#!/usr/bin/env python3 # -*- coding: utf-8 -*- from io import StringIO import re import inspect from collections import namedtuple from format_strings import FormatStrings from evision_structures import evision_structrised_classes from typing import Optional ArgTypeInfo = namedtuple('ArgTypeInfo', ['atype', 'format_str', 'default_value', 'strict_conversion', 'is_enum']) # strict_conversion is False by default ArgTypeInfo.__new__.__defaults__ = (False,) simple_argtype_mapping = { "bool": ArgTypeInfo("bool", FormatStrings.unsigned_char, "", True, False), "size_t": ArgTypeInfo("size_t", FormatStrings.unsigned_long_long, "", True, False), "int": ArgTypeInfo("int", FormatStrings.int, "", True, False), "float": ArgTypeInfo("float", FormatStrings.float, "", True, False), "double": ArgTypeInfo("double", FormatStrings.double, "", True, False), "c_string": ArgTypeInfo("char*", FormatStrings.string, '(char*)""', False, False), "string": ArgTypeInfo("std::string", FormatStrings.object, None, True, False), "Stream": ArgTypeInfo("Stream", FormatStrings.object, 'Stream::Null()', True, False), } def handle_ptr(tp): if tp.startswith('Ptr_'): tp = 'Ptr<' + "::".join(tp.split('_')[1:]) + '>' return tp def normalize_class_name(name): return re.sub(r"^cv\.", "", name).replace(".", "_") def get_type_format_string(arg_type_info): if arg_type_info.strict_conversion: return FormatStrings.object else: return arg_type_info.format_str def argsort(seq): # http://stackoverflow.com/questions/3382352/equivalent-of-numpy-argsort-in-basic-python/3383106#3383106 #lambda version by Tony Veijalainen return [x for x,y in sorted(enumerate(seq), key = lambda x: x[1])] def reserved_keywords(): # Set of reserved keywords for Erlang/Elixir. # Keywords that are reserved in C/C++ are excluded because they can not be # used as variables identifiers return [ "true", "false", "nil", "as", "def", "end", "rescue", "defmodule", "defmacro", "when", "in", "fn", "with", "of" ] def forbidden_arg_types(): return ["void*"] def ignored_arg_types(): return ["RNG*"] def io_bound_funcs(): return [ # read 'evision_cv_dnn_dnn_Net_readFromModelOptimizer_static', 'evision_cv_imread', 'evision_cv_imreadmulti', 'evision_cv_readOpticalFlow', 'evision_cv_dnn_Net_readFromModelOptimizer', 'evision_cv_dnn_readNet', 'evision_cv_dnn_readNetFromCaffe', 'evision_cv_dnn_readNetFromDarknet', 'evision_cv_dnn_readNetFromModelOptimizer', 'evision_cv_dnn_readNetFromONNX', 'evision_cv_dnn_readNetFromTensorflow', 'evision_cv_dnn_readNetFromTorch', 'evision_cv_dnn_readTensorFromONNX', 'evision_cv_dnn_readTorchBlob', # write 'evision_cv_FileStorage_writeComment', 'evision_cv_imwrite', 'evision_cv_imwritemulti', 'evision_cv_writeOpticalFlow', 'evision_cv_dnn_writeTextGraph', ] def pass_by_val_types(): return ["Point*", "Point2f*", "Rect*", "String*", "double*", "float*", "int*"] def evision_nif_prefix(): return 'evision_cv_' def special_handling_funcs(): return [ "{}{}".format(evision_nif_prefix(), name) for name in [ 'imshow', 'waitKey', 'destroyWindow', 'destroyAllWindows', 'imdecode', 'videoCapture_waitAny'] ] def handle_inline_math_escaping(text, start_pos=0): inline_docs_inline_math_re = re.compile(r'(?:.*?)\\\\f[$\[](.*?)\\\\f[$\]]', re.MULTILINE|re.DOTALL) processed = text[:start_pos] todo = text[start_pos:] if len(todo) == 0: return text inline_math_match = inline_docs_inline_math_re.match(todo) if inline_math_match: start = inline_math_match.start(1) end = inline_math_match.end(1) math_text = inline_math_match.group(1) if math_text and len(math_text) > 0: # avoid inline math `*` translating to `` when passing through markdown parser math_text = math_text.replace('*', r'\\*') # avoid inline math `_` translating to `` when passing through markdown parser math_text = math_text.replace('_', r'\\_') # avoid markdown parser trying to match inline math `[` for markdown `[]()` math_text = math_text.replace('[', r'\\[') # escape left/right curly brackets math_text = math_text.replace(r'\\{', r'\\\\{').replace(r'\\}', r'\\\\}') # avoid plus(`+`)/minus(`-`) sign translating as list when passing through markdown parser math_lines = "" for line in math_text.split("\n"): strip_line = line.lstrip() if strip_line.startswith('- '): math_lines += line.replace('- ', r'\\- ', 1) elif strip_line.startswith('+ '): math_lines += line.replace('+ ', r'\\+ ', 1) else: if line.strip() == '=': math_lines = math_lines.rstrip() math_lines += '=' else: math_lines += line math_lines += "\n" math_text = math_lines[:-1] replaced = processed + todo[:start] + math_text + todo[end:] return handle_inline_math_escaping(replaced, len(processed) + start + len(math_text) + 1) else: return text else: return text module_name_map = { "aruco": "ArUco", "barcode": "Barcode", "bgsegm": "BgSegm", "bioinspired": "Bioinspired", "ccm": "CCM", "cuda": "CUDA", "cudacodec": "CUDACodec", "colored_kinfu": "ColoredKinFu", "detail": "Detail", "dnn": "DNN", "dnn_superres": "DNNSuperRes", "DnnSuperResImpl": "DNNSuperResImpl", "dynafu": "DynaFu", "face": "Face", "flann": "Flann", "fisheye": "FishEye", "hfs": "HFS", "img_hash": "ImgHash", "kinfu": "KinFu", "large_kinfu": "LargeKinfu", "legacy": "Legacy", "linemod": "LineMod", "line_descriptor": "LineDescriptor", "mcc": "MCC", "ml": "ML", "optflow": "OptFlow", "ocl": "OCL", "plot": "Plot", "phase_unwrapping": "PhaseUnwrapping", "ppf_match_3d": "PPFMatch3D", "quality": "Quality", "rapid": "Rapid", "reg": "Reg", "rgbd": "RGBD", "saliency": "Saliency", "segmentation": "Segmentation", "stereo": "Stereo", "structured_light": "StructuredLight", "text": "Text", "utils": "Utils", "utils_fs": "UtilsFS", "videoio_registry": "VideoIORegistry", "xfeatures2d": "XFeatures2D", "ximgproc": "XImgProc", "xphoto": "XPhoto", "wechat_qrcode": "WeChatQRCode", } def make_elixir_module_names(module_name: Optional[str] = None, separated_ns: Optional[list] = None): global module_name_map if module_name is not None: return module_name_map.get(module_name, f"{module_name[0].upper()}{module_name[1:]}") if separated_ns is not None: return ".".join([module_name_map.get(n, f"{n[0].upper()}{n[1:]}") for n in separated_ns]) def get_module_func_name(module_func_name: str, is_ns: bool, full_qualified_name: str): if len(module_func_name) > 0 and not ('a' <= module_func_name[0] <= 'z'): if len(module_func_name) >= 2 and ('a' <= module_func_name[1] <= 'z'): module_func_name = module_func_name[0].lower() + module_func_name[1:] elif len(module_func_name) == 1: module_func_name = module_func_name.lower() else: mapping = { 'BFMatcher': 'bfMatcher', 'DMatch': 'dMatcher', 'HOGDescriptor': 'hogDescriptor', 'QRCodeDetector': 'qrCodeDetector', 'PSNR': 'psnr', 'LUT': 'lut', 'KAZE_create': 'kaze_create', 'ORB_create': 'orb_create', 'SIFT_create': 'sift_create', 'AKAZE_create': 'akaze_create', 'EMD': 'emd', 'PCAProject': 'pcaProject', 'PCABackProject': 'pcaBackProject', 'PCACompute': 'pcaCompute', 'PCACompute2': 'pcaCompute2', 'SVBackSubst': 'svBackSubst', 'SVDecomp': 'svdecomp', 'RQDecomp3x3': 'rqdecomp3x3', 'ECCEnabled': 'eccEnabled', 'BOWKMeansTrainer': 'bowKMeansTrainer', 'BOWImgDescriptorExtractor': 'bowImgDescriptorExtractor', 'UMat': 'uMat', 'NMSBoxes': 'nmsBoxes', 'NMSBoxesRotated': 'nmsBoxesRotated', } if module_func_name in mapping: module_func_name = mapping[module_func_name] else: if is_ns and full_qualified_name == 'cv': ignore_names = [ 'BFMatcher_BFMatcher', # OpenCV.BFMatch.bfMather 'BFMatcher_create', # OpenCV.BFMatch.create 'BOWImgDescriptorExtractor_BOWImgDescriptorExtractor', # OpenCV.BOWImgDescriptorExtractor.bowImgDescriptorExtractor 'BOWKMeansTrainer_BOWKMeansTrainer', # OpenCV.BOWKMeansTrainer.bowKMeansTrainer 'BRISK_create', # OpenCV.BRISK.create 'DMatch_DMatch', # OpenCV.DMatch.dMatcher 'DISOpticalFlow_create', # OpenCV.DISOpticalFlow.create 'GFTTDetector_create', # OpenCV.GFTTDetector.create 'HOGDescriptor_HOGDescriptor', # OpenCV.HOGDescriptor.hogDescriptor 'HOGDescriptor_getDaimlerPeopleDetector', # OpenCV.HOGDescriptor.getDaimlerPeopleDetector 'HOGDescriptor_getDefaultPeopleDetector', # OpenCV.HOGDescriptor.getDefaultPeopleDetector 'MSER_create', # OpenCV.MSER.create 'QRCodeDetector_QRCodeDetector', # OpenCV.QRCodeDetector.qrCodeDetector 'UMat_UMat', # OpenCV.UMat.uMat 'UMat_context', # OpenCV.UMat.context 'UMat_queue' # OpenCV.UMat.queue ] if module_func_name in ignore_names: return True, module_func_name