|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 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":
|
| 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()
|
|
|
