This repository was archived by the owner on Feb 25, 2025. It is now read-only.
This repository was archived by the owner on Feb 25, 2025. It is now read-only.
estimate_calibrated_two_view_geometry(): incompatible function arguments #292
Description
Hi,
- Win11
- pycolmap 0.6 (since there is a known problem with pycolmap 3.10.0 and win)
I am facing problems utilizing estimate_calibrated_two_view_geometry, estimate_calibrated_two_view_geometry, estimate_two_view_geometry_pose. Annoyingly, I can't figure out where my error is. Estimating the Essential Matrix with the same arguments works without problems. (see also example script)
Thanks in advance.
Markus
TypeError: estimate_calibrated_two_view_geometry(): incompatible function arguments. The following argument types are supported:
1. (camera1: pycolmap.Camera, points1: numpy.ndarray[numpy.float64[m, 2]], camera2: pycolmap.Camera, points2: numpy.ndarray[numpy.float64[m, 2]], matches: numpy.ndarray[numpy.uint32[m, 2]] = None, options: pycolmap.TwoViewGeometryOptions = <pycolmap.TwoViewGeometryOptions object at 0x000001CDDD695D70>) -> pycolmap.TwoViewGeometry
Invoked with: Camera(camera_id=0, model=SIMPLE_PINHOLE, width=1280, height=720, params=[910.000000, 640.000000, 360.000000] (f, cx, cy)), array([[ 103.25252533, 627.5736084 ],
[ 635.10766602, 293.56375122],
[1170.61694336, 609.92657471],
[ 995.36523438, 359.21173096],
[1038.58496094, 416.06182861],
[1181.74780273, 393.3609314 ],
[ 830.24676514, 512.47650146],
[ 619.87194824, 591.88787842],
[ 814.02850342, 355.37408447],
[ 910.16351318, 650.93408203]]), Camera(camera_id=1, model=SIMPLE_PINHOLE, width=1280, height=720, params=[910.000000, 640.000000, 360.000000] (f, cx, cy)), array([[ 961.42596436, 386.71902466],
[1213.98132324, 658.73760986],
[1173.48864746, 609.75372314],
[ 998.50354004, 362.80661011],
[1038.75439453, 413.33563232],
[1181.22009277, 393.20046997],
[ 829.9644165 , 512.37768555],
[ 616.26953125, 592.09075928],
[ 812.72821045, 356.39505005],
[ 909.18566895, 650.11999512]])
Complete Script (call of estimate_calibrated_two_view_geometry at the end of the script)
from pathlib import Path
from PIL import Image, ImageOps
import numpy as np
import cv2 as cv2
from scipy.spatial.transform import Rotation as R_
import torch
import pycolmap
def mutual_nn_matcher(descriptors1, descriptors2):
# Mutual nearest neighbors (NN) matcher for L2 normalized descriptors.
device = descriptors1.device
sim = descriptors1 @ descriptors2.t()
nn_sim, nn12 = torch.max(sim, dim=1)
nn_dist = torch.sqrt(2 - 2 * nn_sim)
nn21 = torch.max(sim, dim=0)[1]
ids1 = torch.arange(0, sim.shape[0], device=device)
mask = (ids1 == nn21[nn12])
matches = torch.stack([ids1[mask], nn12[mask]])
return matches.t(), nn_dist[mask]
ops = pycolmap.SiftExtractionOptions()
ops.max_num_features = 50
sift = pycolmap.Sift(ops)
fin1 = r"X:\**\ref_image\origin_000000.jpg"
fin2 = r"X:\**\video\origin_000011.jpg"
img1 = Image.open(fin1).convert('RGB')
img11 = np.array(ImageOps.grayscale(img1))
img1 = ImageOps.grayscale(img1)
img1 = np.array(img11).astype(np.float32) / 255.
keypoints1, descriptors1 = sift.extract(img1)
img2 = Image.open(fin2).convert('RGB')
img2 = ImageOps.grayscale(img2)
img2 = np.array(img2).astype(np.float32) / 255.
