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COLMAP Binary File Reader for ControlWave
Reads cameras.bin and images.bin files generated by VGGT/COLMAP
Based on COLMAP's official format specification and read_write_model.py
"""
import struct
import numpy as np
from pathlib import Path
from typing import Dict, List, Tuple, Optional, NamedTuple
import collections
# Data structures
CameraModel = collections.namedtuple(
"CameraModel", ["model_id", "model_name", "num_params"]
)
Camera = collections.namedtuple(
"Camera", ["id", "model", "width", "height", "params"]
)
BaseImage = collections.namedtuple(
"Image", ["id", "qvec", "tvec", "camera_id", "name", "xys", "point3D_ids"]
)
Point3D = collections.namedtuple(
"Point3D", ["id", "xyz", "rgb", "error", "image_ids", "point2D_idxs"]
)
class Image(BaseImage):
def qvec2rotmat(self):
return qvec2rotmat(self.qvec)
# Camera model definitions
CAMERA_MODELS = {
0: CameraModel(model_id=0, model_name="SIMPLE_PINHOLE", num_params=3),
1: CameraModel(model_id=1, model_name="PINHOLE", num_params=4),
2: CameraModel(model_id=2, model_name="SIMPLE_RADIAL", num_params=4),
3: CameraModel(model_id=3, model_name="RADIAL", num_params=5),
4: CameraModel(model_id=4, model_name="OPENCV", num_params=8),
5: CameraModel(model_id=5, model_name="OPENCV_FISHEYE", num_params=8),
6: CameraModel(model_id=6, model_name="FULL_OPENCV", num_params=12),
7: CameraModel(model_id=7, model_name="FOV", num_params=5),
8: CameraModel(model_id=8, model_name="SIMPLE_RADIAL_FISHEYE", num_params=4),
9: CameraModel(model_id=9, model_name="RADIAL_FISHEYE", num_params=5),
10: CameraModel(model_id=10, model_name="THIN_PRISM_FISHEYE", num_params=12),
}
CAMERA_MODEL_IDS = CAMERA_MODELS
def read_next_bytes(fid, num_bytes, format_char_sequence, endian_character="<"):
"""Read and unpack the next bytes from a binary file.
Args:
fid: File handle
num_bytes: Number of bytes to read
format_char_sequence: Format string for struct.unpack
endian_character: Endianness character ('<' for little-endian)
Returns:
Unpacked data tuple
"""
data = fid.read(num_bytes)
return struct.unpack(endian_character + format_char_sequence, data)
def qvec2rotmat(qvec):
"""Convert quaternion to rotation matrix.
Args:
qvec: Quaternion [w, x, y, z]
Returns:
3x3 rotation matrix
"""
return np.array(
[
[
1 - 2 * qvec[2] ** 2 - 2 * qvec[3] ** 2,
2 * qvec[1] * qvec[2] - 2 * qvec[0] * qvec[3],
2 * qvec[3] * qvec[1] + 2 * qvec[0] * qvec[2],
],
[
2 * qvec[1] * qvec[2] + 2 * qvec[0] * qvec[3],
1 - 2 * qvec[1] ** 2 - 2 * qvec[3] ** 2,
2 * qvec[2] * qvec[3] - 2 * qvec[0] * qvec[1],
],
[
2 * qvec[3] * qvec[1] - 2 * qvec[0] * qvec[2],
2 * qvec[2] * qvec[3] + 2 * qvec[0] * qvec[1],
1 - 2 * qvec[1] ** 2 - 2 * qvec[2] ** 2,
],
]
)
def rotmat2qvec(R):
"""Convert rotation matrix to quaternion.
Args:
R: 3x3 rotation matrix
Returns:
Quaternion [w, x, y, z]
"""
Rxx, Ryx, Rzx, Rxy, Ryy, Rzy, Rxz, Ryz, Rzz = R.flat
K = (
np.array(
[
[Rxx - Ryy - Rzz, 0, 0, 0],
[Ryx + Rxy, Ryy - Rxx - Rzz, 0, 0],
[Rzx + Rxz, Rzy + Ryz, Rzz - Rxx - Ryy, 0],
[Ryz - Rzy, Rzx - Rxz, Rxy - Ryx, Rxx + Ryy + Rzz],
]
)
/ 3.0
)
eigvals, eigvecs = np.linalg.eigh(K)
qvec = eigvecs[[3, 0, 1, 2], np.argmax(eigvals)]
if qvec[0] < 0:
qvec *= -1
return qvec
def read_cameras_binary(path_to_model_file):
"""Read cameras from binary file.
