Source code for nerfstudio.data.utils.colmap_parsing_utils

"""
This file copied with small modifications from:
 * https://github.com/colmap/colmap/blob/1a4d0bad2e90aa65ce997c9d1779518eaed998d5/scripts/python/read_write_model.py

TODO(1480) Delete this file when moving to pycolmap.


"""

# Copyright (c) 2023, ETH Zurich and UNC Chapel Hill.
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# Author: Johannes L. Schoenberger (jsch-at-demuc-dot-de)

import collections
import os
import struct

import numpy as np

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"])


[docs]class Image(BaseImage): def qvec2rotmat(self): return qvec2rotmat(self.qvec)
CAMERA_MODELS = { CameraModel(model_id=0, model_name="SIMPLE_PINHOLE", num_params=3), CameraModel(model_id=1, model_name="PINHOLE", num_params=4), CameraModel(model_id=2, model_name="SIMPLE_RADIAL", num_params=4), CameraModel(model_id=3, model_name="RADIAL", num_params=5), CameraModel(model_id=4, model_name="OPENCV", num_params=8), CameraModel(model_id=5, model_name="OPENCV_FISHEYE", num_params=8), CameraModel(model_id=6, model_name="FULL_OPENCV", num_params=12), CameraModel(model_id=7, model_name="FOV", num_params=5), CameraModel(model_id=8, model_name="SIMPLE_RADIAL_FISHEYE", num_params=4), CameraModel(model_id=9, model_name="RADIAL_FISHEYE", num_params=5), CameraModel(model_id=10, model_name="THIN_PRISM_FISHEYE", num_params=12), } CAMERA_MODEL_IDS = dict([(camera_model.model_id, camera_model) for camera_model in CAMERA_MODELS]) CAMERA_MODEL_NAMES = dict([(camera_model.model_name, camera_model) for camera_model in CAMERA_MODELS])
[docs]def read_next_bytes(fid, num_bytes, format_char_sequence, endian_character="<"): """Read and unpack the next bytes from a binary file. :param fid: :param num_bytes: Sum of combination of {2, 4, 8}, e.g. 2, 6, 16, 30, etc. :param format_char_sequence: List of {c, e, f, d, h, H, i, I, l, L, q, Q}. :param endian_character: Any of {@, =, <, >, !} :return: Tuple of read and unpacked values. """ data = fid.read(num_bytes) return struct.unpack(endian_character + format_char_sequence, data)
[docs]def write_next_bytes(fid, data, format_char_sequence, endian_character="<"): """pack and write to a binary file. :param fid: :param data: data to send, if multiple elements are sent at the same time, they should be encapsuled either in a list or a tuple :param format_char_sequence: List of {c, e, f, d, h, H, i, I, l, L, q, Q}. should be the same length as the data list or tuple :param endian_character: Any of {@, =, <, >, !} """ if isinstance(data, (list, tuple)): bytes = struct.pack(endian_character + format_char_sequence, *data) else: bytes = struct.pack(endian_character + format_char_sequence, data) fid.write(bytes)
[docs]def read_cameras_text(path): """ see: src/base/reconstruction.cc void Reconstruction::WriteCamerasText(const std::string& path) void Reconstruction::ReadCamerasText(const std::string& path) """ cameras = {} with open(path, "r") as fid: while True: line = fid.readline() if not line: break line = line.strip() if len(line) > 0 and line[0] != "#": elems = line.split() camera_id = int(elems[0]) model = elems[1] width = int(elems[2]) height = int(elems[3]) params = np.array(tuple(map(float, elems[4:]))) cameras[camera_id] = Camera(id=camera_id, model=model, width=width, height=height, params=params) return cameras
[docs]def read_cameras_binary(path_to_model_file): """ see: src/base/reconstruction.cc void Reconstruction::WriteCamerasBinary(const std::string& path) void Reconstruction::ReadCamerasBinary(const std::string& path) """ 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) ) assert len(cameras) == num_cameras return cameras
[docs]def write_cameras_text(cameras, path): """ see: src/base/reconstruction.cc void Reconstruction::WriteCamerasText(const std::string& path) void Reconstruction::ReadCamerasText(const std::string& path) """ HEADER = ( "# Camera list with one line of data per camera:\n" + "# CAMERA_ID, MODEL, WIDTH, HEIGHT, PARAMS[]\n" + "# Number of cameras: {}\n".format(len(cameras)) ) with open(path, "w") as fid: fid.write(HEADER) for _, cam in cameras.items(): to_write = [cam.id, cam.model, cam.width, cam.height, *cam.params] line = " ".join([str(elem) for elem in to_write]) fid.write(line + "\n")
