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Open Source Computer Vision Library
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72 lines
2.9 KiB
72 lines
2.9 KiB
3 years ago
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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, scale=1):
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self.warper_type = warper_type
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self.warper = cv.PyRotationWarper(warper_type, scale)
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self.scale = scale
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def warp_images_and_image_masks(self, imgs, cameras, scale=None, aspect=1):
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self.update_scale(scale)
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for img, camera in zip(imgs, cameras):
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yield self.warp_image_and_image_mask(img, camera, scale, aspect)
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def warp_image_and_image_mask(self, img, camera, scale=None, aspect=1):
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self.update_scale(scale)
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corner, img_warped = self.warp_image(img, camera, aspect)
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mask = 255 * np.ones((img.shape[0], img.shape[1]), np.uint8)
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_, mask_warped = self.warp_image(mask, camera, aspect, mask=True)
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return img_warped, mask_warped, corner
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def warp_image(self, image, camera, aspect=1, mask=False):
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if mask:
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interp_mode = cv.INTER_NEAREST
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border_mode = cv.BORDER_CONSTANT
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else:
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interp_mode = cv.INTER_LINEAR
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border_mode = cv.BORDER_REFLECT
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corner, warped_image = self.warper.warp(image,
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Warper.get_K(camera, aspect),
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camera.R,
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interp_mode,
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border_mode)
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return corner, warped_image
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def warp_roi(self, width, height, camera, scale=None, aspect=1):
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self.update_scale(scale)
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roi = (width, height)
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K = Warper.get_K(camera, aspect)
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return self.warper.warpRoi(roi, K, camera.R)
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def update_scale(self, scale):
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if scale is not None and scale != self.scale:
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self.warper = cv.PyRotationWarper(self.warper_type, scale) # setScale not working: https://docs.opencv.org/master/d5/d76/classcv_1_1PyRotationWarper.html#a90b000bb75f95294f9b0b6ec9859eb55
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self.scale = scale
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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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