diff --git a/environment.yml b/environment.yml index 69ff38b..68cd295 100644 --- a/environment.yml +++ b/environment.yml @@ -16,3 +16,4 @@ dependencies: - submodules/diff-gaussian-rasterization - submodules/simple-knn - opencv-python + - joblib diff --git a/utils/read_write_model.py b/utils/read_write_model.py new file mode 100644 index 0000000..f3f7585 --- /dev/null +++ b/utils/read_write_model.py @@ -0,0 +1,604 @@ +# Copyright (c) 2023, ETH Zurich and UNC Chapel Hill. +# All rights reserved. +# +# Redistribution and use in source and binary forms, with or without +# modification, are permitted provided that the following conditions are met: +# +# * Redistributions of source code must retain the above copyright +# notice, this list of conditions and the following disclaimer. +# +# * Redistributions in binary form must reproduce the above copyright +# notice, this list of conditions and the following disclaimer in the +# documentation and/or other materials provided with the distribution. +# +# * Neither the name of ETH Zurich and UNC Chapel Hill nor the names of +# its contributors may be used to endorse or promote products derived +# from this software without specific prior written permission. +# +# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE +# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR +# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF +# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS +# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN +# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) +# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE +# POSSIBILITY OF SUCH DAMAGE. + + +import os +import collections +import numpy as np +import struct +import argparse + + +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_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] +) + + +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) + + +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) + + +def read_cameras_text(path): + """ + see: src/colmap/scene/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 + + +def read_cameras_binary(path_to_model_file): + """ + see: src/colmap/scene/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 + + +def write_cameras_text(cameras, path): + """ + see: src/colmap/scene/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") + + +def write_cameras_binary(cameras, path_to_model_file): + """ + see: src/colmap/scene/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 + + +def read_images_text(path): + """ + see: src/colmap/scene/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 + + +def read_images_binary(path_to_model_file): + """ + see: src/colmap/scene/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 = "" + current_char = read_next_bytes(fid, 1, "c")[0] + while current_char != b"\x00": # look for the ASCII 0 entry + image_name += current_char.decode("utf-8") + current_char = read_next_bytes(fid, 1, "c")[0] + 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 + + +def write_images_text(images, path): + """ + see: src/colmap/scene/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") + + +def write_images_binary(images, path_to_model_file): + """ + see: src/colmap/scene/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") + + +def read_points3D_text(path): + """ + see: src/colmap/scene/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 + + +def read_points3D_binary(path_to_model_file): + """ + see: src/colmap/scene/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 + + +def write_points3D_text(points3D, path): + """ + see: src/colmap/scene/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") + + +def write_points3D_binary(points3D, path_to_model_file): + """ + see: src/colmap/scene/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( + [ + [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 main(): +# parser = argparse.ArgumentParser( +# description="Read and write COLMAP binary and text models" +# ) +# parser.add_argument("--input_model", help="path to input model folder") +# parser.add_argument( +# "--input_format", +# choices=[".bin", ".txt"], +# help="input model format", +# default="", +# ) +# parser.add_argument("--output_model", help="path to output model folder") +# parser.add_argument( +# "--output_format", +# choices=[".bin", ".txt"], +# help="outut model format", +# default=".txt", +# ) +# args = parser.parse_args() + +# cameras, images, points3D = read_model( +# path=args.input_model, ext=args.input_format +# ) + +# print("num_cameras:", len(cameras)) +# print("num_images:", len(images)) +# print("num_points3D:", len(points3D)) + +# if args.output_model is not None: +# write_model( +# cameras, +# images, +# points3D, +# path=args.output_model, +# ext=args.output_format, +# ) + + +# if __name__ == "__main__": +# main()