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import os |
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import collections |
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import numpy as np |
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import struct |
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import argparse |
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|
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CameraModel = collections.namedtuple( |
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"CameraModel", ["model_id", "model_name", "num_params"]) |
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Camera = collections.namedtuple( |
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"Camera", ["id", "model", "width", "height", "params"]) |
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BaseImage = collections.namedtuple( |
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"Image", ["id", "qvec", "tvec", "camera_id", "name", "xys", "point3D_ids"]) |
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Point3D = collections.namedtuple( |
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"Point3D", ["id", "xyz", "rgb", "error", "image_ids", "point2D_idxs"]) |
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class Image(BaseImage): |
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def qvec2rotmat(self): |
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return qvec2rotmat(self.qvec) |
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CAMERA_MODELS = { |
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CameraModel(model_id=0, model_name="SIMPLE_PINHOLE", num_params=3), |
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CameraModel(model_id=1, model_name="PINHOLE", num_params=4), |
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CameraModel(model_id=2, model_name="SIMPLE_RADIAL", num_params=4), |
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CameraModel(model_id=3, model_name="RADIAL", num_params=5), |
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CameraModel(model_id=4, model_name="OPENCV", num_params=8), |
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CameraModel(model_id=5, model_name="OPENCV_FISHEYE", num_params=8), |
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CameraModel(model_id=6, model_name="FULL_OPENCV", num_params=12), |
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CameraModel(model_id=7, model_name="FOV", num_params=5), |
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CameraModel(model_id=8, model_name="SIMPLE_RADIAL_FISHEYE", num_params=4), |
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CameraModel(model_id=9, model_name="RADIAL_FISHEYE", num_params=5), |
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CameraModel(model_id=10, model_name="THIN_PRISM_FISHEYE", num_params=12) |
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} |
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CAMERA_MODEL_IDS = dict([(camera_model.model_id, camera_model) |
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for camera_model in CAMERA_MODELS]) |
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CAMERA_MODEL_NAMES = dict([(camera_model.model_name, camera_model) |
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for camera_model in CAMERA_MODELS]) |
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|
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def read_next_bytes(fid, num_bytes, format_char_sequence, endian_character="<"): |
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"""Read and unpack the next bytes from a binary file. |
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:param fid: |
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:param num_bytes: Sum of combination of {2, 4, 8}, e.g. 2, 6, 16, 30, etc. |
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:param format_char_sequence: List of {c, e, f, d, h, H, i, I, l, L, q, Q}. |
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:param endian_character: Any of {@, =, <, >, !} |
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:return: Tuple of read and unpacked values. |
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""" |
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data = fid.read(num_bytes) |
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return struct.unpack(endian_character + format_char_sequence, data) |
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|
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def write_next_bytes(fid, data, format_char_sequence, endian_character="<"): |
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"""pack and write to a binary file. |
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:param fid: |
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:param data: data to send, if multiple elements are sent at the same time, |
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they should be encapsuled either in a list or a tuple |
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:param format_char_sequence: List of {c, e, f, d, h, H, i, I, l, L, q, Q}. |
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should be the same length as the data list or tuple |
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:param endian_character: Any of {@, =, <, >, !} |
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""" |
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if isinstance(data, (list, tuple)): |
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bytes = struct.pack(endian_character + format_char_sequence, *data) |
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else: |
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bytes = struct.pack(endian_character + format_char_sequence, data) |
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fid.write(bytes) |
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|
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def read_cameras_text(path): |
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""" |
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see: src/base/reconstruction.cc |
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void Reconstruction::WriteCamerasText(const std::string& path) |
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void Reconstruction::ReadCamerasText(const std::string& path) |
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""" |
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cameras = {} |
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with open(path, "r") as fid: |
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while True: |
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line = fid.readline() |
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if not line: |
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break |
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line = line.strip() |
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if len(line) > 0 and line[0] != "#": |
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elems = line.split() |
