(self, sizes, cameras, aspect=1):
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for size, camera in zip(sizes, cameras):
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yield self.create_and_warp_mask(size, camera, aspect)
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def create_and_warp_mask(self, size, camera, aspect=1):
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warper = cv.PyRotationWarper(self.warper_type, self.scale*aspect)
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mask = 255 * np.ones((size[1], size[0]), np.uint8)
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_, warped_mask = warper.warp(mask,
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Warper.get_K(camera, aspect),
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camera.R,
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cv.INTER_NEAREST,
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cv.BORDER_CONSTANT)
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return warped_mask
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def warp_rois(self, sizes, cameras, aspect=1):
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roi_corners = []
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roi_sizes = []
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for size, camera in zip(sizes, cameras):
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roi = self.warp_roi(size, camera, aspect)
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roi_corners.append(roi[0:2])
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roi_sizes.append(roi[2:4])
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return roi_corners, roi_sizes
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def warp_roi(self, size, camera, aspect=1):
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warper = cv.PyRotationWarper(self.warper_type, self.scale*aspect)
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K = Warper.get_K(camera, aspect)
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return warper.warpRoi(size, K, camera.R)
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@staticmethod
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def get_K(camera, aspect=1):
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K = camera.K().astype(np.float32)
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""" Modification of intrinsic parameters needed if cameras were
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obtained on different scale than the scale of the Images which should
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be warped """
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K[0, 0] *= aspect
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K[0, 2] *= aspect
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K[1, 1] *= aspect
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K[1, 2] *= aspect
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return K
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