Args:
path_to_model_file: Path to cameras.bin file
Returns:
Dictionary mapping camera_id to Camera object
"""
cameras = {}
with open(path_to_model_file, "rb") as fid:
num_cameras = read_next_bytes(fid, 8, "Q")[0]
for _ in range(num_cameras):
camera_properties = read_next_bytes(
fid, num_bytes=24, format_char_sequence="iiQQ"
)
camera_id = camera_properties[0]
model_id = camera_properties[1]
model_name = CAMERA_MODEL_IDS[camera_properties[1]].model_name
width = camera_properties[2]
height = camera_properties[3]
num_params = CAMERA_MODEL_IDS[model_id].num_params
params = read_next_bytes(
fid, num_bytes=8 * num_params, format_char_sequence="d" * num_params
)
cameras[camera_id] = Camera(
id=camera_id,
model=model_name,
width=width,
height=height,
params=np.array(params),
)
return cameras
def read_images_binary(path_to_model_file):
"""Read images from binary file.
Args:
path_to_model_file: Path to images.bin file
Returns:
Dictionary mapping image_id to Image object
"""
images = {}
with open(path_to_model_file, "rb") as fid:
num_reg_images = read_next_bytes(fid, 8, "Q")[0]
for _ in range(num_reg_images):
binary_image_properties = read_next_bytes(
fid, num_bytes=64, format_char_sequence="idddddddi"
)
image_id = binary_image_properties[0]
qvec = np.array(binary_image_properties[1:5])
tvec = np.array(binary_image_properties[5:8])
camera_id = binary_image_properties[8]
binary_image_name = b""
current_char = read_next_bytes(fid, 1, "c")[0]
while current_char != b"\x00": # Look for the ASCII 0 entry
binary_image_name += current_char
current_char = read_next_bytes(fid, 1, "c")[0]
image_name = binary_image_name.decode("utf-8")
num_points2D = read_next_bytes(fid, 8, "Q")[0]
x_y_id_s = read_next_bytes(
fid, num_bytes=24 * num_points2D, format_char_sequence="ddQ" * num_points2D
)
xys = np.column_stack(
[x_y_id_s[0::3], x_y_id_s[1::3]]
)
point3D_ids = np.array(x_y_id_s[2::3])
images[image_id] = Image(
id=image_id,
qvec=qvec,
tvec=tvec,
camera_id=camera_id,
name=image_name,
xys=xys,
point3D_ids=point3D_ids,
)
return images
def read_points3D_binary(path_to_model_file):
"""Read 3D points from binary file.
Args:
path_to_model_file: Path to points3D.bin file
Returns:
Dictionary mapping point3D_id to Point3D object
"""
points3D = {}
with open(path_to_model_file, "rb") as fid:
num_points = read_next_bytes(fid, 8, "Q")[0]
for _ in range(num_points):
binary_point_line_properties = read_next_bytes(
fid, num_bytes=43, format_char_sequence="QdddBBBd"
)
point3D_id = binary_point_line_properties[0]
xyz = np.array(binary_point_line_properties[1:4])
rgb = np.array(binary_point_line_properties[4:7])
error = binary_point_line_properties[7]
track_length = read_next_bytes(fid, 8, "Q")[0]
track_elems = read_next_bytes(
fid, num_bytes=8 * track_length, format_char_sequence="ii" * track_length
)
image_ids = np.array(track_elems[0::2])
point2D_idxs = np.array(track_elems[1::2])
points3D[point3D_id] = Point3D(
id=point3D_id,
xyz=xyz,
rgb=rgb,
error=error,
image_ids=image_ids,
point2D_idxs=point2D_idxs,
)
return points3D
class COLMAPReader:
"""Helper class to read COLMAP reconstruction files."""
def __init__(self, reconstruction_dir: str):
"""Initialize reader with reconstruction directory.
