""" 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}")