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https://github.com/introlab/rtabmap_ros.git
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132 lines
5.2 KiB
Python
132 lines
5.2 KiB
Python
# Copyright 2025 matlabbe
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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#
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# * Redistributions of source code must retain the above copyright
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# notice, this list of conditions and the following disclaimer.
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#
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# * Redistributions in binary form must reproduce the above copyright
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# notice, this list of conditions and the following disclaimer in the
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# documentation and/or other materials provided with the distribution.
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#
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# * Neither the name of the matlabbe nor the names of its
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# contributors may be used to endorse or promote products derived from
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# this software without specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
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# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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# POSSIBILITY OF SUCH DAMAGE.
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"""
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Compress numpy arrays into RTAB-Map's ``cv::Mat`` wire format.
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RTAB-Map stores and transmits matrices -- images, laser scans, descriptors -- as a zlib
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payload followed by a 12-byte trailer recording the shape and the element type. Database
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blobs and the compressed fields of ``rtabmap_msgs`` messages both use it.
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The layout is::
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[ zlib stream of the elements in C order ][ rows ][ cols ][ type ]
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int32 int32 int32
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The three trailer fields are written with ``struct`` format ``'iii'`` -- native byte order
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and size, matching the C++ side's raw ``int`` writes. That makes the encoding
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**host-endian**, so a blob does not travel between machines of opposite endianness.
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``type`` is the OpenCV depth of the elements: 0 ``CV_8U``, 1 ``CV_8S``, 2 ``CV_16U``,
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3 ``CV_16S``, 4 ``CV_32S``, 5 ``CV_32F``, 6 ``CV_64F``.
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These two functions are the Python side of that format. They match ``compressData()`` and
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``uncompressData()`` in RTAB-Map's ``corelib/src/Compression.cpp`` byte for byte, so a
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matrix written by either side can be read by the other.
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Single-channel matrices only. The C++ encoder packs the channel count into the type code
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alongside the depth; the tables here cover the single-channel depths ``CV_8U`` through
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``CV_64F``, which is what the codes 0 to 6 mean.
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"""
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import struct
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import zlib
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import numpy as np
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def compress(data):
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"""
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Compress a 1-D or 2-D array into RTAB-Map's format.
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:param data: a single-channel array whose dtype is one of ``uint8``, ``int8``,
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``uint16``, ``int16``, ``int32``, ``float32`` or ``float64``. A 1-D array of
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length ``n`` is recorded as a 1-by-``n`` matrix, which is the shape
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:func:`uncompress` gives back. Any memory layout is accepted; the bytes are
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always written in C order.
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:returns: a ``bytearray`` holding the zlib payload followed by the trailer described
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in the module docstring.
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:raises AssertionError: if ``data`` has more than two dimensions.
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:raises KeyError: if its dtype is not one of the seven above -- ``int64`` and
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``float16`` have no encoding in this format.
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"""
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assert data.ndim == 1 or data.ndim == 2
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dim1 = 1
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if data.ndim == 1:
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dim1 = 1
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dim2 = len(data)
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else:
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dim1 = data.shape[0]
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dim2 = data.shape[1]
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numpy_type_to_cvtype = {
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'uint8': 0,
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'int8': 1,
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'uint16': 2,
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'int16': 3,
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'int32': 4,
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'float32': 5,
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'float64': 6,
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}
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compressed_data = bytearray(zlib.compress(data.tobytes()))
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compressed_data.extend(
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struct.pack('iii', dim1, dim2, numpy_type_to_cvtype[data.dtype.name])
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)
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return compressed_data
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def uncompress(data):
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"""
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Restore an array written by :func:`compress` or by RTAB-Map's C++ side.
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:param data: a bytes-like object laid out as :func:`compress` returns.
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:returns: a 2-D array of the recorded shape and dtype. It is 2-D even when
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:func:`compress` was handed a 1-D array, and it is **read-only**: it views the
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decompressed buffer instead of copying it, so call ``.copy()`` before writing.
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:raises KeyError: if the trailer's type code is not a single-channel depth 0 to 6,
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which is what a multi-channel matrix from the C++ side encodes to.
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"""
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cvtype_to_numpy_type = {
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0: 'uint8',
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1: 'int8',
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2: 'uint16',
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3: 'int16',
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4: 'int32',
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5: 'float32',
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6: 'float64',
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}
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out = zlib.decompress(data[: len(data) - 3 * 4])
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rows, cols, datatype = struct.unpack_from('iii', data, offset=len(data) - 3 * 4)
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data = np.frombuffer(out, dtype=cvtype_to_numpy_type[datatype])
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return data.reshape((rows, cols))
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