First Commit
This commit is contained in:
marco
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__all__: list[str] = []
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# Enumerations
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StsOk: int
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STS_OK: int
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StsBackTrace: int
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STS_BACK_TRACE: int
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StsError: int
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STS_ERROR: int
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StsInternal: int
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STS_INTERNAL: int
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StsNoMem: int
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STS_NO_MEM: int
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StsBadArg: int
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STS_BAD_ARG: int
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StsBadFunc: int
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STS_BAD_FUNC: int
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StsNoConv: int
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STS_NO_CONV: int
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StsAutoTrace: int
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STS_AUTO_TRACE: int
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HeaderIsNull: int
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HEADER_IS_NULL: int
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BadImageSize: int
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BAD_IMAGE_SIZE: int
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BadOffset: int
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BAD_OFFSET: int
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BadDataPtr: int
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BAD_DATA_PTR: int
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BadStep: int
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BAD_STEP: int
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BadModelOrChSeq: int
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BAD_MODEL_OR_CH_SEQ: int
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BadNumChannels: int
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BAD_NUM_CHANNELS: int
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BadNumChannel1U: int
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BAD_NUM_CHANNEL1U: int
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BadDepth: int
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BAD_DEPTH: int
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BadAlphaChannel: int
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BAD_ALPHA_CHANNEL: int
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BadOrder: int
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BAD_ORDER: int
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BadOrigin: int
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BAD_ORIGIN: int
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BadAlign: int
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BAD_ALIGN: int
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BadCallBack: int
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BAD_CALL_BACK: int
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BadTileSize: int
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BAD_TILE_SIZE: int
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BadCOI: int
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BAD_COI: int
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BadROISize: int
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BAD_ROISIZE: int
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MaskIsTiled: int
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MASK_IS_TILED: int
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StsNullPtr: int
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STS_NULL_PTR: int
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StsVecLengthErr: int
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STS_VEC_LENGTH_ERR: int
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StsFilterStructContentErr: int
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STS_FILTER_STRUCT_CONTENT_ERR: int
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StsKernelStructContentErr: int
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STS_KERNEL_STRUCT_CONTENT_ERR: int
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StsFilterOffsetErr: int
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STS_FILTER_OFFSET_ERR: int
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StsBadSize: int
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STS_BAD_SIZE: int
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StsDivByZero: int
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STS_DIV_BY_ZERO: int
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StsInplaceNotSupported: int
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STS_INPLACE_NOT_SUPPORTED: int
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StsObjectNotFound: int
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STS_OBJECT_NOT_FOUND: int
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StsUnmatchedFormats: int
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STS_UNMATCHED_FORMATS: int
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StsBadFlag: int
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STS_BAD_FLAG: int
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StsBadPoint: int
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STS_BAD_POINT: int
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StsBadMask: int
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STS_BAD_MASK: int
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StsUnmatchedSizes: int
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STS_UNMATCHED_SIZES: int
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StsUnsupportedFormat: int
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STS_UNSUPPORTED_FORMAT: int
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StsOutOfRange: int
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STS_OUT_OF_RANGE: int
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StsParseError: int
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STS_PARSE_ERROR: int
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StsNotImplemented: int
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STS_NOT_IMPLEMENTED: int
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StsBadMemBlock: int
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STS_BAD_MEM_BLOCK: int
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StsAssert: int
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STS_ASSERT: int
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GpuNotSupported: int
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GPU_NOT_SUPPORTED: int
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GpuApiCallError: int
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GPU_API_CALL_ERROR: int
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OpenGlNotSupported: int
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OPEN_GL_NOT_SUPPORTED: int
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OpenGlApiCallError: int
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OPEN_GL_API_CALL_ERROR: int
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OpenCLApiCallError: int
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OPEN_CLAPI_CALL_ERROR: int
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OpenCLDoubleNotSupported: int
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OPEN_CLDOUBLE_NOT_SUPPORTED: int
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OpenCLInitError: int
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OPEN_CLINIT_ERROR: int
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OpenCLNoAMDBlasFft: int
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OPEN_CLNO_AMDBLAS_FFT: int
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Code = int
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"""One of [StsOk, STS_OK, StsBackTrace, STS_BACK_TRACE, StsError, STS_ERROR, StsInternal, STS_INTERNAL, StsNoMem, STS_NO_MEM, StsBadArg, STS_BAD_ARG, StsBadFunc, STS_BAD_FUNC, StsNoConv, STS_NO_CONV, StsAutoTrace, STS_AUTO_TRACE, HeaderIsNull, HEADER_IS_NULL, BadImageSize, BAD_IMAGE_SIZE, BadOffset, BAD_OFFSET, BadDataPtr, BAD_DATA_PTR, BadStep, BAD_STEP, BadModelOrChSeq, BAD_MODEL_OR_CH_SEQ, BadNumChannels, BAD_NUM_CHANNELS, BadNumChannel1U, BAD_NUM_CHANNEL1U, BadDepth, BAD_DEPTH, BadAlphaChannel, BAD_ALPHA_CHANNEL, BadOrder, BAD_ORDER, BadOrigin, BAD_ORIGIN, BadAlign, BAD_ALIGN, BadCallBack, BAD_CALL_BACK, BadTileSize, BAD_TILE_SIZE, BadCOI, BAD_COI, BadROISize, BAD_ROISIZE, MaskIsTiled, MASK_IS_TILED, StsNullPtr, STS_NULL_PTR, StsVecLengthErr, STS_VEC_LENGTH_ERR, StsFilterStructContentErr, STS_FILTER_STRUCT_CONTENT_ERR, StsKernelStructContentErr, STS_KERNEL_STRUCT_CONTENT_ERR, StsFilterOffsetErr, STS_FILTER_OFFSET_ERR, StsBadSize, STS_BAD_SIZE, StsDivByZero, STS_DIV_BY_ZERO, StsInplaceNotSupported, STS_INPLACE_NOT_SUPPORTED, StsObjectNotFound, STS_OBJECT_NOT_FOUND, StsUnmatchedFormats, STS_UNMATCHED_FORMATS, StsBadFlag, STS_BAD_FLAG, StsBadPoint, STS_BAD_POINT, StsBadMask, STS_BAD_MASK, StsUnmatchedSizes, STS_UNMATCHED_SIZES, StsUnsupportedFormat, STS_UNSUPPORTED_FORMAT, StsOutOfRange, STS_OUT_OF_RANGE, StsParseError, STS_PARSE_ERROR, StsNotImplemented, STS_NOT_IMPLEMENTED, StsBadMemBlock, STS_BAD_MEM_BLOCK, StsAssert, STS_ASSERT, GpuNotSupported, GPU_NOT_SUPPORTED, GpuApiCallError, GPU_API_CALL_ERROR, OpenGlNotSupported, OPEN_GL_NOT_SUPPORTED, OpenGlApiCallError, OPEN_GL_API_CALL_ERROR, OpenCLApiCallError, OPEN_CLAPI_CALL_ERROR, OpenCLDoubleNotSupported, OPEN_CLDOUBLE_NOT_SUPPORTED, OpenCLInitError, OPEN_CLINIT_ERROR, OpenCLNoAMDBlasFft, OPEN_CLNO_AMDBLAS_FFT]"""
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+3617
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Load Diff
+21
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MIT License
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Copyright (c) Olli-Pekka Heinisuo
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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+181
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'''
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OpenCV Python binary extension loader
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'''
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import os
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import importlib
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import sys
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__all__ = []
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try:
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import numpy
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import numpy.core.multiarray
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except ImportError:
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print('OpenCV bindings requires "numpy" package.')
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print('Install it via command:')
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print(' pip install numpy')
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raise
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# TODO
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# is_x64 = sys.maxsize > 2**32
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def __load_extra_py_code_for_module(base, name, enable_debug_print=False):
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module_name = "{}.{}".format(__name__, name)
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export_module_name = "{}.{}".format(base, name)
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native_module = sys.modules.pop(module_name, None)
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try:
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py_module = importlib.import_module(module_name)
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except (ImportError, AttributeError) as err:
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if enable_debug_print:
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print("Can't load Python code for module:", module_name,
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". Reason:", err)
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# Extension doesn't contain extra py code
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return False
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if base in sys.modules and not hasattr(sys.modules[base], name):
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setattr(sys.modules[base], name, py_module)
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sys.modules[export_module_name] = py_module
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# If it is C extension module it is already loaded by cv2 package
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if native_module:
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setattr(py_module, "_native", native_module)
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for k, v in filter(lambda kv: not hasattr(py_module, kv[0]),
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native_module.__dict__.items()):
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if enable_debug_print: print(' symbol({}): {} = {}'.format(name, k, v))
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setattr(py_module, k, v)
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return True
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def __collect_extra_submodules(enable_debug_print=False):
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def modules_filter(module):
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return all((
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# module is not internal
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not module.startswith("_"),
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not module.startswith("python-"),
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# it is not a file
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os.path.isdir(os.path.join(_extra_submodules_init_path, module))
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))
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if sys.version_info[0] < 3:
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if enable_debug_print:
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print("Extra submodules is loaded only for Python 3")
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return []
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__INIT_FILE_PATH = os.path.abspath(__file__)
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_extra_submodules_init_path = os.path.dirname(__INIT_FILE_PATH)
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return filter(modules_filter, os.listdir(_extra_submodules_init_path))
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def bootstrap():
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import sys
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import copy
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save_sys_path = copy.copy(sys.path)
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if hasattr(sys, 'OpenCV_LOADER'):
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print(sys.path)
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raise ImportError('ERROR: recursion is detected during loading of "cv2" binary extensions. Check OpenCV installation.')
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sys.OpenCV_LOADER = True
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DEBUG = False
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if hasattr(sys, 'OpenCV_LOADER_DEBUG'):
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DEBUG = True
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import platform
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if DEBUG: print('OpenCV loader: os.name="{}" platform.system()="{}"'.format(os.name, str(platform.system())))
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LOADER_DIR = os.path.dirname(os.path.abspath(os.path.realpath(__file__)))
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PYTHON_EXTENSIONS_PATHS = []
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BINARIES_PATHS = []
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g_vars = globals()
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l_vars = locals().copy()
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if sys.version_info[:2] < (3, 0):
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from . load_config_py2 import exec_file_wrapper
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else:
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from . load_config_py3 import exec_file_wrapper
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def load_first_config(fnames, required=True):
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for fname in fnames:
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fpath = os.path.join(LOADER_DIR, fname)
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if not os.path.exists(fpath):
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if DEBUG: print('OpenCV loader: config not found, skip: {}'.format(fpath))
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continue
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if DEBUG: print('OpenCV loader: loading config: {}'.format(fpath))
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exec_file_wrapper(fpath, g_vars, l_vars)
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return True
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if required:
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raise ImportError('OpenCV loader: missing configuration file: {}. Check OpenCV installation.'.format(fnames))
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load_first_config(['config.py'], True)
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load_first_config([
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'config-{}.{}.py'.format(sys.version_info[0], sys.version_info[1]),
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'config-{}.py'.format(sys.version_info[0])
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], True)
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if DEBUG: print('OpenCV loader: PYTHON_EXTENSIONS_PATHS={}'.format(str(l_vars['PYTHON_EXTENSIONS_PATHS'])))
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if DEBUG: print('OpenCV loader: BINARIES_PATHS={}'.format(str(l_vars['BINARIES_PATHS'])))
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applySysPathWorkaround = False
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if hasattr(sys, 'OpenCV_REPLACE_SYS_PATH_0'):
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applySysPathWorkaround = True
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else:
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try:
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BASE_DIR = os.path.dirname(LOADER_DIR)
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if sys.path[0] == BASE_DIR or os.path.realpath(sys.path[0]) == BASE_DIR:
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applySysPathWorkaround = True
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except:
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if DEBUG: print('OpenCV loader: exception during checking workaround for sys.path[0]')
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pass # applySysPathWorkaround is False
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for p in reversed(l_vars['PYTHON_EXTENSIONS_PATHS']):
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sys.path.insert(1 if not applySysPathWorkaround else 0, p)
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if os.name == 'nt':
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if sys.version_info[:2] >= (3, 8): # https://github.com/python/cpython/pull/12302
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for p in l_vars['BINARIES_PATHS']:
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try:
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os.add_dll_directory(p)
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except Exception as e:
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if DEBUG: print('Failed os.add_dll_directory(): '+ str(e))
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pass
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os.environ['PATH'] = ';'.join(l_vars['BINARIES_PATHS']) + ';' + os.environ.get('PATH', '')
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if DEBUG: print('OpenCV loader: PATH={}'.format(str(os.environ['PATH'])))
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else:
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# amending of LD_LIBRARY_PATH works for sub-processes only
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os.environ['LD_LIBRARY_PATH'] = ':'.join(l_vars['BINARIES_PATHS']) + ':' + os.environ.get('LD_LIBRARY_PATH', '')
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if DEBUG: print("Relink everything from native cv2 module to cv2 package")
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py_module = sys.modules.pop("cv2")
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native_module = importlib.import_module("cv2")
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sys.modules["cv2"] = py_module
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setattr(py_module, "_native", native_module)
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for item_name, item in filter(lambda kv: kv[0] not in ("__file__", "__loader__", "__spec__",
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"__name__", "__package__"),
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native_module.__dict__.items()):
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if item_name not in g_vars:
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g_vars[item_name] = item
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sys.path = save_sys_path # multiprocessing should start from bootstrap code (https://github.com/opencv/opencv/issues/18502)
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try:
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del sys.OpenCV_LOADER
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except Exception as e:
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if DEBUG:
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print("Exception during delete OpenCV_LOADER:", e)
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if DEBUG: print('OpenCV loader: binary extension... OK')
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|
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for submodule in __collect_extra_submodules(DEBUG):
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if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
|
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if DEBUG: print("Extra Python code for", submodule, "is loaded")
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if DEBUG: print('OpenCV loader: DONE')
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bootstrap()
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+6858
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+327
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__all__: list[str] = []
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|
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import cv2
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import cv2.typing
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import typing as _typing
|
||||
|
||||
|
||||
# Enumerations
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CORNER_REFINE_NONE: int
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CORNER_REFINE_SUBPIX: int
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CORNER_REFINE_CONTOUR: int
|
||||
CORNER_REFINE_APRILTAG: int
|
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CornerRefineMethod = int
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"""One of [CORNER_REFINE_NONE, CORNER_REFINE_SUBPIX, CORNER_REFINE_CONTOUR, CORNER_REFINE_APRILTAG]"""
|
||||
|
||||
DICT_4X4_50: int
|
||||
DICT_4X4_100: int
|
||||
DICT_4X4_250: int
|
||||
DICT_4X4_1000: int
|
||||
DICT_5X5_50: int
|
||||
DICT_5X5_100: int
|
||||
DICT_5X5_250: int
|
||||
DICT_5X5_1000: int
|
||||
DICT_6X6_50: int
|
||||
DICT_6X6_100: int
|
||||
DICT_6X6_250: int
|
||||
DICT_6X6_1000: int
|
||||
DICT_7X7_50: int
|
||||
DICT_7X7_100: int
|
||||
DICT_7X7_250: int
|
||||
DICT_7X7_1000: int
|
||||
DICT_ARUCO_ORIGINAL: int
|
||||
DICT_APRILTAG_16h5: int
|
||||
DICT_APRILTAG_16H5: int
|
||||
DICT_APRILTAG_25h9: int
|
||||
DICT_APRILTAG_25H9: int
|
||||
DICT_APRILTAG_36h10: int
|
||||
DICT_APRILTAG_36H10: int
|
||||
DICT_APRILTAG_36h11: int
|
||||
DICT_APRILTAG_36H11: int
|
||||
DICT_ARUCO_MIP_36h12: int
|
||||
DICT_ARUCO_MIP_36H12: int
|
||||
PredefinedDictionaryType = int
|
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"""One of [DICT_4X4_50, DICT_4X4_100, DICT_4X4_250, DICT_4X4_1000, DICT_5X5_50, DICT_5X5_100, DICT_5X5_250, DICT_5X5_1000, DICT_6X6_50, DICT_6X6_100, DICT_6X6_250, DICT_6X6_1000, DICT_7X7_50, DICT_7X7_100, DICT_7X7_250, DICT_7X7_1000, DICT_ARUCO_ORIGINAL, DICT_APRILTAG_16h5, DICT_APRILTAG_16H5, DICT_APRILTAG_25h9, DICT_APRILTAG_25H9, DICT_APRILTAG_36h10, DICT_APRILTAG_36H10, DICT_APRILTAG_36h11, DICT_APRILTAG_36H11, DICT_ARUCO_MIP_36h12, DICT_ARUCO_MIP_36H12]"""
|
||||
|
||||
|
||||
|
||||
# Classes
|
||||
class Board:
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, objPoints: _typing.Sequence[cv2.typing.MatLike], dictionary: Dictionary, ids: cv2.typing.MatLike) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, objPoints: _typing.Sequence[cv2.UMat], dictionary: Dictionary, ids: cv2.UMat) -> None: ...
|
||||
|
||||
def getDictionary(self) -> Dictionary: ...
|
||||
|
||||
def getObjPoints(self) -> _typing.Sequence[_typing.Sequence[cv2.typing.Point3f]]: ...
|
||||
|
||||
def getIds(self) -> _typing.Sequence[int]: ...
|
||||
|
||||
def getRightBottomCorner(self) -> cv2.typing.Point3f: ...
|
||||
|
||||
@_typing.overload
|
||||
def matchImagePoints(self, detectedCorners: _typing.Sequence[cv2.typing.MatLike], detectedIds: cv2.typing.MatLike, objPoints: cv2.typing.MatLike | None = ..., imgPoints: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def matchImagePoints(self, detectedCorners: _typing.Sequence[cv2.UMat], detectedIds: cv2.UMat, objPoints: cv2.UMat | None = ..., imgPoints: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat]: ...
|
||||
|
||||
@_typing.overload
|
||||
def generateImage(self, outSize: cv2.typing.Size, img: cv2.typing.MatLike | None = ..., marginSize: int = ..., borderBits: int = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def generateImage(self, outSize: cv2.typing.Size, img: cv2.UMat | None = ..., marginSize: int = ..., borderBits: int = ...) -> cv2.UMat: ...
|
||||
|
||||
|
||||
class GridBoard(Board):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, size: cv2.typing.Size, markerLength: float, markerSeparation: float, dictionary: Dictionary, ids: cv2.typing.MatLike | None = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, size: cv2.typing.Size, markerLength: float, markerSeparation: float, dictionary: Dictionary, ids: cv2.UMat | None = ...) -> None: ...
|
||||
|
||||
def getGridSize(self) -> cv2.typing.Size: ...
|
||||
|
||||
def getMarkerLength(self) -> float: ...
|
||||
|
||||
def getMarkerSeparation(self) -> float: ...
|
||||
|
||||
|
||||
class CharucoBoard(Board):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, size: cv2.typing.Size, squareLength: float, markerLength: float, dictionary: Dictionary, ids: cv2.typing.MatLike | None = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, size: cv2.typing.Size, squareLength: float, markerLength: float, dictionary: Dictionary, ids: cv2.UMat | None = ...) -> None: ...
|
||||
|
||||
def setLegacyPattern(self, legacyPattern: bool) -> None: ...
|
||||
|
||||
def getLegacyPattern(self) -> bool: ...
|
||||
|
||||
def getChessboardSize(self) -> cv2.typing.Size: ...
|
||||
|
||||
def getSquareLength(self) -> float: ...
|
||||
|
||||
def getMarkerLength(self) -> float: ...
|
||||
|
||||
def getChessboardCorners(self) -> _typing.Sequence[cv2.typing.Point3f]: ...
|
||||
|
||||
@_typing.overload
|
||||
def checkCharucoCornersCollinear(self, charucoIds: cv2.typing.MatLike) -> bool: ...
|
||||
@_typing.overload
|
||||
def checkCharucoCornersCollinear(self, charucoIds: cv2.UMat) -> bool: ...
|
||||
|
||||
|
||||
class DetectorParameters:
|
||||
adaptiveThreshWinSizeMin: int
|
||||
adaptiveThreshWinSizeMax: int
|
||||
adaptiveThreshWinSizeStep: int
|
||||
adaptiveThreshConstant: float
|
||||
minMarkerPerimeterRate: float
|
||||
maxMarkerPerimeterRate: float
|
||||
polygonalApproxAccuracyRate: float
|
||||
minCornerDistanceRate: float
|
||||
minDistanceToBorder: int
|
||||
minMarkerDistanceRate: float
|
||||
minGroupDistance: float
|
||||
cornerRefinementMethod: int
|
||||
cornerRefinementWinSize: int
|
||||
relativeCornerRefinmentWinSize: float
|
||||
cornerRefinementMaxIterations: int
|
||||
cornerRefinementMinAccuracy: float
|
||||
markerBorderBits: int
|
||||
perspectiveRemovePixelPerCell: int
|
||||
perspectiveRemoveIgnoredMarginPerCell: float
|
||||
maxErroneousBitsInBorderRate: float
|
||||
minOtsuStdDev: float
|
||||
errorCorrectionRate: float
|
||||
aprilTagQuadDecimate: float
|
||||
aprilTagQuadSigma: float
|
||||
aprilTagMinClusterPixels: int
|
||||
aprilTagMaxNmaxima: int
|
||||
aprilTagCriticalRad: float
|
||||
aprilTagMaxLineFitMse: float
|
||||
aprilTagMinWhiteBlackDiff: int
|
||||
aprilTagDeglitch: int
|
||||
detectInvertedMarker: bool
|
||||
useAruco3Detection: bool
|
||||
minSideLengthCanonicalImg: int
|
||||
minMarkerLengthRatioOriginalImg: float
|
||||
validBitIdThreshold: float
|
||||
|
||||
# Functions
|
||||
def __init__(self) -> None: ...
|
||||
|
||||
def readDetectorParameters(self, fn: cv2.FileNode) -> bool: ...
|
||||
|
||||
def writeDetectorParameters(self, fs: cv2.FileStorage, name: str = ...) -> bool: ...
|
||||
|
||||
|
||||
class RefineParameters:
|
||||
minRepDistance: float
|
||||
errorCorrectionRate: float
|
||||
checkAllOrders: bool
|
||||
|
||||
# Functions
|
||||
def __init__(self, minRepDistance: float = ..., errorCorrectionRate: float = ..., checkAllOrders: bool = ...) -> None: ...
|
||||
|
||||
def readRefineParameters(self, fn: cv2.FileNode) -> bool: ...
|
||||
|
||||
def writeRefineParameters(self, fs: cv2.FileStorage, name: str = ...) -> bool: ...
|
||||
|
||||
|
||||
class ArucoDetector(cv2.Algorithm):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, dictionary: Dictionary = ..., detectorParams: DetectorParameters = ..., refineParams: RefineParameters = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, dictionaries: _typing.Sequence[Dictionary], detectorParams: DetectorParameters = ..., refineParams: RefineParameters = ...) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def detectMarkers(self, image: cv2.typing.MatLike, corners: _typing.Sequence[cv2.typing.MatLike] | None = ..., ids: cv2.typing.MatLike | None = ..., rejectedImgPoints: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> tuple[_typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike]]: ...
|
||||
@_typing.overload
|
||||
def detectMarkers(self, image: cv2.UMat, corners: _typing.Sequence[cv2.UMat] | None = ..., ids: cv2.UMat | None = ..., rejectedImgPoints: _typing.Sequence[cv2.UMat] | None = ...) -> tuple[_typing.Sequence[cv2.UMat], cv2.UMat, _typing.Sequence[cv2.UMat]]: ...
|
||||
|
||||
@_typing.overload
|
||||
def detectMarkersWithConfidence(self, image: cv2.typing.MatLike, corners: _typing.Sequence[cv2.typing.MatLike] | None = ..., ids: cv2.typing.MatLike | None = ..., markersConfidence: cv2.typing.MatLike | None = ..., rejectedImgPoints: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> tuple[_typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike, cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike]]: ...
|
||||
@_typing.overload
|
||||
def detectMarkersWithConfidence(self, image: cv2.UMat, corners: _typing.Sequence[cv2.UMat] | None = ..., ids: cv2.UMat | None = ..., markersConfidence: cv2.UMat | None = ..., rejectedImgPoints: _typing.Sequence[cv2.UMat] | None = ...) -> tuple[_typing.Sequence[cv2.UMat], cv2.UMat, cv2.UMat, _typing.Sequence[cv2.UMat]]: ...