Args:
reconstruction_dir: Directory containing cameras.bin, images.bin, and optionally points3D.bin
"""
self.reconstruction_dir = Path(reconstruction_dir)
self.cameras = None
self.images = None
self.points3D = None
def read_cameras(self) -> Dict[int, Camera]:
"""Read cameras from cameras.bin file."""
cameras_file = self.reconstruction_dir / "cameras.bin"
if not cameras_file.exists():
raise FileNotFoundError(f"cameras.bin not found in {self.reconstruction_dir}")
self.cameras = read_cameras_binary(str(cameras_file))
return self.cameras
def read_images(self) -> Dict[int, Image]:
"""Read images from images.bin file."""
images_file = self.reconstruction_dir / "images.bin"
if not images_file.exists():
raise FileNotFoundError(f"images.bin not found in {self.reconstruction_dir}")
self.images = read_images_binary(str(images_file))
return self.images
def read_points3D(self) -> Dict[int, Point3D]:
"""Read 3D points from points3D.bin file."""
points_file = self.reconstruction_dir / "points3D.bin"
if not points_file.exists():
raise FileNotFoundError(f"points3D.bin not found in {self.reconstruction_dir}")
self.points3D = read_points3D_binary(str(points_file))
return self.points3D
def read_all(self) -> Tuple[Dict[int, Camera], Dict[int, Image], Optional[Dict[int, Point3D]]]:
"""Read all available reconstruction files."""
cameras = self.read_cameras()
images = self.read_images()
# Points3D is optional
points3D = None
if (self.reconstruction_dir / "points3D.bin").exists():
points3D = self.read_points3D()
return cameras, images, points3D
def get_camera_poses(self) -> List[np.ndarray]:
"""Get camera poses as 4x4 transformation matrices.
Returns:
List of 4x4 numpy arrays representing camera poses (world to camera transform)
"""
if self.images is None:
self.read_images()
poses = []
for image_id in sorted(self.images.keys()):
image = self.images[image_id]
# Convert quaternion to rotation matrix
R = qvec2rotmat(image.qvec)
t = image.tvec
# Create 4x4 transformation matrix
pose = np.eye(4)
pose[:3, :3] = R
pose[:3, 3] = t
poses.append(pose)
return poses
def get_intrinsics(self) -> List[np.ndarray]:
"""Get camera intrinsics as 3x3 matrices.
Returns:
List of 3x3 intrinsic matrices
"""
if self.cameras is None:
self.read_cameras()
if self.images is None:
self.read_images()
intrinsics = []
for image_id in sorted(self.images.keys()):
image = self.images[image_id]
camera = self.cameras[image.camera_id]
# Build intrinsic matrix based on camera model
K = np.eye(3)
if camera.model == "SIMPLE_PINHOLE":
# f, cx, cy
f, cx, cy = camera.params
K[0, 0] = f
K[1, 1] = f
K[0, 2] = cx
K[1, 2] = cy
elif camera.model == "PINHOLE":
# fx, fy, cx, cy
fx, fy, cx, cy = camera.params[:4]
K[0, 0] = fx
K[1, 1] = fy
K[0, 2] = cx
K[1, 2] = cy
else:
# For other models, use the first two parameters as fx, fy
# and parameters 3,4 as cx, cy (if available)
if len(camera.params) >= 2:
K[0, 0] = camera.params[0]
K[1, 1] = camera.params[1] if len(camera.params) > 1 else camera.params[0]
if len(camera.params) >= 4:
K[0, 2] = camera.params[2]
K[1, 2] = camera.params[3]
else:
# Default to image center
K[0, 2] = camera.width / 2
K[1, 2] = camera.height / 2
intrinsics.append(K)
return intrinsics
# Example usage
if __name__ == "__main__":
# Example: Read COLMAP reconstruction
reader = COLMAPReader("/path/to/reconstruction")
# Read all data
cameras, images, points3D = reader.read_all()
# Get camera poses and intrinsics
poses = reader.get_camera_poses()
intrinsics = reader.get_intrinsics()
print(f"Found {len(cameras)} cameras")
print(f"Found {len(images)} images")
if points3D:
print(f"Found {len(points3D)} 3D points")
# Print first camera info
if cameras:
first_camera = list(cameras.values())[0]
print(f"\nFirst camera:")
print(f" Model: {first_camera.model}")
print(f" Resolution: {first_camera.width}x{first_camera.height}")
print(f" Parameters: {first_camera.params}")
# Print first image info
if images:
first_image = list(images.values())[0]
print(f"\nFirst image:")
print(f" Name: {first_image.name}")
print(f" Camera ID: {first_image.camera_id}")
print(f" Rotation (qvec): {first_image.qvec}")
print(f" Translation: {first_image.tvec}") |