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# Copyright (C) 2024-present Naver Corporation. All rights reserved.
# Licensed under CC BY-NC-SA 4.0 (non-commercial use only).
#
# --------------------------------------------------------
# main pnp code
# --------------------------------------------------------
import numpy as np
import quaternion
import cv2
from packaging import version
from dust3r.utils.geometry import opencv_to_colmap_intrinsics
try:
import poselib # noqa
HAS_POSELIB = True
except Exception as e:
HAS_POSELIB = False
try:
import pycolmap # noqa
version_number = pycolmap.__version__
if version.parse(version_number) < version.parse("0.5.0"):
HAS_PYCOLMAP = False
else:
HAS_PYCOLMAP = True
except Exception as e:
HAS_PYCOLMAP = False
def run_pnp(pts2D, pts3D, K, distortion = None, mode='cv2', reprojectionError=5, img_size = None):
"""
use OPENCV model for distortion (4 values)
"""
assert mode in ['cv2', 'poselib', 'pycolmap']
try:
if len(pts2D) > 4 and mode == "cv2":
confidence = 0.9999
iterationsCount = 10_000
if distortion is not None:
cv2_pts2ds = np.copy(pts2D)
cv2_pts2ds = cv2.undistortPoints(cv2_pts2ds, K, np.array(distortion), R=None, P=K)
pts2D = cv2_pts2ds.reshape((-1, 2))
success, r_pose, t_pose, _ = cv2.solvePnPRansac(pts3D, pts2D, K, None, flags=cv2.SOLVEPNP_SQPNP,
iterationsCount=iterationsCount,
reprojectionError=reprojectionError,
confidence=confidence)
if not success:
return False, None
r_pose = cv2.Rodrigues(r_pose)[0] # world2cam == world2cam2
RT = np.r_[np.c_[r_pose, t_pose], [(0,0,0,1)]] # world2cam2
return True, np.linalg.inv(RT) # cam2toworld
elif len(pts2D) > 4 and mode == "poselib":
assert HAS_POSELIB
confidence = 0.9999
iterationsCount = 10_000
# NOTE: `Camera` struct currently contains `width`/`height` fields,
# however these are not used anywhere in the code-base and are provided simply to be consistent with COLMAP.
# so we put garbage in there
colmap_intrinsics = opencv_to_colmap_intrinsics(K)
fx = colmap_intrinsics[0, 0]
fy = colmap_intrinsics[1, 1]
cx = colmap_intrinsics[0, 2]
cy = colmap_intrinsics[1, 2]
width = img_size[0] if img_size is not None else int(cx*2)
height = img_size[1] if img_size is not None else int(cy*2)
if distortion is None:
camera = {'model': 'PINHOLE', 'width': width, 'height': height, 'params': [fx, fy, cx, cy]}
else:
camera = {'model': 'OPENCV', 'width': width, 'height': height,
'params': [fx, fy, cx, cy] + distortion}
pts2D = np.copy(pts2D)
pts2D[:, 0] += 0.5
pts2D[:, 1] += 0.5
pose, _ = poselib.estimate_absolute_pose(pts2D, pts3D, camera,
{'max_reproj_error': reprojectionError,
'max_iterations': iterationsCount,
'success_prob': confidence}, {})
if pose is None:
return False, None
RT = pose.Rt # (3x4)
RT = np.r_[RT, [(0,0,0,1)]] # world2cam
return True, np.linalg.inv(RT) # cam2toworld
elif len(pts2D) > 4 and mode == "pycolmap":
assert HAS_PYCOLMAP
assert img_size is not None
pts2D = np.copy(pts2D)
pts2D[:, 0] += 0.5
pts2D[:, 1] += 0.5
colmap_intrinsics = opencv_to_colmap_intrinsics(K)
fx = colmap_intrinsics[0, 0]
fy = colmap_intrinsics[1, 1]
cx = colmap_intrinsics[0, 2]
cy = colmap_intrinsics[1, 2]
width = img_size[0]
height = img_size[1]
if distortion is None:
camera_dict = {'model': 'PINHOLE', 'width': width, 'height': height, 'params': [fx, fy, cx, cy]}
else:
camera_dict = {'model': 'OPENCV', 'width': width, 'height': height,
'params': [fx, fy, cx, cy] + distortion}
pycolmap_camera = pycolmap.Camera(
model=camera_dict['model'], width=camera_dict['width'], height=camera_dict['height'],
params=camera_dict['params'])
pycolmap_estimation_options = dict(ransac=dict(max_error=reprojectionError, min_inlier_ratio=0.01,
min_num_trials=1000, max_num_trials=100000,
confidence=0.9999))
pycolmap_refinement_options=dict(refine_focal_length=False, refine_extra_params=False)
ret = pycolmap.absolute_pose_estimation(pts2D, pts3D, pycolmap_camera,
estimation_options=pycolmap_estimation_options,
refinement_options=pycolmap_refinement_options)
if ret is None:
ret = {'success': False}
else:
ret['success'] = True
if callable(ret['cam_from_world'].matrix):
retmat = ret['cam_from_world'].matrix()
else:
retmat = ret['cam_from_world'].matrix
ret['qvec'] = quaternion.from_rotation_matrix(retmat[:3, :3])
ret['tvec'] = retmat[:3, 3]
if not (ret['success'] and ret['num_inliers'] > 0):
success = False
pose = None
else:
success = True
pr_world_to_querycam = np.r_[ret['cam_from_world'].matrix(), [(0,0,0,1)]]
pose = np.linalg.inv(pr_world_to_querycam)
return success, pose
else:
return False, None
except Exception as e:
print(f'error during pnp: {e}')
return False, None |