|
||||
|
||||
@_typing.overload
|
||||
def refineDetectedMarkers(self, image: cv2.typing.MatLike, board: Board, detectedCorners: _typing.Sequence[cv2.typing.MatLike], detectedIds: cv2.typing.MatLike, rejectedCorners: _typing.Sequence[cv2.typing.MatLike], cameraMatrix: cv2.typing.MatLike | None = ..., distCoeffs: cv2.typing.MatLike | None = ..., recoveredIdxs: cv2.typing.MatLike | None = ...) -> tuple[_typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def refineDetectedMarkers(self, image: cv2.UMat, board: Board, detectedCorners: _typing.Sequence[cv2.UMat], detectedIds: cv2.UMat, rejectedCorners: _typing.Sequence[cv2.UMat], cameraMatrix: cv2.UMat | None = ..., distCoeffs: cv2.UMat | None = ..., recoveredIdxs: cv2.UMat | None = ...) -> tuple[_typing.Sequence[cv2.UMat], cv2.UMat, _typing.Sequence[cv2.UMat], cv2.UMat]: ...
|
||||
|
||||
@_typing.overload
|
||||
def detectMarkersMultiDict(self, image: cv2.typing.MatLike, corners: _typing.Sequence[cv2.typing.MatLike] | None = ..., ids: cv2.typing.MatLike | None = ..., rejectedImgPoints: _typing.Sequence[cv2.typing.MatLike] | None = ..., dictIndices: cv2.typing.MatLike | None = ...) -> tuple[_typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def detectMarkersMultiDict(self, image: cv2.UMat, corners: _typing.Sequence[cv2.UMat] | None = ..., ids: cv2.UMat | None = ..., rejectedImgPoints: _typing.Sequence[cv2.UMat] | None = ..., dictIndices: cv2.UMat | None = ...) -> tuple[_typing.Sequence[cv2.UMat], cv2.UMat, _typing.Sequence[cv2.UMat], cv2.UMat]: ...
|
||||
|
||||
def getDictionary(self) -> Dictionary: ...
|
||||
|
||||
def setDictionary(self, dictionary: Dictionary) -> None: ...
|
||||
|
||||
def getDictionaries(self) -> _typing.Sequence[Dictionary]: ...
|
||||
|
||||
def setDictionaries(self, dictionaries: _typing.Sequence[Dictionary]) -> None: ...
|
||||
|
||||
def getDetectorParameters(self) -> DetectorParameters: ...
|
||||
|
||||
def setDetectorParameters(self, detectorParameters: DetectorParameters) -> None: ...
|
||||
|
||||
def getRefineParameters(self) -> RefineParameters: ...
|
||||
|
||||
def setRefineParameters(self, refineParameters: RefineParameters) -> None: ...
|
||||
|
||||
def write(self, fs: cv2.FileStorage, name: str) -> None: ...
|
||||
|
||||
def read(self, fn: cv2.FileNode) -> None: ...
|
||||
|
||||
|
||||
class Dictionary:
|
||||
bytesList: cv2.typing.MatLike
|
||||
markerSize: int
|
||||
maxCorrectionBits: int
|
||||
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, bytesList: cv2.typing.MatLike, _markerSize: int, maxcorr: int = ...) -> None: ...
|
||||
|
||||
def readDictionary(self, fn: cv2.FileNode) -> bool: ...
|
||||
|
||||
def writeDictionary(self, fs: cv2.FileStorage, name: str = ...) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def identify(self, onlyBits: cv2.typing.MatLike, maxCorrectionRate: float) -> tuple[bool, int, int]: ...
|
||||
@_typing.overload
|
||||
def identify(self, onlyCellPixelRatio: cv2.typing.MatLike, maxCorrectionRate: float, validBitIdThreshold: float) -> tuple[bool, int, int]: ...
|
||||
|
||||
@_typing.overload
|
||||
def getDistanceToId(self, bits: cv2.typing.MatLike, id: int, allRotations: bool = ...) -> int: ...
|
||||
@_typing.overload
|
||||
def getDistanceToId(self, bits: cv2.UMat, id: int, allRotations: bool = ...) -> int: ...
|
||||
|
||||
@_typing.overload
|
||||
def generateImageMarker(self, id: int, sidePixels: int, _img: cv2.typing.MatLike | None = ..., borderBits: int = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def generateImageMarker(self, id: int, sidePixels: int, _img: cv2.UMat | None = ..., borderBits: int = ...) -> cv2.UMat: ...
|
||||
|
||||
@staticmethod
|
||||
def getByteListFromBits(bits: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
||||
|
||||
@staticmethod
|
||||
def getBitsFromByteList(byteList: cv2.typing.MatLike, markerSize: int, rotationId: int = ...) -> cv2.typing.MatLike: ...
|
||||
|
||||
def getMarkerBits(self, markerId: int, rotationId: int = ...) -> cv2.typing.MatLike: ...
|
||||
|
||||
|
||||
class CharucoParameters:
|
||||
cameraMatrix: cv2.typing.MatLike
|
||||
distCoeffs: cv2.typing.MatLike
|
||||
minMarkers: int
|
||||
tryRefineMarkers: bool
|
||||
checkMarkers: bool
|
||||
|
||||
# Functions
|
||||
def __init__(self) -> None: ...
|
||||
|
||||
|
||||
class CharucoDetector(cv2.Algorithm):
|
||||
# Functions
|
||||
def __init__(self, board: CharucoBoard, charucoParams: CharucoParameters = ..., detectorParams: DetectorParameters = ..., refineParams: RefineParameters = ...) -> None: ...
|
||||
|
||||
def getBoard(self) -> CharucoBoard: ...
|
||||
|
||||
def setBoard(self, board: CharucoBoard) -> None: ...
|
||||
|
||||
def getCharucoParameters(self) -> CharucoParameters: ...
|
||||
|
||||
def setCharucoParameters(self, charucoParameters: CharucoParameters) -> None: ...
|
||||
|
||||
def getDetectorParameters(self) -> DetectorParameters: ...
|
||||
|
||||
def setDetectorParameters(self, detectorParameters: DetectorParameters) -> None: ...
|
||||
|
||||
def getRefineParameters(self) -> RefineParameters: ...
|
||||
|
||||
def setRefineParameters(self, refineParameters: RefineParameters) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def detectBoard(self, image: cv2.typing.MatLike, charucoCorners: cv2.typing.MatLike | None = ..., charucoIds: cv2.typing.MatLike | None = ..., markerCorners: _typing.Sequence[cv2.typing.MatLike] | None = ..., markerIds: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def detectBoard(self, image: cv2.UMat, charucoCorners: cv2.UMat | None = ..., charucoIds: cv2.UMat | None = ..., markerCorners: _typing.Sequence[cv2.UMat] | None = ..., markerIds: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat, _typing.Sequence[cv2.UMat], cv2.UMat]: ...
|
||||
|
||||
@_typing.overload
|
||||
def detectDiamonds(self, image: cv2.typing.MatLike, diamondCorners: _typing.Sequence[cv2.typing.MatLike] | None = ..., diamondIds: cv2.typing.MatLike | None = ..., markerCorners: _typing.Sequence[cv2.typing.MatLike] | None = ..., markerIds: cv2.typing.MatLike | None = ...) -> tuple[_typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike], cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def detectDiamonds(self, image: cv2.UMat, diamondCorners: _typing.Sequence[cv2.UMat] | None = ..., diamondIds: cv2.UMat | None = ..., markerCorners: _typing.Sequence[cv2.UMat] | None = ..., markerIds: cv2.UMat | None = ...) -> tuple[_typing.Sequence[cv2.UMat], cv2.UMat, _typing.Sequence[cv2.UMat], cv2.UMat]: ...
|
||||
|
||||
|
||||
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def drawDetectedCornersCharuco(image: cv2.typing.MatLike, charucoCorners: cv2.typing.MatLike, charucoIds: cv2.typing.MatLike | None = ..., cornerColor: cv2.typing.Scalar = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def drawDetectedCornersCharuco(image: cv2.UMat, charucoCorners: cv2.UMat, charucoIds: cv2.UMat | None = ..., cornerColor: cv2.typing.Scalar = ...) -> cv2.UMat: ...
|
||||
|
||||
@_typing.overload
|
||||
def drawDetectedDiamonds(image: cv2.typing.MatLike, diamondCorners: _typing.Sequence[cv2.typing.MatLike], diamondIds: cv2.typing.MatLike | None = ..., borderColor: cv2.typing.Scalar = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def drawDetectedDiamonds(image: cv2.UMat, diamondCorners: _typing.Sequence[cv2.UMat], diamondIds: cv2.UMat | None = ..., borderColor: cv2.typing.Scalar = ...) -> cv2.UMat: ...
|
||||
|
||||
@_typing.overload
|
||||
def drawDetectedMarkers(image: cv2.typing.MatLike, corners: _typing.Sequence[cv2.typing.MatLike], ids: cv2.typing.MatLike | None = ..., borderColor: cv2.typing.Scalar = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def drawDetectedMarkers(image: cv2.UMat, corners: _typing.Sequence[cv2.UMat], ids: cv2.UMat | None = ..., borderColor: cv2.typing.Scalar = ...) -> cv2.UMat: ...
|
||||
|
||||
def extendDictionary(nMarkers: int, markerSize: int, baseDictionary: Dictionary = ..., randomSeed: int = ...) -> Dictionary: ...
|
||||
|
||||
@_typing.overload
|
||||
def generateImageMarker(dictionary: Dictionary, id: int, sidePixels: int, img: cv2.typing.MatLike | None = ..., borderBits: int = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def generateImageMarker(dictionary: Dictionary, id: int, sidePixels: int, img: cv2.UMat | None = ..., borderBits: int = ...) -> cv2.UMat: ...
|
||||
|
||||
def getPredefinedDictionary(dict: int) -> Dictionary: ...
|
||||
|
||||
|
||||
@@ -0,0 +1,40 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
import cv2
|
||||
import cv2.typing
|
||||
import os
|
||||
import typing as _typing
|
||||
|
||||
|
||||
# Classes
|
||||
class BarcodeDetector(cv2.GraphicalCodeDetector):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, super_resolution_model_path: str | os.PathLike[str]) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def decodeWithType(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike) -> tuple[bool, _typing.Sequence[str], _typing.Sequence[str]]: ...
|
||||
@_typing.overload
|
||||
def decodeWithType(self, img: cv2.UMat, points: cv2.UMat) -> tuple[bool, _typing.Sequence[str], _typing.Sequence[str]]: ...
|
||||
|
||||
@_typing.overload
|
||||
def detectAndDecodeWithType(self, img: cv2.typing.MatLike, points: cv2.typing.MatLike | None = ...) -> tuple[bool, _typing.Sequence[str], _typing.Sequence[str], cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def detectAndDecodeWithType(self, img: cv2.UMat, points: cv2.UMat | None = ...) -> tuple[bool, _typing.Sequence[str], _typing.Sequence[str], cv2.UMat]: ...
|
||||
|
||||
def getDownsamplingThreshold(self) -> float: ...
|
||||
|
||||
def setDownsamplingThreshold(self, thresh: float) -> BarcodeDetector: ...
|
||||
|
||||
def getDetectorScales(self) -> _typing.Sequence[float]: ...
|
||||
|
||||
def setDetectorScales(self, sizes: _typing.Sequence[float]) -> BarcodeDetector: ...
|
||||
|
||||
def getGradientThreshold(self) -> float: ...
|
||||
|
||||
def setGradientThreshold(self, thresh: float) -> BarcodeDetector: ...
|
||||
|
||||
|
||||
|
||||
+165
@@ -0,0 +1,165 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
import cv2
|
||||
import cv2.typing
|
||||
import typing as _typing
|
||||
|
||||
|
||||
# Enumerations
|
||||
CCM_LINEAR: int
|
||||
CCM_AFFINE: int
|
||||
CcmType = int
|
||||
"""One of [CCM_LINEAR, CCM_AFFINE]"""
|
||||
|
||||
INITIAL_METHOD_WHITE_BALANCE: int
|
||||
INITIAL_METHOD_LEAST_SQUARE: int
|
||||
InitialMethodType = int
|
||||
"""One of [INITIAL_METHOD_WHITE_BALANCE, INITIAL_METHOD_LEAST_SQUARE]"""
|
||||
|
||||
COLORCHECKER_MACBETH: int
|
||||
COLORCHECKER_VINYL: int
|
||||
COLORCHECKER_DIGITAL_SG: int
|
||||
ColorCheckerType = int
|
||||
"""One of [COLORCHECKER_MACBETH, COLORCHECKER_VINYL, COLORCHECKER_DIGITAL_SG]"""
|
||||
|
||||
COLOR_SPACE_SRGB: int
|
||||
COLOR_SPACE_SRGBL: int
|
||||
COLOR_SPACE_ADOBE_RGB: int
|
||||
COLOR_SPACE_ADOBE_RGBL: int
|
||||
COLOR_SPACE_WIDE_GAMUT_RGB: int
|
||||
COLOR_SPACE_WIDE_GAMUT_RGBL: int
|
||||
COLOR_SPACE_PRO_PHOTO_RGB: int
|
||||
COLOR_SPACE_PRO_PHOTO_RGBL: int
|
||||
COLOR_SPACE_DCI_P3_RGB: int
|
||||
COLOR_SPACE_DCI_P3_RGBL: int
|
||||
COLOR_SPACE_APPLE_RGB: int
|
||||
COLOR_SPACE_APPLE_RGBL: int
|
||||
COLOR_SPACE_REC_709_RGB: int
|
||||
COLOR_SPACE_REC_709_RGBL: int
|
||||
COLOR_SPACE_REC_2020_RGB: int
|
||||
COLOR_SPACE_REC_2020_RGBL: int
|
||||
COLOR_SPACE_XYZ_D65_2: int
|
||||
COLOR_SPACE_XYZ_D50_2: int
|
||||
COLOR_SPACE_XYZ_D65_10: int
|
||||
COLOR_SPACE_XYZ_D50_10: int
|
||||
COLOR_SPACE_XYZ_A_2: int
|
||||
COLOR_SPACE_XYZ_A_10: int
|
||||
COLOR_SPACE_XYZ_D55_2: int
|
||||
COLOR_SPACE_XYZ_D55_10: int
|
||||
COLOR_SPACE_XYZ_D75_2: int
|
||||
COLOR_SPACE_XYZ_D75_10: int
|
||||
COLOR_SPACE_XYZ_E_2: int
|
||||
COLOR_SPACE_XYZ_E_10: int
|
||||
COLOR_SPACE_LAB_D65_2: int
|
||||
COLOR_SPACE_LAB_D50_2: int
|
||||
COLOR_SPACE_LAB_D65_10: int
|
||||
COLOR_SPACE_LAB_D50_10: int
|
||||
COLOR_SPACE_LAB_A_2: int
|
||||
COLOR_SPACE_LAB_A_10: int
|
||||
COLOR_SPACE_LAB_D55_2: int
|
||||
COLOR_SPACE_LAB_D55_10: int
|
||||
COLOR_SPACE_LAB_D75_2: int
|
||||
COLOR_SPACE_LAB_D75_10: int
|
||||
COLOR_SPACE_LAB_E_2: int
|
||||
COLOR_SPACE_LAB_E_10: int
|
||||
ColorSpace = int
|
||||
"""One of [COLOR_SPACE_SRGB, COLOR_SPACE_SRGBL, COLOR_SPACE_ADOBE_RGB, COLOR_SPACE_ADOBE_RGBL, COLOR_SPACE_WIDE_GAMUT_RGB, COLOR_SPACE_WIDE_GAMUT_RGBL, COLOR_SPACE_PRO_PHOTO_RGB, COLOR_SPACE_PRO_PHOTO_RGBL, COLOR_SPACE_DCI_P3_RGB, COLOR_SPACE_DCI_P3_RGBL, COLOR_SPACE_APPLE_RGB, COLOR_SPACE_APPLE_RGBL, COLOR_SPACE_REC_709_RGB, COLOR_SPACE_REC_709_RGBL, COLOR_SPACE_REC_2020_RGB, COLOR_SPACE_REC_2020_RGBL, COLOR_SPACE_XYZ_D65_2, COLOR_SPACE_XYZ_D50_2, COLOR_SPACE_XYZ_D65_10, COLOR_SPACE_XYZ_D50_10, COLOR_SPACE_XYZ_A_2, COLOR_SPACE_XYZ_A_10, COLOR_SPACE_XYZ_D55_2, COLOR_SPACE_XYZ_D55_10, COLOR_SPACE_XYZ_D75_2, COLOR_SPACE_XYZ_D75_10, COLOR_SPACE_XYZ_E_2, COLOR_SPACE_XYZ_E_10, COLOR_SPACE_LAB_D65_2, COLOR_SPACE_LAB_D50_2, COLOR_SPACE_LAB_D65_10, COLOR_SPACE_LAB_D50_10, COLOR_SPACE_LAB_A_2, COLOR_SPACE_LAB_A_10, COLOR_SPACE_LAB_D55_2, COLOR_SPACE_LAB_D55_10, COLOR_SPACE_LAB_D75_2, COLOR_SPACE_LAB_D75_10, COLOR_SPACE_LAB_E_2, COLOR_SPACE_LAB_E_10]"""
|
||||
|
||||
LINEARIZATION_IDENTITY: int
|
||||
LINEARIZATION_GAMMA: int
|
||||
LINEARIZATION_COLORPOLYFIT: int
|
||||
LINEARIZATION_COLORLOGPOLYFIT: int
|
||||
LINEARIZATION_GRAYPOLYFIT: int
|
||||
LINEARIZATION_GRAYLOGPOLYFIT: int
|
||||
LinearizationType = int
|
||||
"""One of [LINEARIZATION_IDENTITY, LINEARIZATION_GAMMA, LINEARIZATION_COLORPOLYFIT, LINEARIZATION_COLORLOGPOLYFIT, LINEARIZATION_GRAYPOLYFIT, LINEARIZATION_GRAYLOGPOLYFIT]"""
|
||||
|
||||
DISTANCE_CIE76: int
|
||||
DISTANCE_CIE94_GRAPHIC_ARTS: int
|
||||
DISTANCE_CIE94_TEXTILES: int
|
||||
DISTANCE_CIE2000: int
|
||||
DISTANCE_CMC_1TO1: int
|
||||
DISTANCE_CMC_2TO1: int
|
||||
DISTANCE_RGB: int
|
||||
DISTANCE_RGBL: int
|
||||
DistanceType = int
|
||||
"""One of [DISTANCE_CIE76, DISTANCE_CIE94_GRAPHIC_ARTS, DISTANCE_CIE94_TEXTILES, DISTANCE_CIE2000, DISTANCE_CMC_1TO1, DISTANCE_CMC_2TO1, DISTANCE_RGB, DISTANCE_RGBL]"""
|
||||
|
||||
|
||||
|
||||
# Classes
|
||||
class ColorCorrectionModel:
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, src: cv2.typing.MatLike, constColor: int) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, src: cv2.UMat, constColor: int) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, src: cv2.typing.MatLike, colors: cv2.typing.MatLike, refColorSpace: ColorSpace) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, src: cv2.UMat, colors: cv2.UMat, refColorSpace: ColorSpace) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, src: cv2.typing.MatLike, colors: cv2.typing.MatLike, refColorSpace: ColorSpace, coloredPatchesMask: cv2.typing.MatLike) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, src: cv2.UMat, colors: cv2.UMat, refColorSpace: ColorSpace, coloredPatchesMask: cv2.UMat) -> None: ...
|
||||
|
||||
def setColorSpace(self, cs: ColorSpace) -> None: ...
|
||||
|
||||
def setCcmType(self, ccmType: CcmType) -> None: ...
|
||||
|
||||
def setDistance(self, distance: DistanceType) -> None: ...
|
||||
|
||||
def setLinearization(self, linearizationType: LinearizationType) -> None: ...
|
||||
|
||||
def setLinearizationGamma(self, gamma: float) -> None: ...
|
||||
|
||||
def setLinearizationDegree(self, deg: int) -> None: ...
|
||||
|
||||
def setSaturatedThreshold(self, lower: float, upper: float) -> None: ...
|
||||
|
||||
def setWeightsList(self, weightsList: cv2.typing.MatLike) -> None: ...
|
||||
|
||||
def setWeightCoeff(self, weightsCoeff: float) -> None: ...
|
||||
|
||||
def setInitialMethod(self, initialMethodType: InitialMethodType) -> None: ...
|
||||
|
||||
def setMaxCount(self, maxCount: int) -> None: ...
|
||||
|
||||
def setEpsilon(self, epsilon: float) -> None: ...
|
||||
|
||||
def setRGB(self, rgb: bool) -> None: ...
|
||||
|
||||
def compute(self) -> cv2.typing.MatLike: ...
|
||||
|
||||
def getColorCorrectionMatrix(self) -> cv2.typing.MatLike: ...
|
||||
|
||||
def getLoss(self) -> float: ...
|
||||
|
||||
def getSrcLinearRGB(self) -> cv2.typing.MatLike: ...
|
||||
|
||||
def getRefLinearRGB(self) -> cv2.typing.MatLike: ...
|
||||
|
||||
def getMask(self) -> cv2.typing.MatLike: ...
|
||||
|
||||
def getWeights(self) -> cv2.typing.MatLike: ...
|
||||
|
||||
@_typing.overload
|
||||
def correctImage(self, src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., islinear: bool = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def correctImage(self, src: cv2.UMat, dst: cv2.UMat | None = ..., islinear: bool = ...) -> cv2.UMat: ...
|
||||
|
||||
def write(self, fs: cv2.FileStorage) -> None: ...
|
||||
|
||||
def read(self, node: cv2.FileNode) -> None: ...
|
||||
|
||||
|
||||
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def gammaCorrection(src: cv2.typing.MatLike, gamma: float, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def gammaCorrection(src: cv2.UMat, gamma: float, dst: cv2.UMat | None = ...) -> cv2.UMat: ...
