Open Source Computer Vision Library https://opencv.org/
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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