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camera_id = int(elems[0]) |
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model = elems[1] |
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width = int(elems[2]) |
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height = int(elems[3]) |
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params = np.array(tuple(map(float, elems[4:]))) |
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cameras[camera_id] = Camera(id=camera_id, model=model, |
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width=width, height=height, |
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params=params) |
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return cameras |
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|
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def read_cameras_binary(path_to_model_file=None, fid=None): |
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""" |
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see: src/base/reconstruction.cc |
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void Reconstruction::WriteCamerasBinary(const std::string& path) |
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void Reconstruction::ReadCamerasBinary(const std::string& path) |
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""" |
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cameras = {} |
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if fid is None: |
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fid = open(path_to_model_file, "rb") |
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num_cameras = read_next_bytes(fid, 8, "Q")[0] |
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for _ in range(num_cameras): |
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camera_properties = read_next_bytes( |
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fid, num_bytes=24, format_char_sequence="iiQQ") |
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camera_id = camera_properties[0] |
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model_id = camera_properties[1] |
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model_name = CAMERA_MODEL_IDS[camera_properties[1]].model_name |
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width = camera_properties[2] |
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height = camera_properties[3] |
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num_params = CAMERA_MODEL_IDS[model_id].num_params |
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params = read_next_bytes(fid, num_bytes=8*num_params, |
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format_char_sequence="d"*num_params) |
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cameras[camera_id] = Camera(id=camera_id, |
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model=model_name, |
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width=width, |
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height=height, |
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params=np.array(params)) |
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assert len(cameras) == num_cameras |
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if path_to_model_file is not None: |
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fid.close() |
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return cameras |
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|
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def write_cameras_text(cameras, path): |
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""" |
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see: src/base/reconstruction.cc |
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void Reconstruction::WriteCamerasText(const std::string& path) |
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void Reconstruction::ReadCamerasText(const std::string& path) |
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""" |
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HEADER = "# Camera list with one line of data per camera:\n" + \ |
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"# CAMERA_ID, MODEL, WIDTH, HEIGHT, PARAMS[]\n" + \ |
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"# Number of cameras: {}\n".format(len(cameras)) |
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with open(path, "w") as fid: |
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fid.write(HEADER) |
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for _, cam in cameras.items(): |
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to_write = [cam.id, cam.model, cam.width, cam.height, *cam.params] |
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line = " ".join([str(elem) for elem in to_write]) |
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fid.write(line + "\n") |
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|
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def write_cameras_binary(cameras, path_to_model_file): |
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""" |
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see: src/base/reconstruction.cc |
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void Reconstruction::WriteCamerasBinary(const std::string& path) |
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void Reconstruction::ReadCamerasBinary(const std::string& path) |
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""" |
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with open(path_to_model_file, "wb") as fid: |
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write_next_bytes(fid, len(cameras), "Q") |
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for _, cam in cameras.items(): |
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model_id = CAMERA_MODEL_NAMES[cam.model].model_id |
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camera_properties = [cam.id, |
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model_id, |
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cam.width, |
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cam.height] |
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write_next_bytes(fid, camera_properties, "iiQQ") |
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for p in cam.params: |
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write_next_bytes(fid, float(p), "d") |
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return cameras |
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|
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|
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def read_images_text(path): |
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""" |
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see: src/base/reconstruction.cc |
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void Reconstruction::ReadImagesText(const std::string& path) |
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void Reconstruction::WriteImagesText(const std::string& path) |