|
||||
|
||||
|
||||
+24
@@ -0,0 +1,24 @@
|
||||
PYTHON_EXTENSIONS_PATHS = [
|
||||
LOADER_DIR
|
||||
] + PYTHON_EXTENSIONS_PATHS
|
||||
|
||||
ci_and_not_headless = False
|
||||
|
||||
try:
|
||||
from .version import ci_build, headless
|
||||
|
||||
ci_and_not_headless = ci_build and not headless
|
||||
except:
|
||||
pass
|
||||
|
||||
# the Qt plugin is included currently only in the pre-built wheels
|
||||
if sys.platform.startswith("linux") and ci_and_not_headless:
|
||||
os.environ["QT_QPA_PLATFORM_PLUGIN_PATH"] = os.path.join(
|
||||
os.path.dirname(os.path.abspath(__file__)), "qt", "plugins"
|
||||
)
|
||||
|
||||
# Qt will throw warning on Linux if fonts are not found
|
||||
if sys.platform.startswith("linux") and ci_and_not_headless:
|
||||
os.environ["QT_QPA_FONTDIR"] = os.path.join(
|
||||
os.path.dirname(os.path.abspath(__file__)), "qt", "fonts"
|
||||
)
|
||||
+5
@@ -0,0 +1,5 @@
|
||||
import os
|
||||
|
||||
BINARIES_PATHS = [
|
||||
os.path.join(os.path.join(LOADER_DIR, '../../'), 'lib64')
|
||||
] + BINARIES_PATHS
|
||||
+513
@@ -0,0 +1,513 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
import cv2
|
||||
import cv2.typing
|
||||
import typing as _typing
|
||||
|
||||
|
||||
# Enumerations
|
||||
FEATURE_SET_COMPUTE_10: int
|
||||
FEATURE_SET_COMPUTE_11: int
|
||||
FEATURE_SET_COMPUTE_12: int
|
||||
FEATURE_SET_COMPUTE_13: int
|
||||
FEATURE_SET_COMPUTE_20: int
|
||||
FEATURE_SET_COMPUTE_21: int
|
||||
FEATURE_SET_COMPUTE_30: int
|
||||
FEATURE_SET_COMPUTE_32: int
|
||||
FEATURE_SET_COMPUTE_35: int
|
||||
FEATURE_SET_COMPUTE_50: int
|
||||
GLOBAL_ATOMICS: int
|
||||
SHARED_ATOMICS: int
|
||||
NATIVE_DOUBLE: int
|
||||
WARP_SHUFFLE_FUNCTIONS: int
|
||||
DYNAMIC_PARALLELISM: int
|
||||
FeatureSet = int
|
||||
"""One of [FEATURE_SET_COMPUTE_10, FEATURE_SET_COMPUTE_11, FEATURE_SET_COMPUTE_12, FEATURE_SET_COMPUTE_13, FEATURE_SET_COMPUTE_20, FEATURE_SET_COMPUTE_21, FEATURE_SET_COMPUTE_30, FEATURE_SET_COMPUTE_32, FEATURE_SET_COMPUTE_35, FEATURE_SET_COMPUTE_50, GLOBAL_ATOMICS, SHARED_ATOMICS, NATIVE_DOUBLE, WARP_SHUFFLE_FUNCTIONS, DYNAMIC_PARALLELISM]"""
|
||||
|
||||
|
||||
HostMem_PAGE_LOCKED: int
|
||||
HOST_MEM_PAGE_LOCKED: int
|
||||
HostMem_SHARED: int
|
||||
HOST_MEM_SHARED: int
|
||||
HostMem_WRITE_COMBINED: int
|
||||
HOST_MEM_WRITE_COMBINED: int
|
||||
HostMem_AllocType = int
|
||||
"""One of [HostMem_PAGE_LOCKED, HOST_MEM_PAGE_LOCKED, HostMem_SHARED, HOST_MEM_SHARED, HostMem_WRITE_COMBINED, HOST_MEM_WRITE_COMBINED]"""
|
||||
|
||||
Event_DEFAULT: int
|
||||
EVENT_DEFAULT: int
|
||||
Event_BLOCKING_SYNC: int
|
||||
EVENT_BLOCKING_SYNC: int
|
||||
Event_DISABLE_TIMING: int
|
||||
EVENT_DISABLE_TIMING: int
|
||||
Event_INTERPROCESS: int
|
||||
EVENT_INTERPROCESS: int
|
||||
Event_CreateFlags = int
|
||||
"""One of [Event_DEFAULT, EVENT_DEFAULT, Event_BLOCKING_SYNC, EVENT_BLOCKING_SYNC, Event_DISABLE_TIMING, EVENT_DISABLE_TIMING, Event_INTERPROCESS, EVENT_INTERPROCESS]"""
|
||||
|
||||
DeviceInfo_ComputeModeDefault: int
|
||||
DEVICE_INFO_COMPUTE_MODE_DEFAULT: int
|
||||
DeviceInfo_ComputeModeExclusive: int
|
||||
DEVICE_INFO_COMPUTE_MODE_EXCLUSIVE: int
|
||||
DeviceInfo_ComputeModeProhibited: int
|
||||
DEVICE_INFO_COMPUTE_MODE_PROHIBITED: int
|
||||
DeviceInfo_ComputeModeExclusiveProcess: int
|
||||
DEVICE_INFO_COMPUTE_MODE_EXCLUSIVE_PROCESS: int
|
||||
DeviceInfo_ComputeMode = int
|
||||
"""One of [DeviceInfo_ComputeModeDefault, DEVICE_INFO_COMPUTE_MODE_DEFAULT, DeviceInfo_ComputeModeExclusive, DEVICE_INFO_COMPUTE_MODE_EXCLUSIVE, DeviceInfo_ComputeModeProhibited, DEVICE_INFO_COMPUTE_MODE_PROHIBITED, DeviceInfo_ComputeModeExclusiveProcess, DEVICE_INFO_COMPUTE_MODE_EXCLUSIVE_PROCESS]"""
|
||||
|
||||
|
||||
# Classes
|
||||
class GpuMat:
|
||||
@property
|
||||
def step(self) -> int: ...
|
||||
|
||||
# Classes
|
||||
class Allocator:
|
||||
...
|
||||
|
||||
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, allocator: GpuMat.Allocator = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, rows: int, cols: int, type: int, allocator: GpuMat.Allocator = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, size: cv2.typing.Size, type: int, allocator: GpuMat.Allocator = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, rows: int, cols: int, type: int, s: cv2.typing.Scalar, allocator: GpuMat.Allocator = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, size: cv2.typing.Size, type: int, s: cv2.typing.Scalar, allocator: GpuMat.Allocator = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, m: GpuMat) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, m: GpuMat, rowRange: cv2.typing.Range, colRange: cv2.typing.Range) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, m: GpuMat, roi: cv2.typing.Rect) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, arr: cv2.typing.MatLike, allocator: GpuMat.Allocator = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, arr: GpuMat, allocator: GpuMat.Allocator = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, arr: cv2.UMat, allocator: GpuMat.Allocator = ...) -> None: ...
|
||||
|
||||
@staticmethod
|
||||
def defaultAllocator() -> GpuMat.Allocator: ...
|
||||
|
||||
@staticmethod
|
||||
def setDefaultAllocator(allocator: GpuMat.Allocator) -> None: ...
|
||||
|
||||
@staticmethod
|
||||
def getStdAllocator() -> GpuMat.Allocator: ...
|
||||
|
||||
@_typing.overload
|
||||
def create(self, rows: int, cols: int, type: int) -> None: ...
|
||||
@_typing.overload
|
||||
def create(self, size: cv2.typing.Size, type: int) -> None: ...
|
||||
|
||||
def release(self) -> None: ...
|
||||
|
||||
def swap(self, mat: GpuMat) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def upload(self, arr: cv2.typing.MatLike) -> None: ...
|
||||
@_typing.overload
|
||||
def upload(self, arr: GpuMat) -> None: ...
|
||||
@_typing.overload
|
||||
def upload(self, arr: cv2.UMat) -> None: ...
|
||||
@_typing.overload
|
||||
def upload(self, arr: cv2.typing.MatLike, stream: Stream) -> None: ...
|
||||
@_typing.overload
|
||||
def upload(self, arr: GpuMat, stream: Stream) -> None: ...
|
||||
@_typing.overload
|
||||
def upload(self, arr: cv2.UMat, stream: Stream) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def download(self, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def download(self, dst: GpuMat | None = ...) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def download(self, dst: cv2.UMat | None = ...) -> cv2.UMat: ...
|
||||
@_typing.overload
|
||||
def download(self, stream: Stream, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def download(self, stream: Stream, dst: GpuMat | None = ...) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def download(self, stream: Stream, dst: cv2.UMat | None = ...) -> cv2.UMat: ...
|
||||
|
||||
def clone(self) -> GpuMat: ...
|
||||
|
||||
@_typing.overload
|
||||
def copyTo(self, dst: GpuMat | None = ...) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def copyTo(self, stream: Stream, dst: GpuMat | None = ...) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def copyTo(self, mask: GpuMat, dst: GpuMat | None = ...) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def copyTo(self, mask: GpuMat, stream: Stream, dst: GpuMat | None = ...) -> GpuMat: ...
|
||||
|
||||
@_typing.overload
|
||||
def setTo(self, s: cv2.typing.Scalar) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def setTo(self, s: cv2.typing.Scalar, stream: Stream) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def setTo(self, s: cv2.typing.Scalar, mask: cv2.typing.MatLike) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def setTo(self, s: cv2.typing.Scalar, mask: GpuMat) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def setTo(self, s: cv2.typing.Scalar, mask: cv2.UMat) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def setTo(self, s: cv2.typing.Scalar, mask: cv2.typing.MatLike, stream: Stream) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def setTo(self, s: cv2.typing.Scalar, mask: GpuMat, stream: Stream) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def setTo(self, s: cv2.typing.Scalar, mask: cv2.UMat, stream: Stream) -> GpuMat: ...
|
||||
|
||||
@_typing.overload
|
||||
def convertTo(self, rtype: int, dst: GpuMat | None = ...) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def convertTo(self, rtype: int, stream: Stream, dst: GpuMat | None = ...) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def convertTo(self, rtype: int, dst: GpuMat | None = ..., alpha: float = ..., beta: float = ...) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def convertTo(self, rtype: int, alpha: float, beta: float, stream: Stream, dst: GpuMat | None = ...) -> GpuMat: ...
|
||||
|
||||
def assignTo(self, m: GpuMat, type: int = ...) -> None: ...
|
||||
|
||||
def row(self, y: int) -> GpuMat: ...
|
||||
|
||||
def col(self, x: int) -> GpuMat: ...
|
||||
|
||||
@_typing.overload
|
||||
def rowRange(self, startrow: int, endrow: int) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def rowRange(self, r: cv2.typing.Range) -> GpuMat: ...
|
||||
|
||||
@_typing.overload
|
||||
def colRange(self, startcol: int, endcol: int) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def colRange(self, r: cv2.typing.Range) -> GpuMat: ...
|
||||
|
||||
def reshape(self, cn: int, rows: int = ...) -> GpuMat: ...
|
||||
|
||||
def locateROI(self, wholeSize: cv2.typing.Size, ofs: cv2.typing.Point) -> None: ...
|
||||
|
||||
def adjustROI(self, dtop: int, dbottom: int, dleft: int, dright: int) -> GpuMat: ...
|
||||
|
||||
def isContinuous(self) -> bool: ...
|
||||
|
||||
def elemSize(self) -> int: ...
|
||||
|
||||
def elemSize1(self) -> int: ...
|
||||
|
||||
def type(self) -> int: ...
|
||||
|
||||
def depth(self) -> int: ...
|
||||
|
||||
def channels(self) -> int: ...
|
||||
|
||||
def step1(self) -> int: ...
|
||||
|
||||
def size(self) -> cv2.typing.Size: ...
|
||||
|
||||
def empty(self) -> bool: ...
|
||||
|
||||
def cudaPtr(self) -> cv2.typing.IntPointer: ...
|
||||
|
||||
def updateContinuityFlag(self) -> None: ...
|
||||
|
||||
|
||||
class GpuData:
|
||||
...
|
||||
|
||||
class GpuMatND:
|
||||
...
|
||||
|
||||
class BufferPool:
|
||||
# Functions
|
||||
def __init__(self, stream: Stream) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def getBuffer(self, rows: int, cols: int, type: int) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def getBuffer(self, size: cv2.typing.Size, type: int) -> GpuMat: ...
|
||||
|
||||
def getAllocator(self) -> GpuMat.Allocator: ...
|
||||
|
||||
|
||||
class HostMem:
|
||||
@property
|
||||
def step(self) -> int: ...
|
||||
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, alloc_type: HostMem_AllocType = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, rows: int, cols: int, type: int, alloc_type: HostMem_AllocType = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, size: cv2.typing.Size, type: int, alloc_type: HostMem_AllocType = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, arr: cv2.typing.MatLike, alloc_type: HostMem_AllocType = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, arr: GpuMat, alloc_type: HostMem_AllocType = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, arr: cv2.UMat, alloc_type: HostMem_AllocType = ...) -> None: ...
|
||||
|
||||
def swap(self, b: HostMem) -> None: ...
|
||||
|
||||
def clone(self) -> HostMem: ...
|
||||
|
||||
def create(self, rows: int, cols: int, type: int) -> None: ...
|
||||
|
||||
def reshape(self, cn: int, rows: int = ...) -> HostMem: ...
|
||||
|
||||
def createMatHeader(self) -> cv2.typing.MatLike: ...
|
||||
|
||||
def isContinuous(self) -> bool: ...
|
||||
|
||||
def elemSize(self) -> int: ...
|
||||
|
||||
def elemSize1(self) -> int: ...
|
||||
|
||||
def type(self) -> int: ...
|
||||
|
||||
def depth(self) -> int: ...
|
||||
|
||||
def channels(self) -> int: ...
|
||||
|
||||
def step1(self) -> int: ...
|
||||
|
||||
def size(self) -> cv2.typing.Size: ...
|
||||
|
||||
def empty(self) -> bool: ...
|
||||
|
||||
|
||||
class Stream:
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, allocator: GpuMat.Allocator) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, cudaFlags: int) -> None: ...
|
||||
|
||||
def queryIfComplete(self) -> bool: ...
|
||||
|
||||
def waitForCompletion(self) -> None: ...
|
||||
|
||||
def waitEvent(self, event: Event) -> None: ...
|
||||
|
||||
@classmethod
|
||||
def Null(cls) -> Stream: ...
|
||||
|
||||
def cudaPtr(self) -> cv2.typing.IntPointer: ...
|
||||
|
||||
|
||||
class Event:
|
||||
# Functions
|
||||
def __init__(self, flags: Event_CreateFlags = ...) -> None: ...
|
||||
|
||||
def record(self, stream: Stream = ...) -> None: ...
|
||||
|
||||
def queryIfComplete(self) -> bool: ...
|
||||
|
||||
def waitForCompletion(self) -> None: ...
|
||||
|
||||
@staticmethod
|
||||
def elapsedTime(start: Event, end: Event) -> float: ...
|
||||
|
||||
|
||||
class TargetArchs:
|
||||
# Functions
|
||||
@staticmethod
|
||||
def has(major: int, minor: int) -> bool: ...
|
||||
|
||||
@staticmethod
|
||||
def hasPtx(major: int, minor: int) -> bool: ...
|
||||
|
||||
@staticmethod
|
||||
def hasBin(major: int, minor: int) -> bool: ...
|
||||
|
||||
@staticmethod
|
||||
def hasEqualOrLessPtx(major: int, minor: int) -> bool: ...
|
||||
|
||||
@staticmethod
|
||||
def hasEqualOrGreater(major: int, minor: int) -> bool: ...
|
||||
|
||||
@staticmethod
|
||||
def hasEqualOrGreaterPtx(major: int, minor: int) -> bool: ...
|
||||
|
||||
@staticmethod
|
||||
def hasEqualOrGreaterBin(major: int, minor: int) -> bool: ...
|
||||
|
||||
|
||||
class DeviceInfo:
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, device_id: int) -> None: ...
|
||||
|
||||
def deviceID(self) -> int: ...
|
||||
|
||||
def totalGlobalMem(self) -> int: ...
|
||||
|
||||
def sharedMemPerBlock(self) -> int: ...
|
||||
|
||||
def regsPerBlock(self) -> int: ...
|
||||
|
||||
def warpSize(self) -> int: ...
|
||||
|
||||
def memPitch(self) -> int: ...
|
||||
|
||||
def maxThreadsPerBlock(self) -> int: ...
|
||||
|
||||
def maxThreadsDim(self) -> cv2.typing.Vec3i: ...
|
||||
|
||||
def maxGridSize(self) -> cv2.typing.Vec3i: ...
|
||||
|
||||
def clockRate(self) -> int: ...
|
||||
|
||||
def totalConstMem(self) -> int: ...
|
||||
|
||||
def majorVersion(self) -> int: ...
|
||||
|
||||
def minorVersion(self) -> int: ...
|
||||
|
||||
def textureAlignment(self) -> int: ...
|
||||
|
||||
def texturePitchAlignment(self) -> int: ...
|
||||
|
||||
def multiProcessorCount(self) -> int: ...
|
||||
|
||||
def kernelExecTimeoutEnabled(self) -> bool: ...
|
||||
|
||||
def integrated(self) -> bool: ...
|
||||
|
||||
def canMapHostMemory(self) -> bool: ...
|
||||
|
||||
def computeMode(self) -> DeviceInfo_ComputeMode: ...
|
||||
|
||||
def maxTexture1D(self) -> int: ...
|
||||
|
||||
def maxTexture1DMipmap(self) -> int: ...
|
||||
|
||||
def maxTexture1DLinear(self) -> int: ...
|
||||
|
||||
def maxTexture2D(self) -> cv2.typing.Vec2i: ...
|
||||
|
||||
def maxTexture2DMipmap(self) -> cv2.typing.Vec2i: ...
|
||||
|
||||
def maxTexture2DLinear(self) -> cv2.typing.Vec3i: ...
|
||||
|
||||
def maxTexture2DGather(self) -> cv2.typing.Vec2i: ...
|
||||
|
||||
def maxTexture3D(self) -> cv2.typing.Vec3i: ...
|
||||
|
||||
def maxTextureCubemap(self) -> int: ...
|
||||
|
||||
def maxTexture1DLayered(self) -> cv2.typing.Vec2i: ...
|
||||
|
||||
def maxTexture2DLayered(self) -> cv2.typing.Vec3i: ...
|
||||
|
||||
def maxTextureCubemapLayered(self) -> cv2.typing.Vec2i: ...
|
||||
|
||||
def maxSurface1D(self) -> int: ...
|
||||
|
||||
def maxSurface2D(self) -> cv2.typing.Vec2i: ...
|
||||
|
||||
def maxSurface3D(self) -> cv2.typing.Vec3i: ...
|
||||
|
||||
def maxSurface1DLayered(self) -> cv2.typing.Vec2i: ...
|
||||
|
||||
def maxSurface2DLayered(self) -> cv2.typing.Vec3i: ...
|
||||
|
||||
def maxSurfaceCubemap(self) -> int: ...
|
||||
|
||||
def maxSurfaceCubemapLayered(self) -> cv2.typing.Vec2i: ...
|
||||
|
||||
def surfaceAlignment(self) -> int: ...
|
||||
|
||||
def concurrentKernels(self) -> bool: ...
|
||||
|
||||
def ECCEnabled(self) -> bool: ...
|
||||
|
||||
def pciBusID(self) -> int: ...
|
||||
|
||||
def pciDeviceID(self) -> int: ...
|
||||
|
||||
def pciDomainID(self) -> int: ...
|
||||
|
||||
def tccDriver(self) -> bool: ...
|
||||
|
||||
def asyncEngineCount(self) -> int: ...
|
||||
|
||||
def unifiedAddressing(self) -> bool: ...
|
||||
|
||||
def memoryClockRate(self) -> int: ...
|
||||
|
||||
def memoryBusWidth(self) -> int: ...
|
||||
|
||||
def l2CacheSize(self) -> int: ...
|
||||
|
||||
def maxThreadsPerMultiProcessor(self) -> int: ...
|
||||
|
||||
def queryMemory(self, totalMemory: int, freeMemory: int) -> None: ...
|
||||
|
||||
def freeMemory(self) -> int: ...
|
||||
|
||||
def totalMemory(self) -> int: ...
|
||||
|
||||
def isCompatible(self) -> bool: ...
|
||||
|
||||
|
||||
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def createContinuous(rows: int, cols: int, type: int, arr: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def createContinuous(rows: int, cols: int, type: int, arr: GpuMat | None = ...) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def createContinuous(rows: int, cols: int, type: int, arr: cv2.UMat | None = ...) -> cv2.UMat: ...
|
||||
|
||||
@_typing.overload
|
||||
def createGpuMatFromCudaMemory(rows: int, cols: int, type: int, cudaMemoryAddress: int, step: int = ...) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def createGpuMatFromCudaMemory(size: cv2.typing.Size, type: int, cudaMemoryAddress: int, step: int = ...) -> GpuMat: ...
|
||||
|
||||
@_typing.overload
|
||||
def ensureSizeIsEnough(rows: int, cols: int, type: int, arr: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def ensureSizeIsEnough(rows: int, cols: int, type: int, arr: GpuMat | None = ...) -> GpuMat: ...
|
||||
@_typing.overload
|
||||
def ensureSizeIsEnough(rows: int, cols: int, type: int, arr: cv2.UMat | None = ...) -> cv2.UMat: ...
|
||||
|
||||
def fastNlMeansDenoising(src: GpuMat, h: float, dst: GpuMat | None = ..., search_window: int = ..., block_size: int = ..., stream: Stream = ...) -> GpuMat: ...
|
||||
|
||||
def fastNlMeansDenoisingColored(src: GpuMat, h_luminance: float, photo_render: float, dst: GpuMat | None = ..., search_window: int = ..., block_size: int = ..., stream: Stream = ...) -> GpuMat: ...
|
||||
|
||||
def getCudaEnabledDeviceCount() -> int: ...
|
||||
|
||||
def getDevice() -> int: ...
|
||||
|
||||
def nonLocalMeans(src: GpuMat, h: float, dst: GpuMat | None = ..., search_window: int = ..., block_size: int = ..., borderMode: int = ..., stream: Stream = ...) -> GpuMat: ...
|
||||
|
||||
def printCudaDeviceInfo(device: int) -> None: ...
|
||||
|
||||
def printShortCudaDeviceInfo(device: int) -> None: ...
|
||||
|
||||
def registerPageLocked(m: cv2.typing.MatLike) -> None: ...
|
||||
|
||||
def resetDevice() -> None: ...
|
||||
|
||||
def setBufferPoolConfig(deviceId: int, stackSize: int, stackCount: int) -> None: ...
|
||||
|
||||
def setBufferPoolUsage(on: bool) -> None: ...
|
||||
|
||||
def setDevice(device: int) -> None: ...
|
||||
|
||||
def unregisterPageLocked(m: cv2.typing.MatLike) -> None: ...
|
||||
|
||||
def wrapStream(cudaStreamMemoryAddress: int) -> Stream: ...
|
||||
|
||||
|
||||
BIN
Binary file not shown.
@@ -0,0 +1,3 @@
|
||||
import os
|
||||
|
||||
haarcascades = os.path.join(os.path.dirname(__file__), "")
|
||||
BIN
Binary file not shown.
