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| # | |
| # Copyright (C) 2023, Inria | |
| # GRAPHDECO research group, https://team.inria.fr/graphdeco | |
| # All rights reserved. | |
| # | |
| # This software is free for non-commercial, research and evaluation use | |
| # under the terms of the LICENSE.md file. | |
| # | |
| # For inquiries contact george.drettakis@inria.fr | |
| # | |
| import numpy as np | |
| import collections | |
| import struct | |
| 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"]) | |
| 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 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 | |
| class Image(BaseImage): | |
| def qvec2rotmat(self): | |
| return qvec2rotmat(self.qvec) | |
| 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 read_points3D_text(path): | |
| """ | |
| see: src/base/reconstruction.cc | |
| void Reconstruction::ReadPoints3DText(const std::string& path) | |
| void Reconstruction::WritePoints3DText(const std::string& path) | |
| """ | |
| xyzs = None | |
| rgbs = None | |
| errors = None | |
| num_points = 0 | |
| 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] != "#": | |
| num_points += 1 | |
| xyzs = np.empty((num_points, 3)) | |
| rgbs = np.empty((num_points, 3)) | |
| errors = np.empty((num_points, 1)) | |
| count = 0 | |
| 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() | |
| xyz = np.array(tuple(map(float, elems[1:4]))) | |
| rgb = np.array(tuple(map(int, elems[4:7]))) | |
| error = np.array(float(elems[7])) | |
| xyzs[count] = xyz | |
| rgbs[count] = rgb | |
| errors[count] = error | |
| count += 1 | |
| return xyzs, rgbs, errors | |
| 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) | |
| """ | |
| with open(path_to_model_file, "rb") as fid: | |
| num_points = read_next_bytes(fid, 8, "Q")[0] | |
| xyzs = np.empty((num_points, 3)) | |
| rgbs = np.empty((num_points, 3)) | |
| errors = np.empty((num_points, 1)) | |
| for p_id in range(num_points): | |
| binary_point_line_properties = read_next_bytes( | |
| fid, num_bytes=43, format_char_sequence="QdddBBBd") | |
| 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) | |
| xyzs[p_id] = xyz | |
| rgbs[p_id] = rgb | |
| errors[p_id] = error | |
| return xyzs, rgbs, errors | |
| def read_intrinsics_text(path): | |
| """ | |
| Taken from https://github.com/colmap/colmap/blob/dev/scripts/python/read_write_model.py | |
| """ | |
| 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] | |
| assert model == "PINHOLE", "While the loader support other types, the rest of the code assumes PINHOLE" | |
| 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_extrinsics_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 = "" | |
| 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 read_intrinsics_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 | |
| def read_extrinsics_text(path): | |
| """ | |
| Taken from https://github.com/colmap/colmap/blob/dev/scripts/python/read_write_model.py | |
| """ | |
| 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_colmap_bin_array(path): | |
| """ | |
| Taken from https://github.com/colmap/colmap/blob/dev/scripts/python/read_dense.py | |
| :param path: path to the colmap binary file. | |
| :return: nd array with the floating point values in the value | |
| """ | |
| with open(path, "rb") as fid: | |
| width, height, channels = np.genfromtxt(fid, delimiter="&", max_rows=1, | |
| usecols=(0, 1, 2), dtype=int) | |
| fid.seek(0) | |
| num_delimiter = 0 | |
| byte = fid.read(1) | |
| while True: | |
| if byte == b"&": | |
| num_delimiter += 1 | |
| if num_delimiter >= 3: | |
| break | |
| byte = fid.read(1) | |
| array = np.fromfile(fid, np.float32) | |
| array = array.reshape((width, height, channels), order="F") | |
| return np.transpose(array, (1, 0, 2)).squeeze() | |