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""" |
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images = {} |
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with open(path, "r") as fid: |
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while True: |
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line = fid.readline() |
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if not line: |
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break |
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line = line.strip() |
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if len(line) > 0 and line[0] != "#": |
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elems = line.split() |
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image_id = int(elems[0]) |
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qvec = np.array(tuple(map(float, elems[1:5]))) |
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tvec = np.array(tuple(map(float, elems[5:8]))) |
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camera_id = int(elems[8]) |
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image_name = elems[9] |
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elems = fid.readline().split() |
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xys = np.column_stack([tuple(map(float, elems[0::3])), |
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tuple(map(float, elems[1::3]))]) |
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point3D_ids = np.array(tuple(map(int, elems[2::3]))) |
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images[image_id] = Image( |
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id=image_id, qvec=qvec, tvec=tvec, |
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camera_id=camera_id, name=image_name, |
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xys=xys, point3D_ids=point3D_ids) |
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return images |
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|
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|
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def read_images_binary(path_to_model_file=None, fid=None): |
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""" |
|
see: src/base/reconstruction.cc |
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void Reconstruction::ReadImagesBinary(const std::string& path) |
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void Reconstruction::WriteImagesBinary(const std::string& path) |
|
""" |
|
images = {} |
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if fid is None: |
|
fid = open(path_to_model_file, "rb") |
|
num_reg_images = read_next_bytes(fid, 8, "Q")[0] |
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for _ in range(num_reg_images): |
|
binary_image_properties = read_next_bytes( |
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fid, num_bytes=64, format_char_sequence="idddddddi") |
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image_id = binary_image_properties[0] |
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qvec = np.array(binary_image_properties[1:5]) |
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tvec = np.array(binary_image_properties[5:8]) |
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camera_id = binary_image_properties[8] |
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image_name = "" |
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current_char = read_next_bytes(fid, 1, "c")[0] |
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while current_char != b"\x00": |
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image_name += current_char.decode("utf-8") |
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current_char = read_next_bytes(fid, 1, "c")[0] |
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num_points2D = read_next_bytes(fid, num_bytes=8, |
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format_char_sequence="Q")[0] |
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x_y_id_s = read_next_bytes(fid, num_bytes=24*num_points2D, |
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format_char_sequence="ddq"*num_points2D) |
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xys = np.column_stack([tuple(map(float, x_y_id_s[0::3])), |
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tuple(map(float, x_y_id_s[1::3]))]) |
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point3D_ids = np.array(tuple(map(int, x_y_id_s[2::3]))) |
|
images[image_id] = Image( |
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id=image_id, qvec=qvec, tvec=tvec, |
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camera_id=camera_id, name=image_name, |
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xys=xys, point3D_ids=point3D_ids) |
|
if path_to_model_file is not None: |
|
fid.close() |
|
return images |
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|
|
|
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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") |
|
|
|
|
|
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") |
|
|
|
|
|
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 |
|
|
|
|
|
def read_points3D_binary(path_to_model_file=None, fid=None): |
|
""" |
|
see: src/base/reconstruction.cc |
|
void Reconstruction::ReadPoints3DBinary(const std::string& path) |
|
void Reconstruction::WritePoints3DBinary(const std::string& path) |
|
""" |
|
points3D = {} |
|
if fid is None: |
|
fid = open(path_to_model_file, "rb") |
|
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) |
|
if path_to_model_file is not None: |
|
fid.close() |
|
return points3D |
|
|
|
|
|
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") |
|
|
|
|
|
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=""): |
|
|
|
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], |
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1 - 2 * qvec[1]**2 - 2 * qvec[2]**2]]) |
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|
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def rotmat2qvec(R): |
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Rxx, Ryx, Rzx, Rxy, Ryy, Rzy, Rxz, Ryz, Rzz = R.flat |
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K = np.array([ |
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[Rxx - Ryy - Rzz, 0, 0, 0], |
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[Ryx + Rxy, Ryy - Rxx - Rzz, 0, 0], |
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[Rzx + Rxz, Rzy + Ryz, Rzz - Rxx - Ryy, 0], |
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[Ryz - Rzy, Rzx - Rxz, Rxy - Ryx, Rxx + Ryy + Rzz]]) / 3.0 |
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eigvals, eigvecs = np.linalg.eigh(K) |
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qvec = eigvecs[[3, 0, 1, 2], np.argmax(eigvals)] |
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if qvec[0] < 0: |
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qvec *= -1 |
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return qvec |
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