+543
@@ -0,0 +1,543 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
import cv2
|
||||
import cv2.typing
|
||||
import numpy
|
||||
import typing as _typing
|
||||
|
||||
|
||||
# Enumerations
|
||||
TEST_CUSTOM: int
|
||||
TEST_EQ: int
|
||||
TEST_NE: int
|
||||
TEST_LE: int
|
||||
TEST_LT: int
|
||||
TEST_GE: int
|
||||
TEST_GT: int
|
||||
TestOp = int
|
||||
"""One of [TEST_CUSTOM, TEST_EQ, TEST_NE, TEST_LE, TEST_LT, TEST_GE, TEST_GT]"""
|
||||
|
||||
WAVE_CORRECT_HORIZ: int
|
||||
WAVE_CORRECT_VERT: int
|
||||
WAVE_CORRECT_AUTO: int
|
||||
WaveCorrectKind = int
|
||||
"""One of [WAVE_CORRECT_HORIZ, WAVE_CORRECT_VERT, WAVE_CORRECT_AUTO]"""
|
||||
|
||||
|
||||
Blender_NO: int
|
||||
BLENDER_NO: int
|
||||
Blender_FEATHER: int
|
||||
BLENDER_FEATHER: int
|
||||
Blender_MULTI_BAND: int
|
||||
BLENDER_MULTI_BAND: int
|
||||
|
||||
ExposureCompensator_NO: int
|
||||
EXPOSURE_COMPENSATOR_NO: int
|
||||
ExposureCompensator_GAIN: int
|
||||
EXPOSURE_COMPENSATOR_GAIN: int
|
||||
ExposureCompensator_GAIN_BLOCKS: int
|
||||
EXPOSURE_COMPENSATOR_GAIN_BLOCKS: int
|
||||
ExposureCompensator_CHANNELS: int
|
||||
EXPOSURE_COMPENSATOR_CHANNELS: int
|
||||
ExposureCompensator_CHANNELS_BLOCKS: int
|
||||
EXPOSURE_COMPENSATOR_CHANNELS_BLOCKS: int
|
||||
|
||||
SeamFinder_NO: int
|
||||
SEAM_FINDER_NO: int
|
||||
SeamFinder_VORONOI_SEAM: int
|
||||
SEAM_FINDER_VORONOI_SEAM: int
|
||||
SeamFinder_DP_SEAM: int
|
||||
SEAM_FINDER_DP_SEAM: int
|
||||
|
||||
DpSeamFinder_COLOR: int
|
||||
DP_SEAM_FINDER_COLOR: int
|
||||
DpSeamFinder_COLOR_GRAD: int
|
||||
DP_SEAM_FINDER_COLOR_GRAD: int
|
||||
DpSeamFinder_CostFunction = int
|
||||
"""One of [DpSeamFinder_COLOR, DP_SEAM_FINDER_COLOR, DpSeamFinder_COLOR_GRAD, DP_SEAM_FINDER_COLOR_GRAD]"""
|
||||
|
||||
Timelapser_AS_IS: int
|
||||
TIMELAPSER_AS_IS: int
|
||||
Timelapser_CROP: int
|
||||
TIMELAPSER_CROP: int
|
||||
|
||||
GraphCutSeamFinderBase_COST_COLOR: int
|
||||
GRAPH_CUT_SEAM_FINDER_BASE_COST_COLOR: int
|
||||
GraphCutSeamFinderBase_COST_COLOR_GRAD: int
|
||||
GRAPH_CUT_SEAM_FINDER_BASE_COST_COLOR_GRAD: int
|
||||
GraphCutSeamFinderBase_CostType = int
|
||||
"""One of [GraphCutSeamFinderBase_COST_COLOR, GRAPH_CUT_SEAM_FINDER_BASE_COST_COLOR, GraphCutSeamFinderBase_COST_COLOR_GRAD, GRAPH_CUT_SEAM_FINDER_BASE_COST_COLOR_GRAD]"""
|
||||
|
||||
TrackerSamplerCSC_MODE_INIT_POS: int
|
||||
TRACKER_SAMPLER_CSC_MODE_INIT_POS: int
|
||||
TrackerSamplerCSC_MODE_INIT_NEG: int
|
||||
TRACKER_SAMPLER_CSC_MODE_INIT_NEG: int
|
||||
TrackerSamplerCSC_MODE_TRACK_POS: int
|
||||
TRACKER_SAMPLER_CSC_MODE_TRACK_POS: int
|
||||
TrackerSamplerCSC_MODE_TRACK_NEG: int
|
||||
TRACKER_SAMPLER_CSC_MODE_TRACK_NEG: int
|
||||
TrackerSamplerCSC_MODE_DETECT: int
|
||||
TRACKER_SAMPLER_CSC_MODE_DETECT: int
|
||||
TrackerSamplerCSC_MODE = int
|
||||
"""One of [TrackerSamplerCSC_MODE_INIT_POS, TRACKER_SAMPLER_CSC_MODE_INIT_POS, TrackerSamplerCSC_MODE_INIT_NEG, TRACKER_SAMPLER_CSC_MODE_INIT_NEG, TrackerSamplerCSC_MODE_TRACK_POS, TRACKER_SAMPLER_CSC_MODE_TRACK_POS, TrackerSamplerCSC_MODE_TRACK_NEG, TRACKER_SAMPLER_CSC_MODE_TRACK_NEG, TrackerSamplerCSC_MODE_DETECT, TRACKER_SAMPLER_CSC_MODE_DETECT]"""
|
||||
|
||||
|
||||
# Classes
|
||||
class PoseGraph:
|
||||
...
|
||||
|
||||
class Blender:
|
||||
# Functions
|
||||
@classmethod
|
||||
def createDefault(cls, type: int, try_gpu: bool = ...) -> Blender: ...
|
||||
|
||||
@_typing.overload
|
||||
def prepare(self, corners: _typing.Sequence[cv2.typing.Point], sizes: _typing.Sequence[cv2.typing.Size]) -> None: ...
|
||||
@_typing.overload
|
||||
def prepare(self, dst_roi: cv2.typing.Rect) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def feed(self, img: cv2.typing.MatLike, mask: cv2.typing.MatLike, tl: cv2.typing.Point) -> None: ...
|
||||
@_typing.overload
|
||||
def feed(self, img: cv2.UMat, mask: cv2.UMat, tl: cv2.typing.Point) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def blend(self, dst: cv2.typing.MatLike, dst_mask: cv2.typing.MatLike) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def blend(self, dst: cv2.UMat, dst_mask: cv2.UMat) -> tuple[cv2.UMat, cv2.UMat]: ...
|
||||
|
||||
|
||||
class FeatherBlender(Blender):
|
||||
# Functions
|
||||
def __init__(self, sharpness: float = ...) -> None: ...
|
||||
|
||||
def sharpness(self) -> float: ...
|
||||
|
||||
def setSharpness(self, val: float) -> None: ...
|
||||
|
||||
def prepare(self, dst_roi: cv2.typing.Rect) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def feed(self, img: cv2.typing.MatLike, mask: cv2.typing.MatLike, tl: cv2.typing.Point) -> None: ...
|
||||
@_typing.overload
|
||||
def feed(self, img: cv2.UMat, mask: cv2.UMat, tl: cv2.typing.Point) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def blend(self, dst: cv2.typing.MatLike, dst_mask: cv2.typing.MatLike) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def blend(self, dst: cv2.UMat, dst_mask: cv2.UMat) -> tuple[cv2.UMat, cv2.UMat]: ...
|
||||
|
||||
def createWeightMaps(self, masks: _typing.Sequence[cv2.UMat], corners: _typing.Sequence[cv2.typing.Point], weight_maps: _typing.Sequence[cv2.UMat]) -> tuple[cv2.typing.Rect, _typing.Sequence[cv2.UMat]]: ...
|
||||
|
||||
|
||||
class MultiBandBlender(Blender):
|
||||
# Functions
|
||||
def __init__(self, try_gpu: int = ..., num_bands: int = ..., weight_type: int = ...) -> None: ...
|
||||
|
||||
def numBands(self) -> int: ...
|
||||
|
||||
def setNumBands(self, val: int) -> None: ...
|
||||
|
||||
def prepare(self, dst_roi: cv2.typing.Rect) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def feed(self, img: cv2.typing.MatLike, mask: cv2.typing.MatLike, tl: cv2.typing.Point) -> None: ...
|
||||
@_typing.overload
|
||||
def feed(self, img: cv2.UMat, mask: cv2.UMat, tl: cv2.typing.Point) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def blend(self, dst: cv2.typing.MatLike, dst_mask: cv2.typing.MatLike) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def blend(self, dst: cv2.UMat, dst_mask: cv2.UMat) -> tuple[cv2.UMat, cv2.UMat]: ...
|
||||
|
||||
|
||||
class CameraParams:
|
||||
focal: float
|
||||
aspect: float
|
||||
ppx: float
|
||||
ppy: float
|
||||
R: cv2.typing.MatLike
|
||||
t: cv2.typing.MatLike
|
||||
|
||||
# Functions
|
||||
def K(self) -> cv2.typing.MatLike: ...
|
||||
|
||||
|
||||
class ExposureCompensator:
|
||||
# Functions
|
||||
@classmethod
|
||||
def createDefault(cls, type: int) -> ExposureCompensator: ...
|
||||
|
||||
def feed(self, corners: _typing.Sequence[cv2.typing.Point], images: _typing.Sequence[cv2.UMat], masks: _typing.Sequence[cv2.UMat]) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def apply(self, index: int, corner: cv2.typing.Point, image: cv2.typing.MatLike, mask: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def apply(self, index: int, corner: cv2.typing.Point, image: cv2.UMat, mask: cv2.UMat) -> cv2.UMat: ...
|
||||
|
||||
def getMatGains(self, arg1: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
||||
|
||||
def setMatGains(self, arg1: _typing.Sequence[cv2.typing.MatLike]) -> None: ...
|
||||
|
||||
def setUpdateGain(self, b: bool) -> None: ...
|
||||
|
||||
def getUpdateGain(self) -> bool: ...
|
||||
|
||||
|
||||
class NoExposureCompensator(ExposureCompensator):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def apply(self, arg1: int, arg2: cv2.typing.Point, arg3: cv2.typing.MatLike, arg4: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def apply(self, arg1: int, arg2: cv2.typing.Point, arg3: cv2.UMat, arg4: cv2.UMat) -> cv2.UMat: ...
|
||||
|
||||
def getMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
||||
|
||||
def setMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike]) -> None: ...
|
||||
|
||||
|
||||
class GainCompensator(ExposureCompensator):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, nr_feeds: int) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def apply(self, index: int, corner: cv2.typing.Point, image: cv2.typing.MatLike, mask: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def apply(self, index: int, corner: cv2.typing.Point, image: cv2.UMat, mask: cv2.UMat) -> cv2.UMat: ...
|
||||
|
||||
def getMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
||||
|
||||
def setMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike]) -> None: ...
|
||||
|
||||
def setNrFeeds(self, nr_feeds: int) -> None: ...
|
||||
|
||||
def getNrFeeds(self) -> int: ...
|
||||
|
||||
def setSimilarityThreshold(self, similarity_threshold: float) -> None: ...
|
||||
|
||||
def getSimilarityThreshold(self) -> float: ...
|
||||
|
||||
|
||||
class ChannelsCompensator(ExposureCompensator):
|
||||
# Functions
|
||||
def __init__(self, nr_feeds: int = ...) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def apply(self, index: int, corner: cv2.typing.Point, image: cv2.typing.MatLike, mask: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def apply(self, index: int, corner: cv2.typing.Point, image: cv2.UMat, mask: cv2.UMat) -> cv2.UMat: ...
|
||||
|
||||
def getMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
||||
|
||||
def setMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike]) -> None: ...
|
||||
|
||||
def setNrFeeds(self, nr_feeds: int) -> None: ...
|
||||
|
||||
def getNrFeeds(self) -> int: ...
|
||||
|
||||
def setSimilarityThreshold(self, similarity_threshold: float) -> None: ...
|
||||
|
||||
def getSimilarityThreshold(self) -> float: ...
|
||||
|
||||
|
||||
class BlocksCompensator(ExposureCompensator):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def apply(self, index: int, corner: cv2.typing.Point, image: cv2.typing.MatLike, mask: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def apply(self, index: int, corner: cv2.typing.Point, image: cv2.UMat, mask: cv2.UMat) -> cv2.UMat: ...
|
||||
|
||||
def getMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
||||
|
||||
def setMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike]) -> None: ...
|
||||
|
||||
def setNrFeeds(self, nr_feeds: int) -> None: ...
|
||||
|
||||
def getNrFeeds(self) -> int: ...
|
||||
|
||||
def setSimilarityThreshold(self, similarity_threshold: float) -> None: ...
|
||||
|
||||
def getSimilarityThreshold(self) -> float: ...
|
||||
|
||||
@_typing.overload
|
||||
def setBlockSize(self, width: int, height: int) -> None: ...
|
||||
@_typing.overload
|
||||
def setBlockSize(self, size: cv2.typing.Size) -> None: ...
|
||||
|
||||
def getBlockSize(self) -> cv2.typing.Size: ...
|
||||
|
||||
def setNrGainsFilteringIterations(self, nr_iterations: int) -> None: ...
|
||||
|
||||
def getNrGainsFilteringIterations(self) -> int: ...
|
||||
|
||||
|
||||
class BlocksGainCompensator(BlocksCompensator):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, bl_width: int = ..., bl_height: int = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, bl_width: int, bl_height: int, nr_feeds: int) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def apply(self, index: int, corner: cv2.typing.Point, image: cv2.typing.MatLike, mask: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def apply(self, index: int, corner: cv2.typing.Point, image: cv2.UMat, mask: cv2.UMat) -> cv2.UMat: ...
|
||||
|
||||
def getMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
||||
|
||||
def setMatGains(self, umv: _typing.Sequence[cv2.typing.MatLike]) -> None: ...
|
||||
|
||||
|
||||
class BlocksChannelsCompensator(BlocksCompensator):
|
||||
# Functions
|
||||
def __init__(self, bl_width: int = ..., bl_height: int = ..., nr_feeds: int = ...) -> None: ...
|
||||
|
||||
|
||||
class ImageFeatures:
|
||||
img_idx: int
|
||||
img_size: cv2.typing.Size
|
||||
keypoints: _typing.Sequence[cv2.KeyPoint]
|
||||
descriptors: cv2.UMat
|
||||
|
||||
# Functions
|
||||
def getKeypoints(self) -> _typing.Sequence[cv2.KeyPoint]: ...
|
||||
|
||||
|
||||
class MatchesInfo:
|
||||
src_img_idx: int
|
||||
dst_img_idx: int
|
||||
matches: _typing.Sequence[cv2.DMatch]
|
||||
inliers_mask: numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]]
|
||||
num_inliers: int
|
||||
H: cv2.typing.MatLike
|
||||
confidence: float
|
||||
|
||||
# Functions
|
||||
def getMatches(self) -> _typing.Sequence[cv2.DMatch]: ...
|
||||
|
||||
def getInliers(self) -> numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]]: ...
|
||||
|
||||
|
||||
class FeaturesMatcher:
|
||||
# Functions
|
||||
def apply(self, features1: ImageFeatures, features2: ImageFeatures) -> MatchesInfo: ...
|
||||
|
||||
def apply2(self, features: _typing.Sequence[ImageFeatures], mask: cv2.UMat | None = ...) -> _typing.Sequence[MatchesInfo]: ...
|
||||
|
||||
def isThreadSafe(self) -> bool: ...
|
||||
|
||||
def collectGarbage(self) -> None: ...
|
||||
|
||||
|
||||
class BestOf2NearestMatcher(FeaturesMatcher):
|
||||
# Functions
|
||||
def __init__(self, try_use_gpu: bool = ..., match_conf: float = ..., num_matches_thresh1: int = ..., num_matches_thresh2: int = ..., matches_confidence_thresh: float = ...) -> None: ...
|
||||
|
||||
def collectGarbage(self) -> None: ...
|
||||
|
||||
@classmethod
|
||||
def create(cls, try_use_gpu: bool = ..., match_conf: float = ..., num_matches_thresh1: int = ..., num_matches_thresh2: int = ..., matches_confidence_thresh: float = ...) -> BestOf2NearestMatcher: ...
|
||||
|
||||
|
||||
class BestOf2NearestRangeMatcher(BestOf2NearestMatcher):
|
||||
# Functions
|
||||
def __init__(self, range_width: int = ..., try_use_gpu: bool = ..., match_conf: float = ..., num_matches_thresh1: int = ..., num_matches_thresh2: int = ...) -> None: ...
|
||||
|
||||
|
||||
class AffineBestOf2NearestMatcher(BestOf2NearestMatcher):
|
||||
# Functions
|
||||
def __init__(self, full_affine: bool = ..., try_use_gpu: bool = ..., match_conf: float = ..., num_matches_thresh1: int = ...) -> None: ...
|
||||
|
||||
|
||||
class LightGlueFeaturesMatcher(FeaturesMatcher):
|
||||
# Functions
|
||||
def __init__(self, lgMatcher: cv2.LightGlueMatcher, num_matches_thresh1: int = ..., num_matches_thresh2: int = ..., matches_confidence_thresh: float = ...) -> None: ...
|
||||
|
||||
def setScoreThreshold(self, thresh: float) -> None: ...
|
||||
|
||||
|
||||
class Estimator:
|
||||
# Functions
|
||||
def apply(self, features: _typing.Sequence[ImageFeatures], pairwise_matches: _typing.Sequence[MatchesInfo], cameras: _typing.Sequence[CameraParams]) -> tuple[bool, _typing.Sequence[CameraParams]]: ...
|
||||
|
||||
|
||||
class HomographyBasedEstimator(Estimator):
|
||||
# Functions
|
||||
def __init__(self, is_focals_estimated: bool = ...) -> None: ...
|
||||
|
||||
|
||||
class AffineBasedEstimator(Estimator):
|
||||
# Functions
|
||||
def __init__(self) -> None: ...
|
||||
|
||||
|
||||
class BundleAdjusterBase(Estimator):
|
||||
# Functions
|
||||
def refinementMask(self) -> cv2.typing.MatLike: ...
|
||||
|
||||
def setRefinementMask(self, mask: cv2.typing.MatLike) -> None: ...
|
||||
|
||||
def confThresh(self) -> float: ...
|
||||
|
||||
def setConfThresh(self, conf_thresh: float) -> None: ...
|
||||
|
||||
def termCriteria(self) -> cv2.typing.TermCriteria: ...
|
||||
|
||||
def setTermCriteria(self, term_criteria: cv2.typing.TermCriteria) -> None: ...
|
||||
|
||||
|
||||
class NoBundleAdjuster(BundleAdjusterBase):
|
||||
# Functions
|
||||
def __init__(self) -> None: ...
|
||||
|
||||
|
||||
class BundleAdjusterReproj(BundleAdjusterBase):
|
||||
# Functions
|
||||
def __init__(self) -> None: ...
|
||||
|
||||
|
||||
class BundleAdjusterRay(BundleAdjusterBase):
|
||||
# Functions
|
||||
def __init__(self) -> None: ...
|
||||
|
||||
|
||||
class BundleAdjusterAffine(BundleAdjusterBase):
|
||||
# Functions
|
||||
def __init__(self) -> None: ...
|
||||
|
||||
|
||||
class BundleAdjusterAffinePartial(BundleAdjusterBase):
|
||||
# Functions
|
||||
def __init__(self) -> None: ...
|
||||
|
||||
|
||||
class SeamFinder:
|
||||
# Functions
|
||||
def find(self, src: _typing.Sequence[cv2.UMat], corners: _typing.Sequence[cv2.typing.Point], masks: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ...
|
||||
|
||||
@classmethod
|
||||
def createDefault(cls, type: int) -> SeamFinder: ...
|
||||
|
||||
|
||||
class NoSeamFinder(SeamFinder):
|
||||
# Functions
|
||||
def find(self, arg1: _typing.Sequence[cv2.UMat], arg2: _typing.Sequence[cv2.typing.Point], arg3: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ...
|
||||
|
||||
|
||||
class PairwiseSeamFinder(SeamFinder):
|
||||
# Functions
|
||||
def find(self, src: _typing.Sequence[cv2.UMat], corners: _typing.Sequence[cv2.typing.Point], masks: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ...
|
||||
|
||||
|
||||
class VoronoiSeamFinder(PairwiseSeamFinder):
|
||||
# Functions
|
||||
def find(self, src: _typing.Sequence[cv2.UMat], corners: _typing.Sequence[cv2.typing.Point], masks: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ...
|
||||
|
||||
|
||||
class DpSeamFinder(SeamFinder):
|
||||
# Functions
|
||||
def __init__(self, costFunc: str) -> None: ...
|
||||
|
||||
def setCostFunction(self, val: str) -> None: ...
|
||||
|
||||
|
||||
class GraphCutSeamFinder:
|
||||
# Functions
|
||||
def __init__(self, cost_type: str, terminal_cost: float = ..., bad_region_penalty: float = ...) -> None: ...
|
||||
|
||||
def find(self, src: _typing.Sequence[cv2.UMat], corners: _typing.Sequence[cv2.typing.Point], masks: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ...
|
||||
|
||||
|
||||
class Timelapser:
|
||||
# Functions
|
||||
@classmethod
|
||||
def createDefault(cls, type: int) -> Timelapser: ...
|
||||
|
||||
def initialize(self, corners: _typing.Sequence[cv2.typing.Point], sizes: _typing.Sequence[cv2.typing.Size]) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def process(self, img: cv2.typing.MatLike, mask: cv2.typing.MatLike, tl: cv2.typing.Point) -> None: ...
|
||||
@_typing.overload
|
||||
def process(self, img: cv2.UMat, mask: cv2.UMat, tl: cv2.typing.Point) -> None: ...
|
||||
|
||||
def getDst(self) -> cv2.UMat: ...
|
||||
|
||||
|
||||
class TimelapserCrop(Timelapser):
|
||||
...
|
||||
|
||||
class ProjectorBase:
|
||||
...
|
||||
|
||||
class SphericalProjector(ProjectorBase):
|
||||
# Functions
|
||||
def mapForward(self, x: float, y: float, u: float, v: float) -> None: ...
|
||||
|
||||
def mapBackward(self, u: float, v: float, x: float, y: float) -> None: ...
|
||||
|
||||
|
||||
|
||||
# Functions
|
||||
def calibrateRotatingCamera(Hs: _typing.Sequence[cv2.typing.MatLike], K: cv2.typing.MatLike | None = ...) -> tuple[bool, cv2.typing.MatLike]: ...
|
||||
|
||||
@_typing.overload
|
||||
def computeImageFeatures(featuresFinder: cv2.Feature2D, images: _typing.Sequence[cv2.typing.MatLike], masks: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[ImageFeatures]: ...
|
||||
@_typing.overload
|
||||
def computeImageFeatures(featuresFinder: cv2.Feature2D, images: _typing.Sequence[cv2.UMat], masks: _typing.Sequence[cv2.UMat] | None = ...) -> _typing.Sequence[ImageFeatures]: ...
|
||||
|
||||
@_typing.overload
|
||||
def computeImageFeatures2(featuresFinder: cv2.Feature2D, image: cv2.typing.MatLike, mask: cv2.typing.MatLike | None = ...) -> ImageFeatures: ...
|
||||
@_typing.overload
|
||||
def computeImageFeatures2(featuresFinder: cv2.Feature2D, image: cv2.UMat, mask: cv2.UMat | None = ...) -> ImageFeatures: ...
|
||||
|
||||
@_typing.overload
|
||||
def createLaplacePyr(img: cv2.typing.MatLike, num_levels: int, pyr: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ...
|
||||
@_typing.overload
|
||||
def createLaplacePyr(img: cv2.UMat, num_levels: int, pyr: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ...
|
||||
|
||||
@_typing.overload
|
||||
def createLaplacePyrGpu(img: cv2.typing.MatLike, num_levels: int, pyr: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ...
|
||||
@_typing.overload
|
||||
def createLaplacePyrGpu(img: cv2.UMat, num_levels: int, pyr: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ...
|
||||
|
||||
@_typing.overload
|
||||
def createWeightMap(mask: cv2.typing.MatLike, sharpness: float, weight: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def createWeightMap(mask: cv2.UMat, sharpness: float, weight: cv2.UMat) -> cv2.UMat: ...
|
||||
|
||||
def focalsFromHomography(H: cv2.typing.MatLike, f0: float, f1: float, f0_ok: bool, f1_ok: bool) -> None: ...
|
||||
|
||||
def leaveBiggestComponent(features: _typing.Sequence[ImageFeatures], pairwise_matches: _typing.Sequence[MatchesInfo], conf_threshold: float) -> _typing.Sequence[int]: ...
|
||||
|
||||
def matchesGraphAsString(paths: _typing.Sequence[str], pairwise_matches: _typing.Sequence[MatchesInfo], conf_threshold: float) -> str: ...
|
||||
|
||||
@_typing.overload
|
||||
def normalizeUsingWeightMap(weight: cv2.typing.MatLike, src: cv2.typing.MatLike) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def normalizeUsingWeightMap(weight: cv2.UMat, src: cv2.UMat) -> cv2.UMat: ...
|
||||
|
||||
def overlapRoi(tl1: cv2.typing.Point, tl2: cv2.typing.Point, sz1: cv2.typing.Size, sz2: cv2.typing.Size, roi: cv2.typing.Rect) -> bool: ...
|
||||
|
||||
def restoreImageFromLaplacePyr(pyr: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ...
|
||||
|
||||
def restoreImageFromLaplacePyrGpu(pyr: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[cv2.UMat]: ...
|
||||
|
||||
@_typing.overload
|
||||
def resultRoi(corners: _typing.Sequence[cv2.typing.Point], images: _typing.Sequence[cv2.UMat]) -> cv2.typing.Rect: ...
|
||||
@_typing.overload
|
||||
def resultRoi(corners: _typing.Sequence[cv2.typing.Point], sizes: _typing.Sequence[cv2.typing.Size]) -> cv2.typing.Rect: ...
|
||||
|
||||
def resultRoiIntersection(corners: _typing.Sequence[cv2.typing.Point], sizes: _typing.Sequence[cv2.typing.Size]) -> cv2.typing.Rect: ...
|
||||
|
||||
def resultTl(corners: _typing.Sequence[cv2.typing.Point]) -> cv2.typing.Point: ...
|
||||
|
||||
def selectRandomSubset(count: int, size: int, subset: _typing.Sequence[int]) -> None: ...
|
||||
|
||||
def stitchingLogLevel() -> int: ...