keypoints2, descriptors2 = sift.extract(img2)
print(keypoints1.shape)
print(keypoints1[:10])
print(keypoints2.shape)
print(keypoints2[:10])
print(descriptors1.device)
matches, distances = mutual_nn_matcher(torch.from_numpy(descriptors1), torch.from_numpy(descriptors2))
print(distances.shape)
print(distances[:10])
print(matches.shape)
print(matches[:10])
sorted_indices = np.argsort(-distances)
sorted_matches = matches[sorted_indices]
sorted_distances = distances[sorted_indices]
print(sorted_distances[:10])
print(sorted_matches[:10])
points1 = keypoints1[sorted_matches[:,0]][:,:2]
points2 = keypoints2[sorted_matches[:,1]][:,:2]
# points1 = keypoints1[:10,:2]
# points2 = keypoints2[:10,:2]
cam = pycolmap.Camera()
cam1 = cam.create(0, pycolmap.CameraModelId.SIMPLE_PINHOLE, 910, 1280, 720)
cam2 = cam.create(1, pycolmap.CameraModelId.SIMPLE_PINHOLE, 910, 1280, 720)
print(cam1.summary)
print(cam1.principal_point_x)
print(cam1.principal_point_y)
print(cam1.focal_length_x)
print(cam1.focal_length_y)
cam_intrinsics = np.diag([cam1.focal_length_x, cam1.focal_length_y, 1])
cam_intrinsics[0,2] = cam1.principal_point_x
cam_intrinsics[1,2] = cam1.principal_point_y
print(cam_intrinsics)
# sys.exit()
# calculating essential matrix with cameras and points seems to work
ops_ransac = pycolmap.RANSACOptions()
essential = pycolmap.essential_matrix_estimation(points1,
points2,
cam1,
cam2,
ops_ransac
)
print(essential.keys())
print(essential["E"])
print("CV2")
R1,R2,t = cv2.decomposeEssentialMat(essential["E"])
print("decomposed Essential Matrix")
print(R1)
print(R_.from_matrix(R1).as_euler('xyz', degrees=True))
print(R2)
print(R_.from_matrix(R2).as_euler('xyz', degrees=True))
print(t)
print(essential["inliers"])
points1_inliers = points1[essential["inliers"]]
points2_inliers = points2[essential["inliers"]]
retval, R, t, mask = cv2.recoverPose(essential["E"], points1_inliers, points2_inliers, cam_intrinsics)
print("Result recoverPose CV2")
print(retval)
print(R)
print(t)
print("Result pycolmap")
print(essential["cam2_from_cam1"].matrix())
print(essential["cam2_from_cam1"].inverse().matrix())
print(essential["cam2_from_cam1"].summary())
print("debug prints: estimate_calibrated_two_view_geometry")
print(points1[:10].astype(np.float64))
print(points2[:10].astype(np.float64))
print()
print(points1[:10].astype(np.float64).shape)
print(points2[:10].astype(np.float64).shape)
print()
print(cam1)
print(cam2)
print()
props = pycolmap.TwoViewGeometryOptions()
print(props.summary())
# all those variants through the same exception.
print("estimate_calibrated_two_view_geometry")
answer = pycolmap.estimate_calibrated_two_view_geometry(cam1, points1[:10].astype(np.float64), cam2, points2[:10].astype(np.float64))
# answer = pycolmap.estimate_calibrated_two_view_geometry(cam1, points1[:10].astype(np.float64), cam2, points2[:10].astype(np.float64), None, props)
# answer = pycolmap.estimate_calibrated_two_view_geometry(cam1, points1[:10].astype(np.float64), cam2, points2[:10].astype(np.float64), None, options = props)
Complete Output
(70, 4)
[[ 1.20958347e+01 2.49640312e+01 1.12905636e+01 2.29283905e+00]
[ 1.20958347e+01 2.49640312e+01 1.12905636e+01 -1.76369226e+00]
[ 6.35107666e+02 2.93563751e+02 1.10032005e+01 3.07449651e+00]
[ 6.35107666e+02 2.93563751e+02 1.10032005e+01 -1.25733212e-01]
[ 1.12632788e+03 3.13299805e+02 1.18385363e+01 2.60598612e+00]
[ 2.36843948e+01 3.23181702e+02 9.90066147e+00 -1.41594875e+00]
[ 8.27308167e+02 3.24141815e+02 1.00310946e+01 1.04846478e+00]