[docs]def write_cameras_binary(cameras, path_to_model_file): """ see: src/base/reconstruction.cc void Reconstruction::WriteCamerasBinary(const std::string& path) void Reconstruction::ReadCamerasBinary(const std::string& path) """ with open(path_to_model_file, "wb") as fid: write_next_bytes(fid, len(cameras), "Q") for _, cam in cameras.items(): model_id = CAMERA_MODEL_NAMES[cam.model].model_id camera_properties = [cam.id, model_id, cam.width, cam.height] write_next_bytes(fid, camera_properties, "iiQQ") for p in cam.params: write_next_bytes(fid, float(p), "d") return cameras
[docs]def read_images_text(path): """ see: src/base/reconstruction.cc void Reconstruction::ReadImagesText(const std::string& path) void Reconstruction::WriteImagesText(const std::string& path) """ images = {} with open(path, "r") as fid: while True: line = fid.readline() if not line: break line = line.strip() if len(line) > 0 and line[0] != "#": elems = line.split() image_id = int(elems[0]) qvec = np.array(tuple(map(float, elems[1:5]))) tvec = np.array(tuple(map(float, elems[5:8]))) camera_id = int(elems[8]) image_name = elems[9] elems = fid.readline().split() xys = np.column_stack([tuple(map(float, elems[0::3])), tuple(map(float, elems[1::3]))]) point3D_ids = np.array(tuple(map(int, elems[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
[docs]def read_images_binary(path_to_model_file): """ see: src/base/reconstruction.cc void Reconstruction::ReadImagesBinary(const std::string& path) void Reconstruction::WriteImagesBinary(const std::string& path) """ 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] image_name = b"" current_char = read_next_bytes(fid, 1, "c")[0] while current_char != b"\x00": # look for the ASCII 0 entry image_name += current_char current_char = read_next_bytes(fid, 1, "c")[0] image_name = image_name.decode("utf-8") num_points2D = read_next_bytes(fid, num_bytes=8, format_char_sequence="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([tuple(map(float, x_y_id_s[0::3])), tuple(map(float, x_y_id_s[1::3]))]) point3D_ids = np.array(tuple(map(int, 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
[docs]def write_images_text(images, path): """ see: src/base/reconstruction.cc void Reconstruction::ReadImagesText(const std::string& path) void Reconstruction::WriteImagesText(const std::string& path) """ if len(images) == 0: mean_observations = 0 else: mean_observations = sum((len(img.point3D_ids) for _, img in images.items())) / len(images) HEADER = ( "# Image list with two lines of data per image:\n" + "# IMAGE_ID, QW, QX, QY, QZ, TX, TY, TZ, CAMERA_ID, NAME\n" + "# POINTS2D[] as (X, Y, POINT3D_ID)\n" + "# Number of images: {}, mean observations per image: {}\n".format(len(images), mean_observations) ) with open(path, "w") as fid: fid.write(HEADER) for _, img in images.items(): image_header = [img.id, *img.qvec, *img.tvec, img.camera_id, img.name] first_line = " ".join(map(str, image_header)) fid.write(first_line + "\n") points_strings = [] for xy, point3D_id in zip(img.xys, img.point3D_ids): points_strings.append(" ".join(map(str, [*xy, point3D_id]))) fid.write(" ".join(points_strings) + "\n")
[docs]def write_images_binary(images, path_to_model_file): """ see: src/base/reconstruction.cc void Reconstruction::ReadImagesBinary(const std::string& path) void Reconstruction::WriteImagesBinary(const std::string& path) """ with open(path_to_model_file, "wb") as fid: write_next_bytes(fid, len(images), "Q") for _, img in images.items(): write_next_bytes(fid, img.id, "i") write_next_bytes(fid, img.qvec.tolist(), "dddd") write_next_bytes(fid, img.tvec.tolist(), "ddd") write_next_bytes(fid, img.camera_id, "i") for char in img.name: write_next_bytes(fid, char.encode("utf-8"), "c") write_next_bytes(fid, b"\x00", "c") write_next_bytes(fid, len(img.point3D_ids), "Q") for xy, p3d_id in zip(img.xys, img.point3D_ids): write_next_bytes(fid, [*xy, p3d_id], "ddq")
[docs]def read_points3D_text(path): """ see: src/base/reconstruction.cc void Reconstruction::ReadPoints3DText(const std::string& path) void Reconstruction::WritePoints3DText(const std::string& path) """ points3D = {} with open(path, "r") as fid: while True: line = fid.readline() if not line: break line = line.strip() if len(line) > 0 and line[0] != "#": elems = line.split() point3D_id = int(elems[0]) xyz = np.array(tuple(map(float, elems[1:4]))) rgb = np.array(tuple(map(int, elems[4:7]))) error = float(elems[7]) image_ids = np.array(tuple(map(int, elems[8::2]))) point2D_idxs = np.array(tuple(map(int, elems[9::2]))) points3D[point3D_id] = Point3D( id=point3D_id, xyz=xyz, rgb=rgb, error=error, image_ids=image_ids, point2D_idxs=point2D_idxs ) return points3D