|
||||
|
||||
def waveCorrect(rmats: _typing.Sequence[cv2.typing.MatLike], kind: WaveCorrectKind) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
||||
|
||||
|
||||
+666
@@ -0,0 +1,666 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
import cv2
|
||||
import cv2.typing
|
||||
import numpy
|
||||
import os
|
||||
import sys
|
||||
import typing as _typing
|
||||
if sys.version_info >= (3, 8):
|
||||
from typing import Protocol
|
||||
else:
|
||||
from typing_extensions import Protocol
|
||||
|
||||
|
||||
# Enumerations
|
||||
AUTO_PAD_NONE: int
|
||||
AUTO_PAD_SAME_UPPER: int
|
||||
AUTO_PAD_SAME_LOWER: int
|
||||
AUTO_PAD_VALID: int
|
||||
AutoPadding = int
|
||||
"""One of [AUTO_PAD_NONE, AUTO_PAD_SAME_UPPER, AUTO_PAD_SAME_LOWER, AUTO_PAD_VALID]"""
|
||||
|
||||
ACTIV_NONE: int
|
||||
ACTIV_MISH: int
|
||||
ACTIV_SWISH: int
|
||||
ACTIV_SIGMOID: int
|
||||
ACTIV_TANH: int
|
||||
ACTIV_ELU: int
|
||||
ACTIV_HARDSWISH: int
|
||||
ACTIV_HARDSIGMOID: int
|
||||
ACTIV_GELU: int
|
||||
ACTIV_GELU_APPROX: int
|
||||
ACTIV_RELU: int
|
||||
ACTIV_CLIP: int
|
||||
ActivationType = int
|
||||
"""One of [ACTIV_NONE, ACTIV_MISH, ACTIV_SWISH, ACTIV_SIGMOID, ACTIV_TANH, ACTIV_ELU, ACTIV_HARDSWISH, ACTIV_HARDSIGMOID, ACTIV_GELU, ACTIV_GELU_APPROX, ACTIV_RELU, ACTIV_CLIP]"""
|
||||
|
||||
LOSS_REDUCTION_NONE: int
|
||||
LOSS_REDUCTION_MEAN: int
|
||||
LOSS_REDUCTION_SUM: int
|
||||
LossReduction = int
|
||||
"""One of [LOSS_REDUCTION_NONE, LOSS_REDUCTION_MEAN, LOSS_REDUCTION_SUM]"""
|
||||
|
||||
DNN_BACKEND_DEFAULT: int
|
||||
DNN_BACKEND_INFERENCE_ENGINE: int
|
||||
DNN_BACKEND_OPENCV: int
|
||||
DNN_BACKEND_VKCOM: int
|
||||
DNN_BACKEND_CUDA: int
|
||||
DNN_BACKEND_WEBNN: int
|
||||
DNN_BACKEND_TIMVX: int
|
||||
DNN_BACKEND_CANN: int
|
||||
Backend = int
|
||||
"""One of [DNN_BACKEND_DEFAULT, DNN_BACKEND_INFERENCE_ENGINE, DNN_BACKEND_OPENCV, DNN_BACKEND_VKCOM, DNN_BACKEND_CUDA, DNN_BACKEND_WEBNN, DNN_BACKEND_TIMVX, DNN_BACKEND_CANN]"""
|
||||
|
||||
DNN_TARGET_CPU: int
|
||||
DNN_TARGET_OPENCL: int
|
||||
DNN_TARGET_OPENCL_FP16: int
|
||||
DNN_TARGET_MYRIAD: int
|
||||
DNN_TARGET_VULKAN: int
|
||||
DNN_TARGET_FPGA: int
|
||||
DNN_TARGET_CUDA: int
|
||||
DNN_TARGET_CUDA_FP16: int
|
||||
DNN_TARGET_HDDL: int
|
||||
DNN_TARGET_NPU: int
|
||||
DNN_TARGET_CPU_FP16: int
|
||||
Target = int
|
||||
"""One of [DNN_TARGET_CPU, DNN_TARGET_OPENCL, DNN_TARGET_OPENCL_FP16, DNN_TARGET_MYRIAD, DNN_TARGET_VULKAN, DNN_TARGET_FPGA, DNN_TARGET_CUDA, DNN_TARGET_CUDA_FP16, DNN_TARGET_HDDL, DNN_TARGET_NPU, DNN_TARGET_CPU_FP16]"""
|
||||
|
||||
DNN_TRACE_NONE: int
|
||||
DNN_TRACE_ALL: int
|
||||
DNN_TRACE_OP: int
|
||||
TracingMode = int
|
||||
"""One of [DNN_TRACE_NONE, DNN_TRACE_ALL, DNN_TRACE_OP]"""
|
||||
|
||||
DNN_PROFILE_NONE: int
|
||||
DNN_PROFILE_SUMMARY: int
|
||||
DNN_PROFILE_DETAILED: int
|
||||
ProfilingMode = int
|
||||
"""One of [DNN_PROFILE_NONE, DNN_PROFILE_SUMMARY, DNN_PROFILE_DETAILED]"""
|
||||
|
||||
DNN_MODEL_GENERIC: int
|
||||
DNN_MODEL_ONNX: int
|
||||
DNN_MODEL_TF: int
|
||||
DNN_MODEL_TFLITE: int
|
||||
ModelFormat = int
|
||||
"""One of [DNN_MODEL_GENERIC, DNN_MODEL_ONNX, DNN_MODEL_TF, DNN_MODEL_TFLITE]"""
|
||||
|
||||
DNN_ARG_EMPTY: int
|
||||
DNN_ARG_CONST: int
|
||||
DNN_ARG_INPUT: int
|
||||
DNN_ARG_OUTPUT: int
|
||||
DNN_ARG_TEMP: int
|
||||
DNN_ARG_PATTERN: int
|
||||
ArgKind = int
|
||||
"""One of [DNN_ARG_EMPTY, DNN_ARG_CONST, DNN_ARG_INPUT, DNN_ARG_OUTPUT, DNN_ARG_TEMP, DNN_ARG_PATTERN]"""
|
||||
|
||||
ENGINE_CLASSIC: int
|
||||
ENGINE_NEW: int
|
||||
ENGINE_AUTO: int
|
||||
ENGINE_ORT: int
|
||||
EngineType = int
|
||||
"""One of [ENGINE_CLASSIC, ENGINE_NEW, ENGINE_AUTO, ENGINE_ORT]"""
|
||||
|
||||
DNN_PMODE_NULL: int
|
||||
DNN_PMODE_CROP_CENTER: int
|
||||
DNN_PMODE_LETTERBOX: int
|
||||
ImagePaddingMode = int
|
||||
"""One of [DNN_PMODE_NULL, DNN_PMODE_CROP_CENTER, DNN_PMODE_LETTERBOX]"""
|
||||
|
||||
SoftNMSMethod_SOFTNMS_LINEAR: int
|
||||
SOFT_NMSMETHOD_SOFTNMS_LINEAR: int
|
||||
SoftNMSMethod_SOFTNMS_GAUSSIAN: int
|
||||
SOFT_NMSMETHOD_SOFTNMS_GAUSSIAN: int
|
||||
SoftNMSMethod = int
|
||||
"""One of [SoftNMSMethod_SOFTNMS_LINEAR, SOFT_NMSMETHOD_SOFTNMS_LINEAR, SoftNMSMethod_SOFTNMS_GAUSSIAN, SOFT_NMSMETHOD_SOFTNMS_GAUSSIAN]"""
|
||||
|
||||
|
||||
Reduce2Layer_ReduceType_MAX: int
|
||||
REDUCE2LAYER_REDUCE_TYPE_MAX: int
|
||||
Reduce2Layer_ReduceType_MIN: int
|
||||
REDUCE2LAYER_REDUCE_TYPE_MIN: int
|
||||
Reduce2Layer_ReduceType_MEAN: int
|
||||
REDUCE2LAYER_REDUCE_TYPE_MEAN: int
|
||||
Reduce2Layer_ReduceType_SUM: int
|
||||
REDUCE2LAYER_REDUCE_TYPE_SUM: int
|
||||
Reduce2Layer_ReduceType_L1: int
|
||||
REDUCE2LAYER_REDUCE_TYPE_L1: int
|
||||
Reduce2Layer_ReduceType_L2: int
|
||||
REDUCE2LAYER_REDUCE_TYPE_L2: int
|
||||
Reduce2Layer_ReduceType_PROD: int
|
||||
REDUCE2LAYER_REDUCE_TYPE_PROD: int
|
||||
Reduce2Layer_ReduceType_SUM_SQUARE: int
|
||||
REDUCE2LAYER_REDUCE_TYPE_SUM_SQUARE: int
|
||||
Reduce2Layer_ReduceType_LOG_SUM: int
|
||||
REDUCE2LAYER_REDUCE_TYPE_LOG_SUM: int
|
||||
Reduce2Layer_ReduceType_LOG_SUM_EXP: int
|
||||
REDUCE2LAYER_REDUCE_TYPE_LOG_SUM_EXP: int
|
||||
Reduce2Layer_ReduceType = int
|
||||
"""One of [Reduce2Layer_ReduceType_MAX, REDUCE2LAYER_REDUCE_TYPE_MAX, Reduce2Layer_ReduceType_MIN, REDUCE2LAYER_REDUCE_TYPE_MIN, Reduce2Layer_ReduceType_MEAN, REDUCE2LAYER_REDUCE_TYPE_MEAN, Reduce2Layer_ReduceType_SUM, REDUCE2LAYER_REDUCE_TYPE_SUM, Reduce2Layer_ReduceType_L1, REDUCE2LAYER_REDUCE_TYPE_L1, Reduce2Layer_ReduceType_L2, REDUCE2LAYER_REDUCE_TYPE_L2, Reduce2Layer_ReduceType_PROD, REDUCE2LAYER_REDUCE_TYPE_PROD, Reduce2Layer_ReduceType_SUM_SQUARE, REDUCE2LAYER_REDUCE_TYPE_SUM_SQUARE, Reduce2Layer_ReduceType_LOG_SUM, REDUCE2LAYER_REDUCE_TYPE_LOG_SUM, Reduce2Layer_ReduceType_LOG_SUM_EXP, REDUCE2LAYER_REDUCE_TYPE_LOG_SUM_EXP]"""
|
||||
|
||||
NaryEltwiseLayer_OPERATION_AND: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_AND: int
|
||||
NaryEltwiseLayer_OPERATION_EQUAL: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_EQUAL: int
|
||||
NaryEltwiseLayer_OPERATION_GREATER: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_GREATER: int
|
||||
NaryEltwiseLayer_OPERATION_GREATER_EQUAL: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_GREATER_EQUAL: int
|
||||
NaryEltwiseLayer_OPERATION_LESS: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_LESS: int
|
||||
NaryEltwiseLayer_OPERATION_LESS_EQUAL: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_LESS_EQUAL: int
|
||||
NaryEltwiseLayer_OPERATION_OR: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_OR: int
|
||||
NaryEltwiseLayer_OPERATION_POW: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_POW: int
|
||||
NaryEltwiseLayer_OPERATION_XOR: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_XOR: int
|
||||
NaryEltwiseLayer_OPERATION_BITSHIFT: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_BITSHIFT: int
|
||||
NaryEltwiseLayer_OPERATION_MAX: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_MAX: int
|
||||
NaryEltwiseLayer_OPERATION_MEAN: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_MEAN: int
|
||||
NaryEltwiseLayer_OPERATION_MIN: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_MIN: int
|
||||
NaryEltwiseLayer_OPERATION_MOD: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_MOD: int
|
||||
NaryEltwiseLayer_OPERATION_FMOD: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_FMOD: int
|
||||
NaryEltwiseLayer_OPERATION_PROD: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_PROD: int
|
||||
NaryEltwiseLayer_OPERATION_SUB: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_SUB: int
|
||||
NaryEltwiseLayer_OPERATION_SUM: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_SUM: int
|
||||
NaryEltwiseLayer_OPERATION_ADD: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_ADD: int
|
||||
NaryEltwiseLayer_OPERATION_DIV: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_DIV: int
|
||||
NaryEltwiseLayer_OPERATION_WHERE: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_WHERE: int
|
||||
NaryEltwiseLayer_OPERATION_BITWISE_AND: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_BITWISE_AND: int
|
||||
NaryEltwiseLayer_OPERATION_BITWISE_OR: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_BITWISE_OR: int
|
||||
NaryEltwiseLayer_OPERATION_BITWISE_XOR: int
|
||||
NARY_ELTWISE_LAYER_OPERATION_BITWISE_XOR: int
|
||||
NaryEltwiseLayer_OPERATION = int
|
||||
"""One of [NaryEltwiseLayer_OPERATION_AND, NARY_ELTWISE_LAYER_OPERATION_AND, NaryEltwiseLayer_OPERATION_EQUAL, NARY_ELTWISE_LAYER_OPERATION_EQUAL, NaryEltwiseLayer_OPERATION_GREATER, NARY_ELTWISE_LAYER_OPERATION_GREATER, NaryEltwiseLayer_OPERATION_GREATER_EQUAL, NARY_ELTWISE_LAYER_OPERATION_GREATER_EQUAL, NaryEltwiseLayer_OPERATION_LESS, NARY_ELTWISE_LAYER_OPERATION_LESS, NaryEltwiseLayer_OPERATION_LESS_EQUAL, NARY_ELTWISE_LAYER_OPERATION_LESS_EQUAL, NaryEltwiseLayer_OPERATION_OR, NARY_ELTWISE_LAYER_OPERATION_OR, NaryEltwiseLayer_OPERATION_POW, NARY_ELTWISE_LAYER_OPERATION_POW, NaryEltwiseLayer_OPERATION_XOR, NARY_ELTWISE_LAYER_OPERATION_XOR, NaryEltwiseLayer_OPERATION_BITSHIFT, NARY_ELTWISE_LAYER_OPERATION_BITSHIFT, NaryEltwiseLayer_OPERATION_MAX, NARY_ELTWISE_LAYER_OPERATION_MAX, NaryEltwiseLayer_OPERATION_MEAN, NARY_ELTWISE_LAYER_OPERATION_MEAN, NaryEltwiseLayer_OPERATION_MIN, NARY_ELTWISE_LAYER_OPERATION_MIN, NaryEltwiseLayer_OPERATION_MOD, NARY_ELTWISE_LAYER_OPERATION_MOD, NaryEltwiseLayer_OPERATION_FMOD, NARY_ELTWISE_LAYER_OPERATION_FMOD, NaryEltwiseLayer_OPERATION_PROD, NARY_ELTWISE_LAYER_OPERATION_PROD, NaryEltwiseLayer_OPERATION_SUB, NARY_ELTWISE_LAYER_OPERATION_SUB, NaryEltwiseLayer_OPERATION_SUM, NARY_ELTWISE_LAYER_OPERATION_SUM, NaryEltwiseLayer_OPERATION_ADD, NARY_ELTWISE_LAYER_OPERATION_ADD, NaryEltwiseLayer_OPERATION_DIV, NARY_ELTWISE_LAYER_OPERATION_DIV, NaryEltwiseLayer_OPERATION_WHERE, NARY_ELTWISE_LAYER_OPERATION_WHERE, NaryEltwiseLayer_OPERATION_BITWISE_AND, NARY_ELTWISE_LAYER_OPERATION_BITWISE_AND, NaryEltwiseLayer_OPERATION_BITWISE_OR, NARY_ELTWISE_LAYER_OPERATION_BITWISE_OR, NaryEltwiseLayer_OPERATION_BITWISE_XOR, NARY_ELTWISE_LAYER_OPERATION_BITWISE_XOR]"""
|
||||
|
||||
|
||||
# Classes
|
||||
class DictValue:
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, i: int) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, p: float) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, s: str) -> None: ...
|
||||
|
||||
def isInt(self) -> bool: ...
|
||||
|
||||
def isString(self) -> bool: ...
|
||||
|
||||
def isReal(self) -> bool: ...
|
||||
|
||||
def getIntValue(self, idx: int = ...) -> int: ...
|
||||
|
||||
def getRealValue(self, idx: int = ...) -> float: ...
|
||||
|
||||
def getStringValue(self, idx: int = ...) -> str: ...
|
||||
|
||||
|
||||
class Layer(cv2.Algorithm):
|
||||
blobs: _typing.Sequence[cv2.typing.MatLike]
|
||||
@property
|
||||
def name(self) -> str: ...
|
||||
@property
|
||||
def type(self) -> str: ...
|
||||
@property
|
||||
def preferableTarget(self) -> int: ...
|
||||
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def finalize(self, inputs: _typing.Sequence[cv2.typing.MatLike], outputs: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def finalize(self, inputs: _typing.Sequence[cv2.UMat], outputs: _typing.Sequence[cv2.UMat] | None = ...) -> _typing.Sequence[cv2.UMat]: ...
|
||||
|
||||
def run(self, inputs: _typing.Sequence[cv2.typing.MatLike], internals: _typing.Sequence[cv2.typing.MatLike], outputs: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> tuple[_typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike]]: ...
|
||||
|
||||
def outputNameToIndex(self, outputName: str) -> int: ...
|
||||
|
||||
|
||||
class Net:
|
||||
# Functions
|
||||
def __init__(self) -> None: ...
|
||||
|
||||
@classmethod
|
||||
@_typing.overload
|
||||
def readFromModelOptimizer(cls, xml: str | os.PathLike[str], bin: str | os.PathLike[str]) -> Net: ...
|
||||
@classmethod
|
||||
@_typing.overload
|
||||
def readFromModelOptimizer(cls, bufferModelConfig: numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]], bufferWeights: numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]]) -> Net: ...
|
||||
|
||||
def empty(self) -> bool: ...
|
||||
|
||||
def dump(self) -> str: ...
|
||||
|
||||
def dumpToFile(self, path: str | os.PathLike[str]) -> None: ...
|
||||
|
||||
def dumpToPbtxt(self, path: str | os.PathLike[str]) -> None: ...
|
||||
|
||||
def addLayer(self, name: str, type: str, dtype: int, params: cv2.typing.LayerParams) -> int: ...
|
||||
|
||||
def addLayerToPrev(self, name: str, type: str, dtype: int, params: cv2.typing.LayerParams) -> int: ...
|
||||
|
||||
def getLayerId(self, layer: str) -> int: ...
|
||||
|
||||
def getLayerNames(self) -> _typing.Sequence[str]: ...
|
||||
|
||||
@_typing.overload
|
||||
def getLayer(self, layerId: int) -> Layer: ...
|
||||
@_typing.overload
|
||||
def getLayer(self, layerName: str) -> Layer: ...
|
||||
@_typing.overload
|
||||
def getLayer(self, layerId: cv2.typing.LayerId) -> Layer: ...
|
||||
|
||||
def connect(self, outPin: str, inpPin: str) -> None: ...
|
||||
|
||||
def registerOutput(self, outputName: str, layerId: int, outputPort: int) -> int: ...
|
||||
|
||||
def setInputsNames(self, inputBlobNames: _typing.Sequence[str]) -> None: ...
|
||||
|
||||
def setInputShape(self, inputName: str, shape: cv2.typing.MatShape) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def forward(self, outputName: str = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def forward(self, outputBlobs: _typing.Sequence[cv2.typing.MatLike] | None = ..., outputName: str = ...) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def forward(self, outputBlobs: _typing.Sequence[cv2.UMat] | None = ..., outputName: str = ...) -> _typing.Sequence[cv2.UMat]: ...
|
||||
@_typing.overload
|
||||
def forward(self, outBlobNames: _typing.Sequence[str], outputBlobs: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def forward(self, outBlobNames: _typing.Sequence[str], outputBlobs: _typing.Sequence[cv2.UMat] | None = ...) -> _typing.Sequence[cv2.UMat]: ...
|
||||
|
||||
def forwardAsync(self, outputName: str = ...) -> cv2.AsyncArray: ...
|
||||
|
||||
def forwardAndRetrieve(self, outBlobNames: _typing.Sequence[str]) -> _typing.Sequence[_typing.Sequence[cv2.typing.MatLike]]: ...
|
||||
|
||||
def setPreferableBackend(self, backendId: int) -> None: ...
|
||||
|
||||
def setPreferableTarget(self, targetId: int) -> None: ...
|
||||
|
||||
def finalizeNet(self) -> None: ...
|
||||
|
||||
def setTracingMode(self, tracingMode: TracingMode) -> None: ...
|
||||
|
||||
def getTracingMode(self) -> TracingMode: ...
|
||||
|
||||
def setProfilingMode(self, profilingMode: ProfilingMode) -> None: ...
|
||||
|
||||
def getProfilingMode(self) -> ProfilingMode: ...
|
||||
|
||||
def getModelFormat(self) -> ModelFormat: ...
|
||||
|
||||
@_typing.overload
|
||||
def setInput(self, blob: cv2.typing.MatLike, name: str = ..., scalefactor: float = ..., mean: cv2.typing.Scalar = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def setInput(self, blob: cv2.UMat, name: str = ..., scalefactor: float = ..., mean: cv2.typing.Scalar = ...) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def setParam(self, layer: int, numParam: int, blob: cv2.typing.MatLike) -> None: ...
|
||||
@_typing.overload
|
||||
def setParam(self, layerName: str, numParam: int, blob: cv2.typing.MatLike) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def getParam(self, layer: int, numParam: int = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def getParam(self, layerName: str, numParam: int = ...) -> cv2.typing.MatLike: ...
|
||||
|
||||
def getUnconnectedOutLayers(self) -> _typing.Sequence[int]: ...
|
||||
|
||||
def getUnconnectedOutLayersNames(self) -> _typing.Sequence[str]: ...
|
||||
|
||||
def getLayerShapes(self, netInputShapes: _typing.Sequence[cv2.typing.MatShape], netInputTypes: _typing.Sequence[int], layerId: int) -> tuple[_typing.Sequence[cv2.typing.MatShape], _typing.Sequence[cv2.typing.MatShape]]: ...
|
||||
|
||||
def getFLOPS(self, netInputShapes: _typing.Sequence[cv2.typing.MatShape], netInputTypes: _typing.Sequence[int]) -> int: ...
|
||||
|
||||
def getLayerTypes(self) -> _typing.Sequence[str]: ...
|
||||
|
||||
def getLayersCount(self, layerType: str) -> int: ...
|
||||
|
||||
def getMemoryConsumption(self, netInputShapes: _typing.Sequence[cv2.typing.MatShape], netInputTypes: _typing.Sequence[int]) -> tuple[int, int]: ...
|
||||
|
||||
def enableFusion(self, fusion: bool) -> None: ...
|
||||
|
||||
def enableWinograd(self, useWinograd: bool) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def getPerfProfile(self) -> tuple[int, _typing.Sequence[float]]: ...
|
||||
@_typing.overload
|
||||
def getPerfProfile(self) -> tuple[_typing.Sequence[str], _typing.Sequence[str], _typing.Sequence[str]]: ...
|
||||
|
||||
def enableKVCache(self) -> None: ...
|
||||
|
||||
def disableKVCache(self) -> None: ...
|
||||
|
||||
def resetKVCache(self) -> None: ...
|
||||
|
||||
def printPerfProfile(self) -> None: ...
|
||||
|
||||
|
||||
class Image2BlobParams:
|
||||
scalefactor: cv2.typing.Scalar
|
||||
size: cv2.typing.Size
|
||||
mean: cv2.typing.Scalar
|
||||
swapRB: bool
|
||||
ddepth: int
|
||||
datalayout: cv2.DataLayout
|
||||
paddingmode: ImagePaddingMode
|
||||
borderValue: cv2.typing.Scalar
|
||||
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, scalefactor: cv2.typing.Scalar, size: cv2.typing.Size = ..., mean: cv2.typing.Scalar = ..., swapRB: bool = ..., ddepth: int = ..., datalayout: cv2.DataLayout = ..., mode: ImagePaddingMode = ..., borderValue: cv2.typing.Scalar = ...) -> None: ...
|
||||
|
||||
def blobRectToImageRect(self, rBlob: cv2.typing.Rect, size: cv2.typing.Size) -> cv2.typing.Rect: ...
|
||||
|
||||
def blobRectsToImageRects(self, rBlob: _typing.Sequence[cv2.typing.Rect], size: cv2.typing.Size) -> _typing.Sequence[cv2.typing.Rect]: ...
|
||||
|
||||
|
||||
class Model:
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, model: str | os.PathLike[str], config: str | os.PathLike[str] = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, network: Net) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def setInputSize(self, size: cv2.typing.Size) -> Model: ...
|
||||
@_typing.overload
|
||||
def setInputSize(self, width: int, height: int) -> Model: ...
|
||||
|
||||
def setInputMean(self, mean: cv2.typing.Scalar) -> Model: ...
|
||||
|
||||
def setInputScale(self, scale: cv2.typing.Scalar) -> Model: ...
|
||||
|
||||
def setInputCrop(self, crop: bool) -> Model: ...
|
||||
|
||||
def setInputSwapRB(self, swapRB: bool) -> Model: ...
|
||||
|
||||
def setOutputNames(self, outNames: _typing.Sequence[str]) -> Model: ...
