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- from collections import OrderedDict
- import cv2 as cv
- import numpy as np
- from .stitching_error import StitchingError
- class CameraAdjuster:
- """https://docs.opencv.org/4.x/d5/d56/classcv_1_1detail_1_1BundleAdjusterBase.html""" # noqa
- CAMERA_ADJUSTER_CHOICES = OrderedDict()
- CAMERA_ADJUSTER_CHOICES['ray'] = cv.detail_BundleAdjusterRay
- CAMERA_ADJUSTER_CHOICES['reproj'] = cv.detail_BundleAdjusterReproj
- CAMERA_ADJUSTER_CHOICES['affine'] = cv.detail_BundleAdjusterAffinePartial
- CAMERA_ADJUSTER_CHOICES['no'] = cv.detail_NoBundleAdjuster
- DEFAULT_CAMERA_ADJUSTER = list(CAMERA_ADJUSTER_CHOICES.keys())[0]
- DEFAULT_REFINEMENT_MASK = "xxxxx"
- def __init__(self,
- adjuster=DEFAULT_CAMERA_ADJUSTER,
- refinement_mask=DEFAULT_REFINEMENT_MASK):
- self.adjuster = CameraAdjuster.CAMERA_ADJUSTER_CHOICES[adjuster]()
- self.set_refinement_mask(refinement_mask)
- self.adjuster.setConfThresh(1)
- def set_refinement_mask(self, refinement_mask):
- mask_matrix = np.zeros((3, 3), np.uint8)
- if refinement_mask[0] == 'x':
- mask_matrix[0, 0] = 1
- if refinement_mask[1] == 'x':
- mask_matrix[0, 1] = 1
- if refinement_mask[2] == 'x':
- mask_matrix[0, 2] = 1
- if refinement_mask[3] == 'x':
- mask_matrix[1, 1] = 1
- if refinement_mask[4] == 'x':
- mask_matrix[1, 2] = 1
- self.adjuster.setRefinementMask(mask_matrix)
- def adjust(self, features, pairwise_matches, estimated_cameras):
- b, cameras = self.adjuster.apply(features,
- pairwise_matches,
- estimated_cameras)
- if not b:
- raise StitchingError("Camera parameters adjusting failed.")
- return cameras
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