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Open Source Computer Vision Library
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71 lines
2.9 KiB
71 lines
2.9 KiB
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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