|
||||
|
||||
def setInputParams(self, scale: float = ..., size: cv2.typing.Size = ..., mean: cv2.typing.Scalar = ..., swapRB: bool = ..., crop: bool = ...) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def predict(self, frame: cv2.typing.MatLike, outs: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def predict(self, frame: cv2.UMat, outs: _typing.Sequence[cv2.UMat] | None = ...) -> _typing.Sequence[cv2.UMat]: ...
|
||||
|
||||
def setPreferableBackend(self, backendId: Backend) -> Model: ...
|
||||
|
||||
def setPreferableTarget(self, targetId: Target) -> Model: ...
|
||||
|
||||
def enableWinograd(self, useWinograd: bool) -> Model: ...
|
||||
|
||||
|
||||
class ClassificationModel(Model):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, model: str | os.PathLike[str], config: str | os.PathLike[str] = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, network: Net) -> None: ...
|
||||
|
||||
def setEnableSoftmaxPostProcessing(self, enable: bool) -> ClassificationModel: ...
|
||||
|
||||
def getEnableSoftmaxPostProcessing(self) -> bool: ...
|
||||
|
||||
@_typing.overload
|
||||
def classify(self, frame: cv2.typing.MatLike) -> tuple[int, float]: ...
|
||||
@_typing.overload
|
||||
def classify(self, frame: cv2.UMat) -> tuple[int, float]: ...
|
||||
|
||||
|
||||
class KeypointsModel(Model):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, model: str | os.PathLike[str], config: str | os.PathLike[str] = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, network: Net) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def estimate(self, frame: cv2.typing.MatLike, thresh: float = ...) -> _typing.Sequence[cv2.typing.Point2f]: ...
|
||||
@_typing.overload
|
||||
def estimate(self, frame: cv2.UMat, thresh: float = ...) -> _typing.Sequence[cv2.typing.Point2f]: ...
|
||||
|
||||
|
||||
class SegmentationModel(Model):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, model: str | os.PathLike[str], config: str | os.PathLike[str] = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, network: Net) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def segment(self, frame: cv2.typing.MatLike, mask: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def segment(self, frame: cv2.UMat, mask: cv2.UMat | None = ...) -> cv2.UMat: ...
|
||||
|
||||
|
||||
class DetectionModel(Model):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, model: str | os.PathLike[str], config: str | os.PathLike[str] = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, network: Net) -> None: ...
|
||||
|
||||
def setNmsAcrossClasses(self, value: bool) -> DetectionModel: ...
|
||||
|
||||
def getNmsAcrossClasses(self) -> bool: ...
|
||||
|
||||
@_typing.overload
|
||||
def detect(self, frame: cv2.typing.MatLike, confThreshold: float = ..., nmsThreshold: float = ...) -> tuple[_typing.Sequence[int], _typing.Sequence[float], _typing.Sequence[cv2.typing.Rect]]: ...
|
||||
@_typing.overload
|
||||
def detect(self, frame: cv2.UMat, confThreshold: float = ..., nmsThreshold: float = ...) -> tuple[_typing.Sequence[int], _typing.Sequence[float], _typing.Sequence[cv2.typing.Rect]]: ...
|
||||
|
||||
|
||||
class TextRecognitionModel(Model):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, network: Net) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, model: str | os.PathLike[str], config: str | os.PathLike[str] = ...) -> None: ...
|
||||
|
||||
def setDecodeType(self, decodeType: str) -> TextRecognitionModel: ...
|
||||
|
||||
def getDecodeType(self) -> str: ...
|
||||
|
||||
def setDecodeOptsCTCPrefixBeamSearch(self, beamSize: int, vocPruneSize: int = ...) -> TextRecognitionModel: ...
|
||||
|
||||
def setVocabulary(self, vocabulary: _typing.Sequence[str]) -> TextRecognitionModel: ...
|
||||
|
||||
def getVocabulary(self) -> _typing.Sequence[str]: ...
|
||||
|
||||
@_typing.overload
|
||||
def recognize(self, frame: cv2.typing.MatLike) -> str: ...
|
||||
@_typing.overload
|
||||
def recognize(self, frame: cv2.UMat) -> str: ...
|
||||
@_typing.overload
|
||||
def recognize(self, frame: cv2.typing.MatLike, roiRects: _typing.Sequence[cv2.typing.MatLike]) -> _typing.Sequence[str]: ...
|
||||
@_typing.overload
|
||||
def recognize(self, frame: cv2.UMat, roiRects: _typing.Sequence[cv2.UMat]) -> _typing.Sequence[str]: ...
|
||||
|
||||
|
||||
class TextDetectionModel(Model):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def detect(self, frame: cv2.typing.MatLike) -> tuple[_typing.Sequence[_typing.Sequence[cv2.typing.Point]], _typing.Sequence[float]]: ...
|
||||
@_typing.overload
|
||||
def detect(self, frame: cv2.UMat) -> tuple[_typing.Sequence[_typing.Sequence[cv2.typing.Point]], _typing.Sequence[float]]: ...
|
||||
@_typing.overload
|
||||
def detect(self, frame: cv2.typing.MatLike) -> _typing.Sequence[_typing.Sequence[cv2.typing.Point]]: ...
|
||||
@_typing.overload
|
||||
def detect(self, frame: cv2.UMat) -> _typing.Sequence[_typing.Sequence[cv2.typing.Point]]: ...
|
||||
|
||||
@_typing.overload
|
||||
def detectTextRectangles(self, frame: cv2.typing.MatLike) -> tuple[_typing.Sequence[cv2.typing.RotatedRect], _typing.Sequence[float]]: ...
|
||||
@_typing.overload
|
||||
def detectTextRectangles(self, frame: cv2.UMat) -> tuple[_typing.Sequence[cv2.typing.RotatedRect], _typing.Sequence[float]]: ...
|
||||
@_typing.overload
|
||||
def detectTextRectangles(self, frame: cv2.typing.MatLike) -> _typing.Sequence[cv2.typing.RotatedRect]: ...
|
||||
@_typing.overload
|
||||
def detectTextRectangles(self, frame: cv2.UMat) -> _typing.Sequence[cv2.typing.RotatedRect]: ...
|
||||
|
||||
|
||||
class TextDetectionModel_EAST(TextDetectionModel):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, network: Net) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, model: str | os.PathLike[str], config: str | os.PathLike[str] = ...) -> None: ...
|
||||
|
||||
def setConfidenceThreshold(self, confThreshold: float) -> TextDetectionModel_EAST: ...
|
||||
|
||||
def getConfidenceThreshold(self) -> float: ...
|
||||
|
||||
def setNMSThreshold(self, nmsThreshold: float) -> TextDetectionModel_EAST: ...
|
||||
|
||||
def getNMSThreshold(self) -> float: ...
|
||||
|
||||
|
||||
class TextDetectionModel_DB(TextDetectionModel):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self, network: Net) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, model: str | os.PathLike[str], config: str | os.PathLike[str] = ...) -> None: ...
|
||||
|
||||
def setBinaryThreshold(self, binaryThreshold: float) -> TextDetectionModel_DB: ...
|
||||
|
||||
def getBinaryThreshold(self) -> float: ...
|
||||
|
||||
def setPolygonThreshold(self, polygonThreshold: float) -> TextDetectionModel_DB: ...
|
||||
|
||||
def getPolygonThreshold(self) -> float: ...
|
||||
|
||||
def setUnclipRatio(self, unclipRatio: float) -> TextDetectionModel_DB: ...
|
||||
|
||||
def getUnclipRatio(self) -> float: ...
|
||||
|
||||
def setMaxCandidates(self, maxCandidates: int) -> TextDetectionModel_DB: ...
|
||||
|
||||
def getMaxCandidates(self) -> int: ...
|
||||
|
||||
|
||||
class Tokenizer:
|
||||
# Functions
|
||||
@classmethod
|
||||
def load(cls, model_config: str | os.PathLike[str]) -> Tokenizer: ...
|
||||
|
||||
def encode(self, text: str) -> _typing.Sequence[int]: ...
|
||||
|
||||
def decode(self, tokens: _typing.Sequence[int]) -> str: ...
|
||||
|
||||
|
||||
class LayerProtocol(Protocol):
|
||||
# Functions
|
||||
def __init__(self, params: dict[str, DictValue], blobs: _typing.Sequence[cv2.typing.MatLike]) -> None: ...
|
||||
|
||||
def getMemoryShapes(self, inputs: _typing.Sequence[_typing.Sequence[int]]) -> _typing.Sequence[_typing.Sequence[int]]: ...
|
||||
|
||||
def forward(self, inputs: _typing.Sequence[cv2.typing.MatLike]) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
||||
|
||||
|
||||
|
||||
# Functions
|
||||
def NMSBoxes(bboxes: _typing.Sequence[cv2.typing.Rect2d], scores: _typing.Sequence[float], score_threshold: float, nms_threshold: float, eta: float = ..., top_k: int = ...) -> _typing.Sequence[int]: ...
|
||||
|
||||
def NMSBoxesBatched(bboxes: _typing.Sequence[cv2.typing.Rect2d], scores: _typing.Sequence[float], class_ids: _typing.Sequence[int], score_threshold: float, nms_threshold: float, eta: float = ..., top_k: int = ...) -> _typing.Sequence[int]: ...
|
||||
|
||||
def NMSBoxesRotated(bboxes: _typing.Sequence[cv2.typing.RotatedRect], scores: _typing.Sequence[float], score_threshold: float, nms_threshold: float, eta: float = ..., top_k: int = ...) -> _typing.Sequence[int]: ...
|
||||
|
||||
@_typing.overload
|
||||
def blobFromImage(image: cv2.typing.MatLike, scalefactor: float = ..., size: cv2.typing.Size = ..., mean: cv2.typing.Scalar = ..., swapRB: bool = ..., crop: bool = ..., ddepth: int = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def blobFromImage(image: cv2.UMat, scalefactor: float = ..., size: cv2.typing.Size = ..., mean: cv2.typing.Scalar = ..., swapRB: bool = ..., crop: bool = ..., ddepth: int = ...) -> cv2.typing.MatLike: ...
|
||||
|
||||
@_typing.overload
|
||||
def blobFromImageWithParams(image: cv2.typing.MatLike, param: Image2BlobParams = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def blobFromImageWithParams(image: cv2.UMat, param: Image2BlobParams = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def blobFromImageWithParams(image: cv2.typing.MatLike, blob: cv2.typing.MatLike | None = ..., param: Image2BlobParams = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def blobFromImageWithParams(image: cv2.UMat, blob: cv2.UMat | None = ..., param: Image2BlobParams = ...) -> cv2.UMat: ...
|
||||
|
||||
@_typing.overload
|
||||
def blobFromImages(images: _typing.Sequence[cv2.typing.MatLike], scalefactor: float = ..., size: cv2.typing.Size = ..., mean: cv2.typing.Scalar = ..., swapRB: bool = ..., crop: bool = ..., ddepth: int = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def blobFromImages(images: _typing.Sequence[cv2.UMat], scalefactor: float = ..., size: cv2.typing.Size = ..., mean: cv2.typing.Scalar = ..., swapRB: bool = ..., crop: bool = ..., ddepth: int = ...) -> cv2.typing.MatLike: ...
|
||||
|
||||
@_typing.overload
|
||||
def blobFromImagesWithParams(images: _typing.Sequence[cv2.typing.MatLike], param: Image2BlobParams = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def blobFromImagesWithParams(images: _typing.Sequence[cv2.UMat], param: Image2BlobParams = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def blobFromImagesWithParams(images: _typing.Sequence[cv2.typing.MatLike], blob: cv2.typing.MatLike | None = ..., param: Image2BlobParams = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def blobFromImagesWithParams(images: _typing.Sequence[cv2.UMat], blob: cv2.UMat | None = ..., param: Image2BlobParams = ...) -> cv2.UMat: ...
|
||||
|
||||
def getAvailableTargets(be: Backend) -> _typing.Sequence[Target]: ...
|
||||
|
||||
def getInferenceEngineBackendType() -> str: ...
|
||||
|
||||
def getInferenceEngineCPUType() -> str: ...
|
||||
|
||||
def getInferenceEngineVPUType() -> str: ...
|
||||
|
||||
@_typing.overload
|
||||
def imagesFromBlob(blob_: cv2.typing.MatLike, images_: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def imagesFromBlob(blob_: cv2.typing.MatLike, images_: _typing.Sequence[cv2.UMat] | None = ...) -> _typing.Sequence[cv2.UMat]: ...
|
||||
|
||||
@_typing.overload
|
||||
def readNet(model: str | os.PathLike[str], config: str | os.PathLike[str] = ..., framework: str = ..., engine: int = ...) -> Net: ...
|
||||
@_typing.overload
|
||||
def readNet(framework: str, bufferModel: numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]], bufferConfig: numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]] = ..., engine: int = ...) -> Net: ...
|
||||
|
||||
@_typing.overload
|
||||
def readNetFromModelOptimizer(xml: str | os.PathLike[str], bin: str | os.PathLike[str] = ...) -> Net: ...
|
||||
@_typing.overload
|
||||
def readNetFromModelOptimizer(bufferModelConfig: numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]], bufferWeights: numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]]) -> Net: ...
|
||||
|
||||
@_typing.overload
|
||||
def readNetFromONNX(onnxFile: str | os.PathLike[str], engine: int = ...) -> Net: ...
|
||||
@_typing.overload
|
||||
def readNetFromONNX(buffer: numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]], engine: int = ...) -> Net: ...
|
||||
|
||||
@_typing.overload
|
||||
def readNetFromTFLite(model: str | os.PathLike[str], engine: int = ...) -> Net: ...
|
||||
@_typing.overload
|
||||
def readNetFromTFLite(bufferModel: numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]], engine: int = ...) -> Net: ...
|
||||
|
||||
@_typing.overload
|
||||
def readNetFromTensorflow(model: str | os.PathLike[str], config: str | os.PathLike[str] = ..., engine: int = ..., extraOutputs: _typing.Sequence[str] = ...) -> Net: ...
|
||||
@_typing.overload
|
||||
def readNetFromTensorflow(bufferModel: numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]], bufferConfig: numpy.ndarray[_typing.Any, numpy.dtype[numpy.uint8]] = ..., engine: int = ..., extraOutputs: _typing.Sequence[str] = ...) -> Net: ...
|
||||
|
||||
def readTensorFromONNX(path: str | os.PathLike[str]) -> cv2.typing.MatLike: ...
|
||||
|
||||
def releaseHDDLPlugin() -> None: ...
|
||||
|
||||
def resetMyriadDevice() -> None: ...
|
||||
|
||||
def setInferenceEngineBackendType(newBackendType: str) -> str: ...
|
||||
|
||||
def softNMSBoxes(bboxes: _typing.Sequence[cv2.typing.Rect], scores: _typing.Sequence[float], score_threshold: float, nms_threshold: float, top_k: int = ..., sigma: float = ..., method: SoftNMSMethod = ...) -> tuple[_typing.Sequence[float], _typing.Sequence[int]]: ...
|
||||
|
||||
def writeTextGraph(model: str | os.PathLike[str], output: str | os.PathLike[str]) -> None: ...
|
||||
|
||||
|
||||
@@ -0,0 +1,72 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
import cv2
|
||||
import cv2.typing
|
||||
import typing as _typing
|
||||
|
||||
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def calibrate(objectPoints: _typing.Sequence[cv2.typing.MatLike], imagePoints: _typing.Sequence[cv2.typing.MatLike], image_size: cv2.typing.Size, K: cv2.typing.MatLike, D: cv2.typing.MatLike, rvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., tvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.typing.MatLike, cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike]]: ...
|
||||
@_typing.overload
|
||||
def calibrate(objectPoints: _typing.Sequence[cv2.UMat], imagePoints: _typing.Sequence[cv2.UMat], image_size: cv2.typing.Size, K: cv2.UMat, D: cv2.UMat, rvecs: _typing.Sequence[cv2.UMat] | None = ..., tvecs: _typing.Sequence[cv2.UMat] | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.UMat, cv2.UMat, _typing.Sequence[cv2.UMat], _typing.Sequence[cv2.UMat]]: ...
|
||||
|
||||
@_typing.overload
|
||||
def distortPoints(undistorted: cv2.typing.MatLike, K: cv2.typing.MatLike, D: cv2.typing.MatLike, distorted: cv2.typing.MatLike | None = ..., alpha: float = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def distortPoints(undistorted: cv2.UMat, K: cv2.UMat, D: cv2.UMat, distorted: cv2.UMat | None = ..., alpha: float = ...) -> cv2.UMat: ...
|
||||
@_typing.overload
|
||||
def distortPoints(undistorted: cv2.typing.MatLike, Kundistorted: cv2.typing.MatLike, K: cv2.typing.MatLike, D: cv2.typing.MatLike, distorted: cv2.typing.MatLike | None = ..., alpha: float = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def distortPoints(undistorted: cv2.UMat, Kundistorted: cv2.UMat, K: cv2.UMat, D: cv2.UMat, distorted: cv2.UMat | None = ..., alpha: float = ...) -> cv2.UMat: ...
|
||||
|
||||
@_typing.overload
|
||||
def estimateNewCameraMatrixForUndistortRectify(K: cv2.typing.MatLike, D: cv2.typing.MatLike, image_size: cv2.typing.Size, R: cv2.typing.MatLike, P: cv2.typing.MatLike | None = ..., balance: float = ..., new_size: cv2.typing.Size = ..., fov_scale: float = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def estimateNewCameraMatrixForUndistortRectify(K: cv2.UMat, D: cv2.UMat, image_size: cv2.typing.Size, R: cv2.UMat, P: cv2.UMat | None = ..., balance: float = ..., new_size: cv2.typing.Size = ..., fov_scale: float = ...) -> cv2.UMat: ...
|
||||
|
||||
@_typing.overload
|
||||
def initUndistortRectifyMap(K: cv2.typing.MatLike, D: cv2.typing.MatLike | None, R: cv2.typing.MatLike, P: cv2.typing.MatLike, size: cv2.typing.Size, m1type: int, map1: cv2.typing.MatLike | None = ..., map2: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def initUndistortRectifyMap(K: cv2.UMat, D: cv2.UMat | None, R: cv2.UMat, P: cv2.UMat, size: cv2.typing.Size, m1type: int, map1: cv2.UMat | None = ..., map2: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat]: ...
|
||||
|
||||
@_typing.overload
|
||||
def projectPoints(objectPoints: cv2.typing.MatLike, rvec: cv2.typing.MatLike, tvec: cv2.typing.MatLike, K: cv2.typing.MatLike, D: cv2.typing.MatLike, imagePoints: cv2.typing.MatLike | None = ..., alpha: float = ..., jacobian: cv2.typing.MatLike | None = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def projectPoints(objectPoints: cv2.UMat, rvec: cv2.UMat, tvec: cv2.UMat, K: cv2.UMat, D: cv2.UMat, imagePoints: cv2.UMat | None = ..., alpha: float = ..., jacobian: cv2.UMat | None = ...) -> tuple[cv2.UMat, cv2.UMat]: ...
|
||||
|
||||
@_typing.overload
|
||||
def solvePnP(objectPoints: cv2.typing.MatLike, imagePoints: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, rvec: cv2.typing.MatLike | None = ..., tvec: cv2.typing.MatLike | None = ..., useExtrinsicGuess: bool = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[bool, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def solvePnP(objectPoints: cv2.UMat, imagePoints: cv2.UMat, cameraMatrix: cv2.UMat, distCoeffs: cv2.UMat, rvec: cv2.UMat | None = ..., tvec: cv2.UMat | None = ..., useExtrinsicGuess: bool = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[bool, cv2.UMat, cv2.UMat]: ...
|
||||
|
||||
@_typing.overload
|
||||
def solvePnPRansac(objectPoints: cv2.typing.MatLike, imagePoints: cv2.typing.MatLike, cameraMatrix: cv2.typing.MatLike, distCoeffs: cv2.typing.MatLike, rvec: cv2.typing.MatLike | None = ..., tvec: cv2.typing.MatLike | None = ..., useExtrinsicGuess: bool = ..., iterationsCount: int = ..., reprojectionError: float = ..., confidence: float = ..., inliers: cv2.typing.MatLike | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[bool, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def solvePnPRansac(objectPoints: cv2.UMat, imagePoints: cv2.UMat, cameraMatrix: cv2.UMat, distCoeffs: cv2.UMat, rvec: cv2.UMat | None = ..., tvec: cv2.UMat | None = ..., useExtrinsicGuess: bool = ..., iterationsCount: int = ..., reprojectionError: float = ..., confidence: float = ..., inliers: cv2.UMat | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[bool, cv2.UMat, cv2.UMat, cv2.UMat]: ...
|
||||
|
||||
@_typing.overload
|
||||
def stereoCalibrate(objectPoints: _typing.Sequence[cv2.typing.MatLike], imagePoints1: _typing.Sequence[cv2.typing.MatLike], imagePoints2: _typing.Sequence[cv2.typing.MatLike], K1: cv2.typing.MatLike, D1: cv2.typing.MatLike, K2: cv2.typing.MatLike, D2: cv2.typing.MatLike, imageSize: cv2.typing.Size, R: cv2.typing.MatLike | None = ..., T: cv2.typing.MatLike | None = ..., rvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., tvecs: _typing.Sequence[cv2.typing.MatLike] | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, _typing.Sequence[cv2.typing.MatLike], _typing.Sequence[cv2.typing.MatLike]]: ...
|
||||
@_typing.overload
|
||||
def stereoCalibrate(objectPoints: _typing.Sequence[cv2.UMat], imagePoints1: _typing.Sequence[cv2.UMat], imagePoints2: _typing.Sequence[cv2.UMat], K1: cv2.UMat, D1: cv2.UMat, K2: cv2.UMat, D2: cv2.UMat, imageSize: cv2.typing.Size, R: cv2.UMat | None = ..., T: cv2.UMat | None = ..., rvecs: _typing.Sequence[cv2.UMat] | None = ..., tvecs: _typing.Sequence[cv2.UMat] | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat, _typing.Sequence[cv2.UMat], _typing.Sequence[cv2.UMat]]: ...
|
||||
@_typing.overload
|
||||
def stereoCalibrate(objectPoints: _typing.Sequence[cv2.typing.MatLike], imagePoints1: _typing.Sequence[cv2.typing.MatLike], imagePoints2: _typing.Sequence[cv2.typing.MatLike], K1: cv2.typing.MatLike, D1: cv2.typing.MatLike, K2: cv2.typing.MatLike, D2: cv2.typing.MatLike, imageSize: cv2.typing.Size, R: cv2.typing.MatLike | None = ..., T: cv2.typing.MatLike | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def stereoCalibrate(objectPoints: _typing.Sequence[cv2.UMat], imagePoints1: _typing.Sequence[cv2.UMat], imagePoints2: _typing.Sequence[cv2.UMat], K1: cv2.UMat, D1: cv2.UMat, K2: cv2.UMat, D2: cv2.UMat, imageSize: cv2.typing.Size, R: cv2.UMat | None = ..., T: cv2.UMat | None = ..., flags: int = ..., criteria: cv2.typing.TermCriteria = ...) -> tuple[float, cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat]: ...
|
||||
|
||||
@_typing.overload
|
||||
def stereoRectify(K1: cv2.typing.MatLike, D1: cv2.typing.MatLike, K2: cv2.typing.MatLike, D2: cv2.typing.MatLike, imageSize: cv2.typing.Size, R: cv2.typing.MatLike, tvec: cv2.typing.MatLike, flags: int, R1: cv2.typing.MatLike | None = ..., R2: cv2.typing.MatLike | None = ..., P1: cv2.typing.MatLike | None = ..., P2: cv2.typing.MatLike | None = ..., Q: cv2.typing.MatLike | None = ..., newImageSize: cv2.typing.Size = ..., balance: float = ..., fov_scale: float = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def stereoRectify(K1: cv2.UMat, D1: cv2.UMat, K2: cv2.UMat, D2: cv2.UMat, imageSize: cv2.typing.Size, R: cv2.UMat, tvec: cv2.UMat, flags: int, R1: cv2.UMat | None = ..., R2: cv2.UMat | None = ..., P1: cv2.UMat | None = ..., P2: cv2.UMat | None = ..., Q: cv2.UMat | None = ..., newImageSize: cv2.typing.Size = ..., balance: float = ..., fov_scale: float = ...) -> tuple[cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat, cv2.UMat]: ...