[ 6.04895447e+02 3.27756073e+02 1.00869875e+01 1.54187500e+00]
[ 8.14028503e+02 3.55374084e+02 1.12396946e+01 2.85701305e-02]
[ 5.75664001e+02 3.93533051e+02 1.12058096e+01 7.28527129e-01]]
(65, 4)
[[ 1.0320951e+03 1.2873740e+02 1.0616852e+01 -2.7713996e-01]
[ 1.0473472e+03 2.0890219e+02 1.1400822e+01 1.1236876e+00]
[ 1.0473472e+03 2.0890219e+02 1.1400822e+01 2.4707258e+00]
[ 1.1936158e+03 2.5239784e+02 1.0976992e+01 9.3526775e-01]
[ 6.3142053e+02 2.9328156e+02 1.0946433e+01 3.0389867e+00]
[ 2.2146999e+02 3.0215933e+02 1.0667258e+01 1.6780452e+00]
[ 8.2680542e+02 3.2253909e+02 1.0808415e+01 1.0410192e+00]
[ 6.0235468e+02 3.2771146e+02 1.0073055e+01 1.5506287e+00]
[ 1.1461711e+03 3.5643707e+02 1.0565990e+01 1.9988568e+00]
[ 9.9850354e+02 3.6280661e+02 1.0206414e+01 -1.2435182e+00]]
cpu
torch.Size([52])
tensor([0.0423, 0.5597, 0.0987, 0.0226, 0.1768, 0.0705, 0.2038, 0.1330, 0.1284,
0.0778])
torch.Size([52, 2])
tensor([[ 2, 4],
[ 3, 30],
[ 6, 6],
[ 7, 7],
[ 8, 43],
[ 9, 11],
[10, 12],
[12, 14],
[13, 15],
[15, 18]])
tensor([0.5860, 0.5597, 0.4843, 0.3750, 0.2752, 0.2038, 0.1919, 0.1845, 0.1768,
0.1348])
tensor([[31, 10],
[ 3, 30],
[30, 60],
[47, 9],
[50, 13],
[10, 12],
[18, 21],
[62, 27],
[ 8, 43],
[67, 62]])
<bound method PyCapsule.summary of Camera(camera_id=0, model=SIMPLE_PINHOLE, width=1280, height=720, params=[910.000000, 640.000000, 360.000000] (f, cx, cy))>
640.0
360.0
910.0
910.0
[[910. 0. 640.]
[ 0. 910. 360.]
[ 0. 0. 1.]]
dict_keys(['E', 'cam2_from_cam1', 'num_inliers', 'inliers'])
[[-1.30618467e-04 6.90040270e-01 -4.56431589e-02]
[-6.89801758e-01 2.47030238e-05 1.48734697e-01]
[ 4.53045055e-02 -1.47513174e-01 -5.26641889e-06]]
CV2
decomposed Essential Matrix
[[ 9.99998438e-01 7.24951801e-05 -1.76573383e-03]
[-7.33895479e-05 9.99999869e-01 -5.06453850e-04]
[ 1.76569688e-03 5.06582646e-04 9.99998313e-01]]
[ 0.02902509 -0.10116703 -0.00420492]
[[-0.91223713 0.02686638 0.40878065]
[ 0.02701979 -0.9917285 0.12547711]
[ 0.40877053 0.12551005 0.90396564]]
[ 7.90462991 -24.12762502 178.30343705]
[[0.2086198 ]
[0.06405504]
[0.97589689]]
[ True True True True True True True True True True True True
True True True True True True True True True True True True
True True True True True True True True True True True True
True True True True True True True True True True True True
True True True True]
Result recoverPose CV2
1
[[ 9.99998438e-01 7.24951801e-05 -1.76573383e-03]
[-7.33895479e-05 9.99999869e-01 -5.06453850e-04]
[ 1.76569688e-03 5.06582646e-04 9.99998313e-01]]
[[0.2086198 ]
[0.06405504]
[0.97589689]]
Result pycolmap
[[ 9.99998438e-01 7.24951801e-05 -1.76573383e-03 -2.08619803e-01]
[-7.33895479e-05 9.99999869e-01 -5.06453850e-04 -6.40550357e-02]
[ 1.76569688e-03 5.06582646e-04 9.99998313e-01 -9.75896885e-01]]
[[ 9.99998438e-01 -7.33895479e-05 1.76569688e-03 2.10337914e-01]
[ 7.24951801e-05 9.99999869e-01 5.06582646e-04 6.45645236e-02]
[-1.76573383e-03 -5.06453850e-04 9.99998313e-01 9.75494431e-01]]
Rigid3d:
rotation: Rotation3d:
quat = [ 2.53259231e-04 -8.82858051e-04 -3.64711974e-05 9.99999578e-01]
translation = [-0.2086198 -0.06405504 -0.97589689]
debug prints: estimate_calibrated_two_view_geometry
[[ 103.25252533 627.5736084 ]
[ 635.10766602 293.56375122]
[1170.61694336 609.92657471]
[ 995.36523438 359.21173096]
[1038.58496094 416.06182861]
[1181.74780273 393.3609314 ]
[ 830.24676514 512.47650146]
[ 619.87194824 591.88787842]
[ 814.02850342 355.37408447]
[ 910.16351318 650.93408203]]
[[ 961.42596436 386.71902466]
[1213.98132324 658.73760986]
[1173.48864746 609.75372314]
