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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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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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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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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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def read_cameras_binary(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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cameras = {} |
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with open(path_to_model_file, "rb") as fid: |
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num_cameras = read_next_bytes(fid, 8, "Q")[0] |
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for camera_line_index 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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return cameras |
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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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def read_images_binary(path_to_model_file): |
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""" |
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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) |
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""" |
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images = {} |
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with open(path_to_model_file, "rb") as fid: |
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num_reg_images = read_next_bytes(fid, 8, "Q")[0] |
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for image_index in range(num_reg_images): |
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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]))) |
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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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def read_points3D_text(path): |
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""" |
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see: src/base/reconstruction.cc |
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void Reconstruction::ReadPoints3DText(const std::string& path) |
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void Reconstruction::WritePoints3DText(const std::string& path) |
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""" |
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points3D = {} |
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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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point3D_id = int(elems[0]) |
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xyz = np.array(tuple(map(float, elems[1:4]))) |
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rgb = np.array(tuple(map(int, elems[4:7]))) |
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error = float(elems[7]) |
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image_ids = np.array(tuple(map(int, elems[8::2]))) |
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point2D_idxs = np.array(tuple(map(int, elems[9::2]))) |
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points3D[point3D_id] = Point3D(id=point3D_id, xyz=xyz, rgb=rgb, |
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error=error, image_ids=image_ids, |
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point2D_idxs=point2D_idxs) |
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return points3D |
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def read_points3d_binary(path_to_model_file): |
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""" |
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see: src/base/reconstruction.cc |
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void Reconstruction::ReadPoints3DBinary(const std::string& path) |
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void Reconstruction::WritePoints3DBinary(const std::string& path) |
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""" |
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points3D = {} |
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with open(path_to_model_file, "rb") as fid: |
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num_points = read_next_bytes(fid, 8, "Q")[0] |
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for point_line_index in range(num_points): |
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binary_point_line_properties = read_next_bytes( |
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fid, num_bytes=43, format_char_sequence="QdddBBBd") |
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point3D_id = binary_point_line_properties[0] |
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xyz = np.array(binary_point_line_properties[1:4]) |
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rgb = np.array(binary_point_line_properties[4:7]) |
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error = np.array(binary_point_line_properties[7]) |
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track_length = read_next_bytes( |
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fid, num_bytes=8, format_char_sequence="Q")[0] |
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track_elems = read_next_bytes( |
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fid, num_bytes=8*track_length, |
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format_char_sequence="ii"*track_length) |
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image_ids = np.array(tuple(map(int, track_elems[0::2]))) |
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point2D_idxs = np.array(tuple(map(int, track_elems[1::2]))) |
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points3D[point3D_id] = Point3D( |
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id=point3D_id, xyz=xyz, rgb=rgb, |
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error=error, image_ids=image_ids, |
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point2D_idxs=point2D_idxs) |
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return points3D |
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def read_model(path, ext): |
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if ext == ".txt": |
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cameras = read_cameras_text(os.path.join(path, "cameras" + ext)) |
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images = read_images_text(os.path.join(path, "images" + ext)) |
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points3D = read_points3D_text(os.path.join(path, "points3D") + ext) |
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else: |
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cameras = read_cameras_binary(os.path.join(path, "cameras" + ext)) |
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images = read_images_binary(os.path.join(path, "images" + ext)) |
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points3D = read_points3d_binary(os.path.join(path, "points3D") + ext) |
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return cameras, images, points3D |
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def qvec2rotmat(qvec): |
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return np.array([ |
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[1 - 2 * qvec[2]**2 - 2 * qvec[3]**2, |
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2 * qvec[1] * qvec[2] - 2 * qvec[0] * qvec[3], |
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2 * qvec[3] * qvec[1] + 2 * qvec[0] * qvec[2]], |
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[2 * qvec[1] * qvec[2] + 2 * qvec[0] * qvec[3], |
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1 - 2 * qvec[1]**2 - 2 * qvec[3]**2, |
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2 * qvec[2] * qvec[3] - 2 * qvec[0] * qvec[1]], |
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[2 * qvec[3] * qvec[1] - 2 * qvec[0] * qvec[2], |
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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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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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