|
||||
|
||||
@_typing.overload
|
||||
def undistortImage(distorted: cv2.typing.MatLike, K: cv2.typing.MatLike, D: cv2.typing.MatLike, undistorted: cv2.typing.MatLike | None = ..., Knew: cv2.typing.MatLike | None = ..., new_size: cv2.typing.Size = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def undistortImage(distorted: cv2.UMat, K: cv2.UMat, D: cv2.UMat, undistorted: cv2.UMat | None = ..., Knew: cv2.UMat | None = ..., new_size: cv2.typing.Size = ...) -> cv2.UMat: ...
|
||||
|
||||
@_typing.overload
|
||||
def undistortPoints(distorted: cv2.typing.MatLike, K: cv2.typing.MatLike, D: cv2.typing.MatLike, undistorted: cv2.typing.MatLike | None = ..., R: cv2.typing.MatLike | None = ..., P: cv2.typing.MatLike | None = ..., criteria: cv2.typing.TermCriteria = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def undistortPoints(distorted: cv2.UMat, K: cv2.UMat, D: cv2.UMat, undistorted: cv2.UMat | None = ..., R: cv2.UMat | None = ..., P: cv2.UMat | None = ..., criteria: cv2.typing.TermCriteria = ...) -> cv2.UMat: ...
|
||||
|
||||
|
||||
@@ -0,0 +1,65 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
import cv2
|
||||
import cv2.typing
|
||||
import os
|
||||
import typing as _typing
|
||||
|
||||
|
||||
# Enumerations
|
||||
FLANN_INDEX_TYPE_8U: int
|
||||
FLANN_INDEX_TYPE_8S: int
|
||||
FLANN_INDEX_TYPE_16U: int
|
||||
FLANN_INDEX_TYPE_16S: int
|
||||
FLANN_INDEX_TYPE_32S: int
|
||||
FLANN_INDEX_TYPE_32F: int
|
||||
FLANN_INDEX_TYPE_64F: int
|
||||
FLANN_INDEX_TYPE_STRING: int
|
||||
FLANN_INDEX_TYPE_BOOL: int
|
||||
FLANN_INDEX_TYPE_ALGORITHM: int
|
||||
LAST_VALUE_FLANN_INDEX_TYPE: int
|
||||
FlannIndexType = int
|
||||
"""One of [FLANN_INDEX_TYPE_8U, FLANN_INDEX_TYPE_8S, FLANN_INDEX_TYPE_16U, FLANN_INDEX_TYPE_16S, FLANN_INDEX_TYPE_32S, FLANN_INDEX_TYPE_32F, FLANN_INDEX_TYPE_64F, FLANN_INDEX_TYPE_STRING, FLANN_INDEX_TYPE_BOOL, FLANN_INDEX_TYPE_ALGORITHM, LAST_VALUE_FLANN_INDEX_TYPE]"""
|
||||
|
||||
|
||||
|
||||
# Classes
|
||||
class Index:
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def __init__(self) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, features: cv2.typing.MatLike, params: cv2.typing.IndexParams, distType: int = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def __init__(self, features: cv2.UMat, params: cv2.typing.IndexParams, distType: int = ...) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def build(self, features: cv2.typing.MatLike, params: cv2.typing.IndexParams, distType: int = ...) -> None: ...
|
||||
@_typing.overload
|
||||
def build(self, features: cv2.UMat, params: cv2.typing.IndexParams, distType: int = ...) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def knnSearch(self, query: cv2.typing.MatLike, knn: int, indices: cv2.typing.MatLike | None = ..., dists: cv2.typing.MatLike | None = ..., params: cv2.typing.SearchParams = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def knnSearch(self, query: cv2.UMat, knn: int, indices: cv2.UMat | None = ..., dists: cv2.UMat | None = ..., params: cv2.typing.SearchParams = ...) -> tuple[cv2.UMat, cv2.UMat]: ...
|
||||
|
||||
@_typing.overload
|
||||
def radiusSearch(self, query: cv2.typing.MatLike, radius: float, maxResults: int, indices: cv2.typing.MatLike | None = ..., dists: cv2.typing.MatLike | None = ..., params: cv2.typing.SearchParams = ...) -> tuple[int, cv2.typing.MatLike, cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def radiusSearch(self, query: cv2.UMat, radius: float, maxResults: int, indices: cv2.UMat | None = ..., dists: cv2.UMat | None = ..., params: cv2.typing.SearchParams = ...) -> tuple[int, cv2.UMat, cv2.UMat]: ...
|
||||
|
||||
def save(self, filename: str | os.PathLike[str]) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def load(self, features: cv2.typing.MatLike, filename: str | os.PathLike[str]) -> bool: ...
|
||||
@_typing.overload
|
||||
def load(self, features: cv2.UMat, filename: str | os.PathLike[str]) -> bool: ...
|
||||
|
||||
def release(self) -> None: ...
|
||||
|
||||
def getDistance(self) -> int: ...
|
||||
|
||||
def getAlgorithm(self) -> int: ...
|
||||
|
||||
|
||||
|
||||
@@ -0,0 +1,24 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
# Enumerations
|
||||
TYPE_GENERAL: int
|
||||
TYPE_MARKER: int
|
||||
TYPE_WRAPPER: int
|
||||
TYPE_FUN: int
|
||||
TYPE = int
|
||||
"""One of [TYPE_GENERAL, TYPE_MARKER, TYPE_WRAPPER, TYPE_FUN]"""
|
||||
|
||||
IMPL_PLAIN: int
|
||||
IMPL_IPP: int
|
||||
IMPL_OPENCL: int
|
||||
IMPL = int
|
||||
"""One of [IMPL_PLAIN, IMPL_IPP, IMPL_OPENCL]"""
|
||||
|
||||
FLAGS_NONE: int
|
||||
FLAGS_MAPPING: int
|
||||
FLAGS_EXPAND_SAME_NAMES: int
|
||||
FLAGS = int
|
||||
"""One of [FLAGS_NONE, FLAGS_MAPPING, FLAGS_EXPAND_SAME_NAMES]"""
|
||||
|
||||
|
||||
|
||||
+14
@@ -0,0 +1,14 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
# Functions
|
||||
def getIppVersion() -> str: ...
|
||||
|
||||
def setUseIPP(flag: bool) -> None: ...
|
||||
|
||||
def setUseIPP_NotExact(flag: bool) -> None: ...
|
||||
|
||||
def useIPP() -> bool: ...
|
||||
|
||||
def useIPP_NotExact() -> bool: ...
|
||||
|
||||
|
||||
@@ -0,0 +1,6 @@
|
||||
# flake8: noqa
|
||||
import sys
|
||||
|
||||
if sys.version_info[:2] < (3, 0):
|
||||
def exec_file_wrapper(fpath, g_vars, l_vars):
|
||||
execfile(fpath, g_vars, l_vars)
|
||||
@@ -0,0 +1,9 @@
|
||||
# flake8: noqa
|
||||
import os
|
||||
import sys
|
||||
|
||||
if sys.version_info[:2] >= (3, 0):
|
||||
def exec_file_wrapper(fpath, g_vars, l_vars):
|
||||
with open(fpath) as f:
|
||||
code = compile(f.read(), fpath, 'exec')
|
||||
exec(code, g_vars, l_vars)
|
||||
@@ -0,0 +1,40 @@
|
||||
__all__ = []
|
||||
|
||||
import numpy as np
|
||||
import cv2 as cv
|
||||
from typing import TYPE_CHECKING, Any
|
||||
|
||||
# Same as cv2.typing.NumPyArrayNumeric, but avoids circular dependencies
|
||||
if TYPE_CHECKING:
|
||||
_NumPyArrayNumeric = np.ndarray[Any, np.dtype[np.integer[Any] | np.floating[Any]]]
|
||||
else:
|
||||
_NumPyArrayNumeric = np.ndarray
|
||||
|
||||
# NumPy documentation: https://numpy.org/doc/stable/user/basics.subclassing.html
|
||||
|
||||
|
||||
class Mat(_NumPyArrayNumeric):
|
||||
'''
|
||||
cv.Mat wrapper for numpy array.
|
||||
|
||||
Stores extra metadata information how to interpret and process of numpy array for underlying C++ code.
|
||||
'''
|
||||
|
||||
def __new__(cls, arr, **kwargs):
|
||||
obj = arr.view(Mat)
|
||||
return obj
|
||||
|
||||
def __init__(self, arr, **kwargs):
|
||||
self.wrap_channels = kwargs.pop('wrap_channels', getattr(arr, 'wrap_channels', False))
|
||||
if len(kwargs) > 0:
|
||||
raise TypeError('Unknown parameters: {}'.format(repr(kwargs)))
|
||||
|
||||
def __array_finalize__(self, obj):
|
||||
if obj is None:
|
||||
return
|
||||
self.wrap_channels = getattr(obj, 'wrap_channels', None)
|
||||
|
||||
|
||||
Mat.__module__ = cv.__name__
|
||||
cv.Mat = Mat
|
||||
cv._registerMatType(Mat)
|
||||
BIN
Binary file not shown.
+118
@@ -0,0 +1,118 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
import cv2
|
||||
import cv2.dnn
|
||||
import cv2.typing
|
||||
import typing as _typing
|
||||
|
||||
|
||||
# Enumerations
|
||||
MCC24: int
|
||||
SG140: int
|
||||
VINYL18: int
|
||||
ColorChart = int
|
||||
"""One of [MCC24, SG140, VINYL18]"""
|
||||
|
||||
|
||||
|
||||
# Classes
|
||||
class CChecker(cv2.Algorithm):
|
||||
# Functions
|
||||
@classmethod
|
||||
def create(cls) -> CChecker: ...
|
||||
|
||||
def setTarget(self, _target: ColorChart) -> None: ...
|
||||
|
||||
def setBox(self, _box: _typing.Sequence[cv2.typing.Point2f]) -> None: ...
|
||||
|
||||
def setChartsRGB(self, _chartsRGB: cv2.typing.MatLike) -> None: ...
|
||||
|
||||
def setChartsYCbCr(self, _chartsYCbCr: cv2.typing.MatLike) -> None: ...
|
||||
|
||||
def setCost(self, _cost: float) -> None: ...
|
||||
|
||||
def setCenter(self, _center: cv2.typing.Point2f) -> None: ...
|
||||
|
||||
def getTarget(self) -> ColorChart: ...
|
||||
|
||||
def getBox(self) -> _typing.Sequence[cv2.typing.Point2f]: ...
|
||||
|
||||
def getColorCharts(self) -> _typing.Sequence[cv2.typing.Point2f]: ...
|
||||
|
||||
def getChartsRGB(self, getStats: bool = ...) -> cv2.typing.MatLike: ...
|
||||
|
||||
def getChartsYCbCr(self) -> cv2.typing.MatLike: ...
|
||||
|
||||
def getCost(self) -> float: ...
|
||||
|
||||
def getCenter(self) -> cv2.typing.Point2f: ...
|
||||
|
||||
|
||||
class DetectorParametersMCC:
|
||||
adaptiveThreshWinSizeMin: int
|
||||
adaptiveThreshWinSizeMax: int
|
||||
adaptiveThreshWinSizeStep: int
|
||||
adaptiveThreshConstant: float
|
||||
minContoursAreaRate: float
|
||||
minContoursArea: float
|
||||
confidenceThreshold: float
|
||||
minContourSolidity: float
|
||||
findCandidatesApproxPolyDPEpsMultiplier: float
|
||||
borderWidth: int
|
||||
B0factor: float
|
||||
maxError: float
|
||||
minContourPointsAllowed: int
|
||||
minContourLengthAllowed: int
|
||||
minInterContourDistance: int
|
||||
minInterCheckerDistance: int
|
||||
minImageSize: int
|
||||
minGroupSize: int
|
||||
|
||||
# Functions
|
||||
def __init__(self) -> None: ...
|
||||
|
||||
|
||||
class CCheckerDetector(cv2.Algorithm):
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def processWithROI(self, image: cv2.typing.MatLike, regionsOfInterest: _typing.Sequence[cv2.typing.Rect], nc: int = ...) -> bool: ...
|
||||
@_typing.overload
|
||||
def processWithROI(self, image: cv2.UMat, regionsOfInterest: _typing.Sequence[cv2.typing.Rect], nc: int = ...) -> bool: ...
|
||||
|
||||
@_typing.overload
|
||||
def process(self, image: cv2.typing.MatLike, nc: int = ...) -> bool: ...
|
||||
@_typing.overload
|
||||
def process(self, image: cv2.UMat, nc: int = ...) -> bool: ...
|
||||
|
||||
def getBestColorChecker(self) -> CChecker: ...
|
||||
|
||||
def getListColorChecker(self) -> _typing.Sequence[CChecker]: ...
|
||||
|
||||
@classmethod
|
||||
@_typing.overload
|
||||
def create(cls) -> CCheckerDetector: ...
|
||||
@classmethod
|
||||
@_typing.overload
|
||||
def create(cls, net: cv2.dnn.Net) -> CCheckerDetector: ...
|
||||
|
||||
@_typing.overload
|
||||
def draw(self, checkers: _typing.Sequence[CChecker], img: cv2.typing.MatLike, color: cv2.typing.Scalar = ..., thickness: int = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def draw(self, checkers: _typing.Sequence[CChecker], img: cv2.UMat, color: cv2.typing.Scalar = ..., thickness: int = ...) -> cv2.UMat: ...
|
||||
|
||||
def getRefColors(self) -> cv2.typing.MatLike: ...
|
||||
|
||||
def setDetectionParams(self, params: DetectorParametersMCC) -> None: ...
|
||||
|
||||
def setColorChartType(self, chartType: ColorChart) -> None: ...
|
||||
|
||||
def setUseDnnModel(self, useDnn: bool) -> None: ...
|
||||
|
||||
def getUseDnnModel(self) -> bool: ...
|
||||
|
||||
def getDetectionParams(self) -> DetectorParametersMCC: ...
|
||||
|
||||
def getColorChartType(self) -> ColorChart: ...
|
||||
|
||||
|
||||
|
||||
@@ -0,0 +1 @@
|
||||
from .version import get_ocv_version
|
||||
BIN
Binary file not shown.
BIN
Binary file not shown.
@@ -0,0 +1,5 @@
|
||||
import cv2
|
||||
|
||||
|
||||
def get_ocv_version():
|
||||
return getattr(cv2, "__version__", "unavailable")
|
||||
+252
@@ -0,0 +1,252 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
# Enumerations
|
||||
OCL_VECTOR_OWN: int
|
||||
OCL_VECTOR_MAX: int
|
||||
OCL_VECTOR_DEFAULT: int
|
||||
OclVectorStrategy = int
|
||||
"""One of [OCL_VECTOR_OWN, OCL_VECTOR_MAX, OCL_VECTOR_DEFAULT]"""
|
||||
|
||||
|
||||
Device_TYPE_DEFAULT: int
|
||||
DEVICE_TYPE_DEFAULT: int
|
||||
Device_TYPE_CPU: int
|
||||
DEVICE_TYPE_CPU: int
|
||||
Device_TYPE_GPU: int
|
||||
DEVICE_TYPE_GPU: int
|
||||
Device_TYPE_ACCELERATOR: int
|
||||
DEVICE_TYPE_ACCELERATOR: int
|
||||
Device_TYPE_DGPU: int
|
||||
DEVICE_TYPE_DGPU: int
|
||||
Device_TYPE_IGPU: int
|
||||
DEVICE_TYPE_IGPU: int
|
||||
Device_TYPE_ALL: int
|
||||
DEVICE_TYPE_ALL: int
|
||||
Device_FP_DENORM: int
|
||||
DEVICE_FP_DENORM: int
|
||||
Device_FP_INF_NAN: int
|
||||
DEVICE_FP_INF_NAN: int
|
||||
Device_FP_ROUND_TO_NEAREST: int
|
||||
DEVICE_FP_ROUND_TO_NEAREST: int
|
||||
Device_FP_ROUND_TO_ZERO: int
|
||||
DEVICE_FP_ROUND_TO_ZERO: int
|
||||
Device_FP_ROUND_TO_INF: int
|
||||
DEVICE_FP_ROUND_TO_INF: int
|
||||
Device_FP_FMA: int
|
||||
DEVICE_FP_FMA: int
|
||||
Device_FP_SOFT_FLOAT: int
|
||||
DEVICE_FP_SOFT_FLOAT: int
|
||||
Device_FP_CORRECTLY_ROUNDED_DIVIDE_SQRT: int
|
||||
DEVICE_FP_CORRECTLY_ROUNDED_DIVIDE_SQRT: int
|
||||
Device_EXEC_KERNEL: int
|
||||
DEVICE_EXEC_KERNEL: int
|
||||
Device_EXEC_NATIVE_KERNEL: int
|
||||
DEVICE_EXEC_NATIVE_KERNEL: int
|
||||
Device_NO_CACHE: int
|
||||
DEVICE_NO_CACHE: int
|
||||
Device_READ_ONLY_CACHE: int
|
||||
DEVICE_READ_ONLY_CACHE: int
|
||||
Device_READ_WRITE_CACHE: int
|
||||
DEVICE_READ_WRITE_CACHE: int
|
||||
Device_NO_LOCAL_MEM: int
|
||||
DEVICE_NO_LOCAL_MEM: int
|
||||
Device_LOCAL_IS_LOCAL: int
|
||||
DEVICE_LOCAL_IS_LOCAL: int
|
||||
Device_LOCAL_IS_GLOBAL: int
|
||||
DEVICE_LOCAL_IS_GLOBAL: int
|
||||
Device_UNKNOWN_VENDOR: int
|
||||
DEVICE_UNKNOWN_VENDOR: int
|
||||
Device_VENDOR_AMD: int
|
||||
DEVICE_VENDOR_AMD: int
|
||||
Device_VENDOR_INTEL: int
|
||||
DEVICE_VENDOR_INTEL: int
|
||||
Device_VENDOR_NVIDIA: int
|
||||
DEVICE_VENDOR_NVIDIA: int
|
||||
|
||||
KernelArg_LOCAL: int
|
||||
KERNEL_ARG_LOCAL: int
|
||||
KernelArg_READ_ONLY: int
|
||||
KERNEL_ARG_READ_ONLY: int
|
||||
KernelArg_WRITE_ONLY: int
|
||||
KERNEL_ARG_WRITE_ONLY: int
|
||||
KernelArg_READ_WRITE: int
|
||||
KERNEL_ARG_READ_WRITE: int
|
||||
KernelArg_CONSTANT: int
|
||||
KERNEL_ARG_CONSTANT: int
|
||||
KernelArg_PTR_ONLY: int
|
||||
KERNEL_ARG_PTR_ONLY: int
|
||||
KernelArg_NO_SIZE: int
|
||||
KERNEL_ARG_NO_SIZE: int
|
||||
|
||||
|
||||
# Classes
|
||||
class Device:
|
||||
# Functions
|
||||
def __init__(self) -> None: ...
|
||||
|
||||
def name(self) -> str: ...
|
||||
|
||||
def extensions(self) -> str: ...
|
||||
|
||||
def isExtensionSupported(self, extensionName: str) -> bool: ...
|
||||
|
||||
def version(self) -> str: ...
|
||||
|
||||
def vendorName(self) -> str: ...
|
||||
|
||||
def OpenCL_C_Version(self) -> str: ...
|
||||
|
||||
def OpenCLVersion(self) -> str: ...
|
||||
|
||||
def deviceVersionMajor(self) -> int: ...
|
||||
|
||||
def deviceVersionMinor(self) -> int: ...
|
||||
|
||||
def driverVersion(self) -> str: ...
|
||||
|
||||
def type(self) -> int: ...
|
||||
|
||||
def addressBits(self) -> int: ...
|
||||
|
||||
def available(self) -> bool: ...
|
||||
|
||||
def compilerAvailable(self) -> bool: ...
|
||||
|
||||
def linkerAvailable(self) -> bool: ...
|
||||
|
||||
def doubleFPConfig(self) -> int: ...
|
||||
|
||||
def singleFPConfig(self) -> int: ...
|
||||
|
||||
def halfFPConfig(self) -> int: ...
|
||||
|
||||
def hasFP64(self) -> bool: ...
|
||||
|
||||
def hasFP16(self) -> bool: ...
|
||||
|
||||
def endianLittle(self) -> bool: ...
|
||||
|
||||
def errorCorrectionSupport(self) -> bool: ...
|
||||
|
||||
def executionCapabilities(self) -> int: ...
|
||||
|
||||
def globalMemCacheSize(self) -> int: ...
|
||||
|
||||
def globalMemCacheType(self) -> int: ...
|
||||
|
||||
def globalMemCacheLineSize(self) -> int: ...
|
||||
|
||||
def globalMemSize(self) -> int: ...
|
||||
|
||||
def localMemSize(self) -> int: ...
|
||||
|
||||
def localMemType(self) -> int: ...
|
||||
|
||||
def hostUnifiedMemory(self) -> bool: ...
|
||||
|
||||
def imageSupport(self) -> bool: ...
|
||||
|
||||
def imageFromBufferSupport(self) -> bool: ...
|
||||
|
||||
def intelSubgroupsSupport(self) -> bool: ...
|
||||
|
||||
def image2DMaxWidth(self) -> int: ...
|
||||
|
||||
def image2DMaxHeight(self) -> int: ...
|
||||
|
||||
def image3DMaxWidth(self) -> int: ...
|
||||
|
||||
def image3DMaxHeight(self) -> int: ...
|
||||
|
||||
def image3DMaxDepth(self) -> int: ...
|
||||
|
||||
def imageMaxBufferSize(self) -> int: ...
|
||||
|
||||
def imageMaxArraySize(self) -> int: ...
|
||||
|
||||
def vendorID(self) -> int: ...
|
||||
|
||||
def isAMD(self) -> bool: ...
|
||||
|
||||
def isIntel(self) -> bool: ...
|
||||
|
||||
def isNVidia(self) -> bool: ...
|
||||
|
||||
def maxClockFrequency(self) -> int: ...
|
||||
|
||||
def maxComputeUnits(self) -> int: ...
|
||||
|
||||
def maxConstantArgs(self) -> int: ...
|
||||
|
||||
def maxConstantBufferSize(self) -> int: ...
|
||||
|
||||
def maxMemAllocSize(self) -> int: ...
|
||||
|
||||
def maxParameterSize(self) -> int: ...
|
||||
|
||||
def maxReadImageArgs(self) -> int: ...
|
||||
|
||||
def maxWriteImageArgs(self) -> int: ...
|
||||
|
||||
def maxSamplers(self) -> int: ...
|
||||
|
||||
def maxWorkGroupSize(self) -> int: ...
|
||||
|
||||
def maxWorkItemDims(self) -> int: ...
|
||||
|
||||
def memBaseAddrAlign(self) -> int: ...
|
||||
|
||||
def nativeVectorWidthChar(self) -> int: ...
|
||||
|
||||
def nativeVectorWidthShort(self) -> int: ...
|
||||
|
||||
def nativeVectorWidthInt(self) -> int: ...
|
||||
|
||||
def nativeVectorWidthLong(self) -> int: ...
|
||||
|
||||
def nativeVectorWidthFloat(self) -> int: ...
|
||||
|
||||
def nativeVectorWidthDouble(self) -> int: ...
|
||||
|
||||
def nativeVectorWidthHalf(self) -> int: ...
|
||||
|
||||
def preferredVectorWidthChar(self) -> int: ...
|
||||
|
||||
def preferredVectorWidthShort(self) -> int: ...
|
||||
|
||||
def preferredVectorWidthInt(self) -> int: ...
|
||||
|
||||
def preferredVectorWidthLong(self) -> int: ...
|
||||
|
||||
def preferredVectorWidthFloat(self) -> int: ...
|
||||
|
||||
def preferredVectorWidthDouble(self) -> int: ...
|
||||
|
||||
def preferredVectorWidthHalf(self) -> int: ...
|
||||
|
||||
def printfBufferSize(self) -> int: ...
|
||||
|
||||
def profilingTimerResolution(self) -> int: ...
|
||||
|
||||
@classmethod
|
||||
def getDefault(cls) -> Device: ...
|
||||
|
||||
|
||||
class OpenCLExecutionContext:
|
||||
...
|
||||
|
||||
|
||||
# Functions
|
||||
def finish() -> None: ...