[ 998.50354004 362.80661011]
[1038.75439453 413.33563232]
[1181.22009277 393.20046997]
[ 829.9644165 512.37768555]
[ 616.26953125 592.09075928]
[ 812.72821045 356.39505005]
[ 909.18566895 650.11999512]]
(10, 2)
(10, 2)
Camera(camera_id=0, model=SIMPLE_PINHOLE, width=1280, height=720, params=[910.000000, 640.000000, 360.000000] (f, cx, cy))
Camera(camera_id=1, model=SIMPLE_PINHOLE, width=1280, height=720, params=[910.000000, 640.000000, 360.000000] (f, cx, cy))
TwoViewGeometryOptions:
min_num_inliers = 15
min_E_F_inlier_ratio = 0.95
max_H_inlier_ratio = 0.8
watermark_min_inlier_ratio = 0.7
watermark_border_size = 0.1
detect_watermark = True
multiple_ignore_watermark = True
force_H_use = False
compute_relative_pose = False
multiple_models = False
ransac: RANSACOptions:
max_error = 4.0
min_inlier_ratio = 0.25
confidence = 0.999
dyn_num_trials_multiplier = 3.0
min_num_trials = 100
max_num_trials = 10000
estimate_calibrated_two_view_geometry
Traceback (most recent call last):
File "d:\dev\research\sam2\test_colmap_2_issue.py", line 135, in <module>
answer = pycolmap.estimate_calibrated_two_view_geometry(cam1, points1[:10].astype(np.float64), cam2, points2[:10].astype(np.float64))
TypeError: estimate_calibrated_two_view_geometry(): incompatible function arguments. The following argument types are supported:
1. (camera1: pycolmap.Camera, points1: numpy.ndarray[numpy.float64[m, 2]], camera2: pycolmap.Camera, points2: numpy.ndarray[numpy.float64[m, 2]], matches: numpy.ndarray[numpy.uint32[m, 2]] = None, options: pycolmap.TwoViewGeometryOptions = <pycolmap.TwoViewGeometryOptions object at 0x000001CDDD695D70>) -> pycolmap.TwoViewGeometry
Invoked with: Camera(camera_id=0, model=SIMPLE_PINHOLE, width=1280, height=720, params=[910.000000, 640.000000, 360.000000] (f, cx, cy)), array([[ 103.25252533, 627.5736084 ],
[ 635.10766602, 293.56375122],
[1170.61694336, 609.92657471],
[ 995.36523438, 359.21173096],
[1038.58496094, 416.06182861],
[1181.74780273, 393.3609314 ],
[ 830.24676514, 512.47650146],
[ 619.87194824, 591.88787842],
[ 814.02850342, 355.37408447],
[ 910.16351318, 650.93408203]]), Camera(camera_id=1, model=SIMPLE_PINHOLE, width=1280, height=720, params=[910.000000, 640.000000, 360.000000] (f, cx, cy)), array([[ 961.42596436, 386.71902466],
[1213.98132324, 658.73760986],
[1173.48864746, 609.75372314],
[ 998.50354004, 362.80661011],
[1038.75439453, 413.33563232],
[1181.22009277, 393.20046997],
[ 829.9644165 , 512.37768555],
[ 616.26953125, 592.09075928],
[ 812.72821045, 356.39505005],
[ 909.18566895, 650.11999512]])
Different Exception utilizing matches argument
# when utilizing the matches argument, a different error occurs. See below.
print("estimate_calibrated_two_view_geometry with matches")
matches2, _ = mutual_nn_matcher(torch.from_numpy(descriptors1[:50]), torch.from_numpy(descriptors2[:50]))
print(matches2.to('cpu').numpy().shape)
answer = pycolmap.estimate_calibrated_two_view_geometry(cam1, keypoints1[:50,:2].astype(np.float64), cam2, keypoints2[:50,:2].astype(np.float64), matches2.to('cpu').numpy())
# calling estimate_calibrated_two_view_geometry with macthes throws a different error.
# estimate_calibrated_two_view_geometry with matches
# (34, 2)
# *** Aborted at 1731322363 (unix time) try "date -d @1731322363" if you are using GNU date ***
# @ 0x7fffed8d4172 log2f
# @ 0x7ff71e51207c OPENSSL_Applink
# @ 0x7fffba9fe5cf __C_specific_handler
# @ 0x7ffff053517f __chkstk
# @ 0x7ffff04ae856 RtlFindCharInUnicodeString
# @ 0x7ffff053416e KiUserExceptionDispatcher