[docs]def read_points3D_binary(path_to_model_file): """ see: src/base/reconstruction.cc void Reconstruction::ReadPoints3DBinary(const std::string& path) void Reconstruction::WritePoints3DBinary(const std::string& path) """ 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 = np.array(binary_point_line_properties[7]) track_length = read_next_bytes(fid, num_bytes=8, format_char_sequence="Q")[0] track_elems = read_next_bytes(fid, num_bytes=8 * track_length, format_char_sequence="ii" * track_length) image_ids = np.array(tuple(map(int, track_elems[0::2]))) point2D_idxs = np.array(tuple(map(int, 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
[docs]def write_points3D_text(points3D, path): """ see: src/base/reconstruction.cc void Reconstruction::ReadPoints3DText(const std::string& path) void Reconstruction::WritePoints3DText(const std::string& path) """ if len(points3D) == 0: mean_track_length = 0 else: mean_track_length = sum((len(pt.image_ids) for _, pt in points3D.items())) / len(points3D) HEADER = ( "# 3D point list with one line of data per point:\n" + "# POINT3D_ID, X, Y, Z, R, G, B, ERROR, TRACK[] as (IMAGE_ID, POINT2D_IDX)\n" + "# Number of points: {}, mean track length: {}\n".format(len(points3D), mean_track_length) ) with open(path, "w") as fid: fid.write(HEADER) for _, pt in points3D.items(): point_header = [pt.id, *pt.xyz, *pt.rgb, pt.error] fid.write(" ".join(map(str, point_header)) + " ") track_strings = [] for image_id, point2D in zip(pt.image_ids, pt.point2D_idxs): track_strings.append(" ".join(map(str, [image_id, point2D]))) fid.write(" ".join(track_strings) + "\n")
[docs]def write_points3D_binary(points3D, path_to_model_file): """ see: src/base/reconstruction.cc void Reconstruction::ReadPoints3DBinary(const std::string& path) void Reconstruction::WritePoints3DBinary(const std::string& path) """ with open(path_to_model_file, "wb") as fid: write_next_bytes(fid, len(points3D), "Q") for _, pt in points3D.items(): write_next_bytes(fid, pt.id, "Q") write_next_bytes(fid, pt.xyz.tolist(), "ddd") write_next_bytes(fid, pt.rgb.tolist(), "BBB") write_next_bytes(fid, pt.error, "d") track_length = pt.image_ids.shape[0] write_next_bytes(fid, track_length, "Q") for image_id, point2D_id in zip(pt.image_ids, pt.point2D_idxs): write_next_bytes(fid, [image_id, point2D_id], "ii")
def detect_model_format(path, ext): if ( os.path.isfile(os.path.join(path, "cameras" + ext)) and os.path.isfile(os.path.join(path, "images" + ext)) and os.path.isfile(os.path.join(path, "points3D" + ext)) ): print("Detected model format: '" + ext + "'") return True return False def read_model(path, ext=""): # try to detect the extension automatically if ext == "": if detect_model_format(path, ".bin"): ext = ".bin" elif detect_model_format(path, ".txt"): ext = ".txt" else: print("Provide model format: '.bin' or '.txt'") return if ext == ".txt": cameras = read_cameras_text(os.path.join(path, "cameras" + ext)) images = read_images_text(os.path.join(path, "images" + ext)) points3D = read_points3D_text(os.path.join(path, "points3D") + ext) else: cameras = read_cameras_binary(os.path.join(path, "cameras" + ext)) images = read_images_binary(os.path.join(path, "images" + ext)) points3D = read_points3D_binary(os.path.join(path, "points3D") + ext) return cameras, images, points3D def write_model(cameras, images, points3D, path, ext=".bin"): if ext == ".txt": write_cameras_text(cameras, os.path.join(path, "cameras" + ext)) write_images_text(images, os.path.join(path, "images" + ext)) write_points3D_text(points3D, os.path.join(path, "points3D") + ext) else: write_cameras_binary(cameras, os.path.join(path, "cameras" + ext)) write_images_binary(images, os.path.join(path, "images" + ext)) write_points3D_binary(points3D, os.path.join(path, "points3D") + ext) return cameras, images, points3D def qvec2rotmat(qvec): 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): Rxx, Ryx, Rzx, Rxy, Ryy, Rzy, Rxz, Ryz, Rzz = R.flat K = ( np.array( [ # type: ignore [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