|
||||
|
||||
def haveAmdBlas() -> bool: ...
|
||||
|
||||
def haveAmdFft() -> bool: ...
|
||||
|
||||
def haveOpenCL() -> bool: ...
|
||||
|
||||
def setUseOpenCL(flag: bool) -> None: ...
|
||||
|
||||
def useOpenCL() -> bool: ...
|
||||
|
||||
|
||||
+51
@@ -0,0 +1,51 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
# Enumerations
|
||||
POINTS: int
|
||||
LINES: int
|
||||
LINE_LOOP: int
|
||||
LINE_STRIP: int
|
||||
TRIANGLES: int
|
||||
TRIANGLE_STRIP: int
|
||||
TRIANGLE_FAN: int
|
||||
QUADS: int
|
||||
QUAD_STRIP: int
|
||||
POLYGON: int
|
||||
RenderModes = int
|
||||
"""One of [POINTS, LINES, LINE_LOOP, LINE_STRIP, TRIANGLES, TRIANGLE_STRIP, TRIANGLE_FAN, QUADS, QUAD_STRIP, POLYGON]"""
|
||||
|
||||
|
||||
Buffer_ARRAY_BUFFER: int
|
||||
BUFFER_ARRAY_BUFFER: int
|
||||
Buffer_ELEMENT_ARRAY_BUFFER: int
|
||||
BUFFER_ELEMENT_ARRAY_BUFFER: int
|
||||
Buffer_PIXEL_PACK_BUFFER: int
|
||||
BUFFER_PIXEL_PACK_BUFFER: int
|
||||
Buffer_PIXEL_UNPACK_BUFFER: int
|
||||
BUFFER_PIXEL_UNPACK_BUFFER: int
|
||||
Buffer_Target = int
|
||||
"""One of [Buffer_ARRAY_BUFFER, BUFFER_ARRAY_BUFFER, Buffer_ELEMENT_ARRAY_BUFFER, BUFFER_ELEMENT_ARRAY_BUFFER, Buffer_PIXEL_PACK_BUFFER, BUFFER_PIXEL_PACK_BUFFER, Buffer_PIXEL_UNPACK_BUFFER, BUFFER_PIXEL_UNPACK_BUFFER]"""
|
||||
|
||||
Buffer_READ_ONLY: int
|
||||
BUFFER_READ_ONLY: int
|
||||
Buffer_WRITE_ONLY: int
|
||||
BUFFER_WRITE_ONLY: int
|
||||
Buffer_READ_WRITE: int
|
||||
BUFFER_READ_WRITE: int
|
||||
Buffer_Access = int
|
||||
"""One of [Buffer_READ_ONLY, BUFFER_READ_ONLY, Buffer_WRITE_ONLY, BUFFER_WRITE_ONLY, Buffer_READ_WRITE, BUFFER_READ_WRITE]"""
|
||||
|
||||
Texture2D_NONE: int
|
||||
TEXTURE2D_NONE: int
|
||||
Texture2D_DEPTH_COMPONENT: int
|
||||
TEXTURE2D_DEPTH_COMPONENT: int
|
||||
Texture2D_RGB: int
|
||||
TEXTURE2D_RGB: int
|
||||
Texture2D_RGBA: int
|
||||
TEXTURE2D_RGBA: int
|
||||
Texture2D_Format = int
|
||||
"""One of [Texture2D_NONE, TEXTURE2D_NONE, Texture2D_DEPTH_COMPONENT, TEXTURE2D_DEPTH_COMPONENT, Texture2D_RGB, TEXTURE2D_RGB, Texture2D_RGBA, TEXTURE2D_RGBA]"""
|
||||
|
||||
|
||||
# Classes
|
||||
|
||||
@@ -0,0 +1,6 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
# Functions
|
||||
def setParallelForBackend(backendName: str, propagateNumThreads: bool = ...) -> bool: ...
|
||||
|
||||
|
||||
Binary file not shown.
@@ -0,0 +1,12 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
# Functions
|
||||
def addSamplesDataSearchPath(path: str) -> None: ...
|
||||
|
||||
def addSamplesDataSearchSubDirectory(subdir: str) -> None: ...
|
||||
|
||||
def findFile(relative_path: str, required: bool = ..., silentMode: bool = ...) -> str: ...
|
||||
|
||||
def findFileOrKeep(relative_path: str, silentMode: bool = ...) -> str: ...
|
||||
|
||||
|
||||
@@ -0,0 +1,39 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
import cv2
|
||||
import cv2.typing
|
||||
import typing as _typing
|
||||
|
||||
|
||||
# Classes
|
||||
class IntelligentScissorsMB:
|
||||
# Functions
|
||||
def __init__(self) -> None: ...
|
||||
|
||||
def setWeights(self, weight_non_edge: float, weight_gradient_direction: float, weight_gradient_magnitude: float) -> IntelligentScissorsMB: ...
|
||||
|
||||
def setGradientMagnitudeMaxLimit(self, gradient_magnitude_threshold_max: float = ...) -> IntelligentScissorsMB: ...
|
||||
|
||||
def setEdgeFeatureZeroCrossingParameters(self, gradient_magnitude_min_value: float = ...) -> IntelligentScissorsMB: ...
|
||||
|
||||
def setEdgeFeatureCannyParameters(self, threshold1: float, threshold2: float, apertureSize: int = ..., L2gradient: bool = ...) -> IntelligentScissorsMB: ...
|
||||
|
||||
@_typing.overload
|
||||
def applyImage(self, image: cv2.typing.MatLike) -> IntelligentScissorsMB: ...
|
||||
@_typing.overload
|
||||
def applyImage(self, image: cv2.UMat) -> IntelligentScissorsMB: ...
|
||||
|
||||
@_typing.overload
|
||||
def applyImageFeatures(self, non_edge: cv2.typing.MatLike, gradient_direction: cv2.typing.MatLike, gradient_magnitude: cv2.typing.MatLike, image: cv2.typing.MatLike | None = ...) -> IntelligentScissorsMB: ...
|
||||
@_typing.overload
|
||||
def applyImageFeatures(self, non_edge: cv2.UMat, gradient_direction: cv2.UMat, gradient_magnitude: cv2.UMat, image: cv2.UMat | None = ...) -> IntelligentScissorsMB: ...
|
||||
|
||||
def buildMap(self, sourcePt: cv2.typing.Point) -> None: ...
|
||||
|
||||
@_typing.overload
|
||||
def getContour(self, targetPt: cv2.typing.Point, contour: cv2.typing.MatLike | None = ..., backward: bool = ...) -> cv2.typing.MatLike: ...
|
||||
@_typing.overload
|
||||
def getContour(self, targetPt: cv2.typing.Point, contour: cv2.UMat | None = ..., backward: bool = ...) -> cv2.UMat: ...
|
||||
|
||||
|
||||
|
||||
+159
@@ -0,0 +1,159 @@
|
||||
__all__ = [
|
||||
"IntPointer",
|
||||
"MatLike",
|
||||
"MatShape",
|
||||
"Size",
|
||||
"Size2f",
|
||||
"Scalar",
|
||||
"Point",
|
||||
"Point2i",
|
||||
"Point2f",
|
||||
"Point2d",
|
||||
"Point3i",
|
||||
"Point3f",
|
||||
"Point3d",
|
||||
"Range",
|
||||
"Rect",
|
||||
"Rect2i",
|
||||
"Rect2f",
|
||||
"Rect2d",
|
||||
"Moments",
|
||||
"RotatedRect",
|
||||
"TermCriteria",
|
||||
"Vec2i",
|
||||
"Vec2f",
|
||||
"Vec2d",
|
||||
"Vec3i",
|
||||
"Vec3f",
|
||||
"Vec3d",
|
||||
"Vec4i",
|
||||
"Vec4f",
|
||||
"Vec4d",
|
||||
"Vec6f",
|
||||
"FeatureDetector",
|
||||
"DescriptorExtractor",
|
||||
"FeatureExtractor",
|
||||
"Matx33f",
|
||||
"Matx33d",
|
||||
"Matx44f",
|
||||
"Matx44d",
|
||||
"LayerId",
|
||||
"LayerParams",
|
||||
"IndexParams",
|
||||
"SearchParams",
|
||||
"map_string_and_string",
|
||||
"map_string_and_int",
|
||||
"map_string_and_vector_size_t",
|
||||
"map_string_and_vector_float",
|
||||
"map_int_and_double",
|
||||
]
|
||||
|
||||
import cv2.dnn
|
||||
import cv2.mat_wrapper
|
||||
import cv2
|
||||
import numpy
|
||||
import typing as _typing
|
||||
|
||||
|
||||
if _typing.TYPE_CHECKING:
|
||||
NumPyArrayNumeric = numpy.ndarray[_typing.Any, numpy.dtype[numpy.integer[_typing.Any] | numpy.floating[_typing.Any]]]
|
||||
else:
|
||||
NumPyArrayNumeric = numpy.ndarray
|
||||
|
||||
|
||||
if _typing.TYPE_CHECKING:
|
||||
NumPyArrayFloat32 = numpy.ndarray[_typing.Any, numpy.dtype[numpy.float32]]
|
||||
else:
|
||||
NumPyArrayFloat32 = numpy.ndarray
|
||||
|
||||
|
||||
if _typing.TYPE_CHECKING:
|
||||
NumPyArrayFloat64 = numpy.ndarray[_typing.Any, numpy.dtype[numpy.float64]]
|
||||
else:
|
||||
NumPyArrayFloat64 = numpy.ndarray
|
||||
|
||||
|
||||
if _typing.TYPE_CHECKING:
|
||||
TermCriteria_Type = cv2.TermCriteria_Type
|
||||
else:
|
||||
TermCriteria_Type = int
|
||||
|
||||
|
||||
IntPointer = int
|
||||
"""Represents an arbitrary pointer"""
|
||||
MatLike = _typing.Union[cv2.mat_wrapper.Mat, NumPyArrayNumeric]
|
||||
MatShape = _typing.Sequence[int]
|
||||
Size = _typing.Sequence[int]
|
||||
"""Required length is 2"""
|
||||
Size2f = _typing.Sequence[float]
|
||||
"""Required length is 2"""
|
||||
Scalar = _typing.Union[_typing.Sequence[float], float]
|
||||
"""Max sequence length is at most 4"""
|
||||
Point = _typing.Sequence[int]
|
||||
"""Required length is 2"""
|
||||
Point2i = Point
|
||||
Point2f = _typing.Sequence[float]
|
||||
"""Required length is 2"""
|
||||
Point2d = _typing.Sequence[float]
|
||||
"""Required length is 2"""
|
||||
Point3i = _typing.Sequence[int]
|
||||
"""Required length is 3"""
|
||||
Point3f = _typing.Sequence[float]
|
||||
"""Required length is 3"""
|
||||
Point3d = _typing.Sequence[float]
|
||||
"""Required length is 3"""
|
||||
Range = _typing.Sequence[int]
|
||||
"""Required length is 2"""
|
||||
Rect = _typing.Sequence[int]
|
||||
"""Required length is 4"""
|
||||
Rect2i = _typing.Sequence[int]
|
||||
"""Required length is 4"""
|
||||
Rect2f = _typing.Sequence[float]
|
||||
"""Required length is 4"""
|
||||
Rect2d = _typing.Sequence[float]
|
||||
"""Required length is 4"""
|
||||
Moments = _typing.Dict[str, float]
|
||||
RotatedRect = _typing.Tuple[Point2f, Size2f, float]
|
||||
"""Any type providing sequence protocol is supported"""
|
||||
TermCriteria = _typing.Tuple[TermCriteria_Type, int, float]
|
||||
"""Any type providing sequence protocol is supported"""
|
||||
Vec2i = _typing.Sequence[int]
|
||||
"""Required length is 2"""
|
||||
Vec2f = _typing.Sequence[float]
|
||||
"""Required length is 2"""
|
||||
Vec2d = _typing.Sequence[float]
|
||||
"""Required length is 2"""
|
||||
Vec3i = _typing.Sequence[int]
|
||||
"""Required length is 3"""
|
||||
Vec3f = _typing.Sequence[float]
|
||||
"""Required length is 3"""
|
||||
Vec3d = _typing.Sequence[float]
|
||||
"""Required length is 3"""
|
||||
Vec4i = _typing.Sequence[int]
|
||||
"""Required length is 4"""
|
||||
Vec4f = _typing.Sequence[float]
|
||||
"""Required length is 4"""
|
||||
Vec4d = _typing.Sequence[float]
|
||||
"""Required length is 4"""
|
||||
Vec6f = _typing.Sequence[float]
|
||||
"""Required length is 6"""
|
||||
FeatureDetector = cv2.Feature2D
|
||||
DescriptorExtractor = cv2.Feature2D
|
||||
FeatureExtractor = cv2.Feature2D
|
||||
Matx33f = NumPyArrayFloat32
|
||||
"""NDArray(shape=(3, 3), dtype=numpy.float32)"""
|
||||
Matx33d = NumPyArrayFloat64
|
||||
"""NDArray(shape=(3, 3), dtype=numpy.float64)"""
|
||||
Matx44f = NumPyArrayFloat32
|
||||
"""NDArray(shape=(4, 4), dtype=numpy.float32)"""
|
||||
Matx44d = NumPyArrayFloat64
|
||||
"""NDArray(shape=(4, 4), dtype=numpy.float64)"""
|
||||
LayerId = cv2.dnn.DictValue
|
||||
LayerParams = _typing.Dict[str, _typing.Union[int, float, str]]
|
||||
IndexParams = _typing.Dict[str, _typing.Union[bool, int, float, str]]
|
||||
SearchParams = _typing.Dict[str, _typing.Union[bool, int, float, str]]
|
||||
map_string_and_string = _typing.Dict[str, str]
|
||||
map_string_and_int = _typing.Dict[str, int]
|
||||
map_string_and_vector_size_t = _typing.Dict[str, _typing.Sequence[int]]
|
||||
map_string_and_vector_float = _typing.Dict[str, _typing.Sequence[float]]
|
||||
map_int_and_double = _typing.Dict[int, float]
|
||||
BIN
Binary file not shown.
+14
@@ -0,0 +1,14 @@
|
||||
from collections import namedtuple
|
||||
|
||||
import cv2
|
||||
|
||||
|
||||
NativeMethodPatchedResult = namedtuple("NativeMethodPatchedResult",
|
||||
("py", "native"))
|
||||
|
||||
|
||||
def testOverwriteNativeMethod(arg):
|
||||
return NativeMethodPatchedResult(
|
||||
arg + 1,
|
||||
cv2.utils._native.testOverwriteNativeMethod(arg)
|
||||
)
|
||||
+110
@@ -0,0 +1,110 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
import cv2
|
||||
import cv2.typing
|
||||
import typing as _typing
|
||||
|
||||
|
||||
from cv2.utils import fs as fs
|
||||
from cv2.utils import logging as logging
|
||||
from cv2.utils import nested as nested
|
||||
|
||||
|
||||
# Classes
|
||||
class ClassWithKeywordProperties:
|
||||
lambda_: int
|
||||
@property
|
||||
def except_(self) -> int: ...
|
||||
|
||||
# Functions
|
||||
def __init__(self, lambda_arg: int = ..., except_arg: int = ...) -> None: ...
|
||||
|
||||
|
||||
|
||||
# Functions
|
||||
@_typing.overload
|
||||
def copyMatAndDumpNamedArguments(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., lambda_: int = ..., sigma: float = ...) -> tuple[str, cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def copyMatAndDumpNamedArguments(src: cv2.UMat, dst: cv2.UMat | None = ..., lambda_: int = ..., sigma: float = ...) -> tuple[str, cv2.UMat]: ...
|
||||
|
||||
def dumpBool(argument: bool) -> str: ...
|
||||
|
||||
def dumpCString(argument: str) -> str: ...
|
||||
|
||||
def dumpDouble(argument: float) -> str: ...
|
||||
|
||||
def dumpFloat(argument: float) -> str: ...
|
||||
|
||||
@_typing.overload
|
||||
def dumpInputArray(argument: cv2.typing.MatLike) -> str: ...
|
||||
@_typing.overload
|
||||
def dumpInputArray(argument: cv2.UMat) -> str: ...
|
||||
|
||||
@_typing.overload
|
||||
def dumpInputArrayOfArrays(argument: _typing.Sequence[cv2.typing.MatLike]) -> str: ...
|
||||
@_typing.overload
|
||||
def dumpInputArrayOfArrays(argument: _typing.Sequence[cv2.UMat]) -> str: ...
|
||||
|
||||
@_typing.overload
|
||||
def dumpInputOutputArray(argument: cv2.typing.MatLike) -> tuple[str, cv2.typing.MatLike]: ...
|
||||
@_typing.overload
|
||||
def dumpInputOutputArray(argument: cv2.UMat) -> tuple[str, cv2.UMat]: ...
|
||||
|
||||
@_typing.overload
|
||||
def dumpInputOutputArrayOfArrays(argument: _typing.Sequence[cv2.typing.MatLike]) -> tuple[str, _typing.Sequence[cv2.typing.MatLike]]: ...
|
||||
@_typing.overload
|
||||
def dumpInputOutputArrayOfArrays(argument: _typing.Sequence[cv2.UMat]) -> tuple[str, _typing.Sequence[cv2.UMat]]: ...
|
||||
|
||||
def dumpInt(argument: int) -> str: ...
|
||||
|
||||
def dumpInt64(argument: int) -> str: ...
|
||||
|
||||
def dumpRange(argument: cv2.typing.Range) -> str: ...
|
||||
|
||||
def dumpRect(argument: cv2.typing.Rect) -> str: ...
|
||||
|
||||
def dumpRotatedRect(argument: cv2.typing.RotatedRect) -> str: ...
|
||||
|
||||
def dumpSizeT(argument: int) -> str: ...
|
||||
|
||||
def dumpString(argument: str) -> str: ...
|
||||
|
||||
def dumpTermCriteria(argument: cv2.typing.TermCriteria) -> str: ...
|
||||
|
||||
def dumpVec2i(value: cv2.typing.Vec2i = ...) -> str: ...
|
||||
|
||||
def dumpVectorOfDouble(vec: _typing.Sequence[float]) -> str: ...
|
||||
|
||||
def dumpVectorOfInt(vec: _typing.Sequence[int]) -> str: ...
|
||||
|
||||
def dumpVectorOfRect(vec: _typing.Sequence[cv2.typing.Rect]) -> str: ...
|
||||
|
||||
def generateVectorOfInt(len: int) -> _typing.Sequence[int]: ...
|
||||
|
||||
def generateVectorOfMat(len: int, rows: int, cols: int, dtype: int, vec: _typing.Sequence[cv2.typing.MatLike] | None = ...) -> _typing.Sequence[cv2.typing.MatLike]: ...
|
||||
|
||||
def generateVectorOfRect(len: int) -> _typing.Sequence[cv2.typing.Rect]: ...
|
||||
|
||||
@_typing.overload
|
||||
def testAsyncArray(argument: cv2.typing.MatLike) -> cv2.AsyncArray: ...
|
||||
@_typing.overload
|
||||
def testAsyncArray(argument: cv2.UMat) -> cv2.AsyncArray: ...
|
||||
|
||||
def testAsyncException() -> cv2.AsyncArray: ...
|
||||
|
||||
@_typing.overload
|
||||
def testOverloadResolution(value: int, point: cv2.typing.Point = ...) -> str: ...
|
||||
@_typing.overload
|
||||
def testOverloadResolution(rect: cv2.typing.Rect) -> str: ...
|
||||
|
||||
def testOverwriteNativeMethod(argument: int) -> int: ...
|
||||
|
||||
def testRaiseGeneralException() -> None: ...
|
||||
|
||||
def testReservedKeywordConversion(positional_argument: int, lambda_: int = ..., from_: int = ...) -> str: ...
|
||||
|
||||
def testRotatedRect(x: float, y: float, w: float, h: float, angle: float) -> cv2.typing.RotatedRect: ...
|
||||
|
||||
def testRotatedRectVector(x: float, y: float, w: float, h: float, angle: float) -> _typing.Sequence[cv2.typing.RotatedRect]: ...
|
||||
|
||||
|
||||
BIN
Binary file not shown.
@@ -0,0 +1,6 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
# Functions
|
||||
def getCacheDirectoryForDownloads() -> str: ...
|
||||
|
||||
|
||||
@@ -0,0 +1,22 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
# Enumerations
|
||||
LOG_LEVEL_SILENT: int
|
||||
LOG_LEVEL_FATAL: int
|
||||
LOG_LEVEL_ERROR: int
|
||||
LOG_LEVEL_WARNING: int
|
||||
LOG_LEVEL_INFO: int
|
||||
LOG_LEVEL_DEBUG: int
|
||||
LOG_LEVEL_VERBOSE: int
|
||||
ENUM_LOG_LEVEL_FORCE_INT: int
|
||||
LogLevel = int
|
||||
"""One of [LOG_LEVEL_SILENT, LOG_LEVEL_FATAL, LOG_LEVEL_ERROR, LOG_LEVEL_WARNING, LOG_LEVEL_INFO, LOG_LEVEL_DEBUG, LOG_LEVEL_VERBOSE, ENUM_LOG_LEVEL_FORCE_INT]"""
|
||||
|
||||
|
||||
|
||||
# Functions
|
||||
def getLogLevel() -> LogLevel: ...
|
||||
|
||||
def setLogLevel(logLevel: LogLevel) -> LogLevel: ...
|
||||
|
||||
|
||||
@@ -0,0 +1,31 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
# Classes
|
||||
class ExportClassName:
|
||||
# Classes
|
||||
class Params:
|
||||
int_value: int
|
||||
float_value: float
|
||||
|
||||
# Functions
|
||||
def __init__(self, int_param: int = ..., float_param: float = ...) -> None: ...
|
||||
|
||||
|
||||
|
||||
# Functions
|
||||
def getIntParam(self) -> int: ...
|
||||
|
||||
def getFloatParam(self) -> float: ...
|
||||
|
||||
@staticmethod
|
||||
def originalName() -> str: ...
|
||||
|
||||
@classmethod
|
||||
def create(cls, params: ExportClassName.Params = ...) -> ExportClassName: ...
|
||||
|
||||
|
||||
|
||||
# Functions
|
||||
def testEchoBooleanFunction(flag: bool) -> bool: ...
|
||||
|
||||
|
||||
+5
@@ -0,0 +1,5 @@
|
||||
opencv_version = "5.0.0.93"
|
||||
contrib = False
|
||||
headless = False
|
||||
rolling = False
|
||||
ci_build = True
|
||||
@@ -0,0 +1,31 @@
|
||||
__all__: list[str] = []
|
||||
|
||||
import cv2
|
||||
|
||||
|
||||
# Functions
|
||||
def getBackendName(api: cv2.VideoCaptureAPIs) -> str: ...
|
||||
|
||||
def getBackends() -> _typing.Sequence[cv2.VideoCaptureAPIs]: ...
|
||||
|
||||
def getCameraBackendPluginVersion(api: cv2.VideoCaptureAPIs) -> tuple[str, int, int]: ...
|
||||
|
||||
def getCameraBackends() -> _typing.Sequence[cv2.VideoCaptureAPIs]: ...
|
||||
|
||||
def getStreamBackendPluginVersion(api: cv2.VideoCaptureAPIs) -> tuple[str, int, int]: ...
|
||||
|
||||
def getStreamBackends() -> _typing.Sequence[cv2.VideoCaptureAPIs]: ...
|
||||
|
||||
def getStreamBufferedBackendPluginVersion(api: cv2.VideoCaptureAPIs) -> tuple[str, int, int]: ...
|
||||
|
||||
def getStreamBufferedBackends() -> _typing.Sequence[cv2.VideoCaptureAPIs]: ...
|
||||
|
||||
def getWriterBackendPluginVersion(api: cv2.VideoCaptureAPIs) -> tuple[str, int, int]: ...
|
||||
|
||||
def getWriterBackends() -> _typing.Sequence[cv2.VideoCaptureAPIs]: ...
|
||||
|
||||
def hasBackend(api: cv2.VideoCaptureAPIs) -> bool: ...
|
||||
|
||||
def isBackendBuiltIn(api: cv2.VideoCaptureAPIs) -> bool: ...
|
||||
|
||||
|
||||
Reference in New Issue
Block a user