module_func_name = module_func_name.lower() return False, module_func_name def when_guard(kind: str, func_guard_data: list): if kind == 'elixir': return when_guard_elixir(func_guard_data) elif kind == 'erlang': return when_guard_erlang(func_guard_data) else: print(f'warning: when_guard: unknown kind `{kind}`') return ' ' def when_guard_elixir(func_guard_data: list): when_guard = ' ' if len(func_guard_data) > 0: when_guard = ' when ' when_guard += ' and '.join(func_guard_data) + '\n ' return when_guard def when_guard_erlang(func_guard_data: list): when_guard = ' ' if len(func_guard_data) > 0: when_guard = ' when ' when_guard += ', '.join(func_guard_data) return when_guard def map_argtype_to_type(argtype: str, classname: Optional[str] = None): if len(argtype) > 0 and argtype.startswith('Ptr<') and argtype.endswith('>'): argtype = argtype[4:-1] if len(argtype) > 0 and argtype[-1] == '*': argtype = argtype[:-1] if is_int_type(argtype): return 'i' elif argtype == 'bool': return 'b' elif argtype == 'double': return 'd' elif argtype == 'float': return 'd' elif argtype == 'vector_char' or argtype == 'vector_uchar' or argtype == 'std::vector' or argtype == 'std::vector': return 'b' elif argtype == 'String' or argtype == 'c_string' or argtype == 'char' or argtype == 'string': return 'b' elif argtype[:7] == 'vector_' or argtype[:12] == 'std::vector<': return 'l' elif is_list_type(argtype): return 'l' elif is_tuple_type(argtype): return 'T' else: if is_struct(argtype, classname=classname): if argtype == 'UMat': return 'Mat' return argtype if argtype == 'Moments': return '(map)' return 't' def map_argname(kind, argname, **kwargs): if kind == 'elixir': return map_argname_elixir(argname, **kwargs) elif kind == 'erlang': return map_argname_erlang(argname, **kwargs) else: print(f'warning: map_argname: unknown kind `{kind}`') def map_argname_elixir(argname, ignore_upper_starting=False, argtype=None, from_struct=False): argname_prefix_re = re.compile(r'^[_]*') name = "" if argname in reserved_keywords(): if argname == 'fn': name = 'func' elif argname == 'end': name = 'end_arg' else: name = f'arg_{argname}' else: name = argname_prefix_re.sub('', argname) if not ignore_upper_starting: name = f"{name[0:1].lower()}{name[1:]}" if from_struct and argtype is not None: name = f"Evision.Internal.Structurise.from_struct({name})" return name def map_argname_erlang(argname, argtype=None, from_struct=False): argname_prefix_re = re.compile(r'^[_]*') name = argname_prefix_re.sub('', argname) name = f"{name[0:1].upper()}{name[1:]}" if from_struct and argtype is not None: name = f"evision_internal_structurise:from_struct({name})" return name def map_argtype_to_guard(kind, argname, argtype, classname: Optional[str] = None): if kind == 'elixir': return map_argtype_to_guard_elixir(argname, argtype, classname=classname) elif kind == 'erlang': return map_argtype_to_guard_erlang(argname, argtype, classname=classname) else: print(f'warning: map_argtype_to_guard: unknown kind `{kind}`') def is_basic_types(argtype: str): argtype = argtype.strip() if argtype.startswith("vector<"): argtype = argtype[len("vector<"):-1] return is_basic_types(argtype) return argtype in ['bool', 'float', 'double', 'string', 'void*', 'String', 'c_string'] or \ is_int_type(argtype) or is_tuple_type(argtype) def is_int_type(argtype): int_types = [ 'uchar', 'uint8_t', 'uint16_t', 'uint32_t', 'uint64_t', 'int8_t', 'int16_t', 'int32_t', 'int64_t', 'unsigned', 'int', 'size_t', 'int64', 'ORB_ScoreType', 'ORB::ScoreType', 'dnn_Backend', 'dnn_Target', 'AKAZE_DescriptorType', 'AKAZE::DescriptorType', 'KAZE_DiffusivityType', 'KAZE::DiffusivityType', 'DescriptorMatcher_MatcherType', 'AgastFeatureDetector_DetectorType', 'AgastFeatureDetector::DetectorType', 'FastFeatureDetector_DetectorType', 'FastFeatureDetector::DetectorType', 'InterpolationFlags', 'AccessFlag', 'WaveCorrectKind', 'VideoCaptureAPIs', 'flann_distance_t', 'cvflann_flann_algorithm_t', 'cvflann::flann_algorithm_t', 'cvflann_flann_distance_t', 'cvflann::flann_distance_t', 'DeviceInfo::ComputeMode', 'CorrectionLevel', 'EncodeMode', 'LocalOptimMethod', 'NeighborSearchMethod', 'SamplingMethod', 'ScoreMethod', 'HOGDescriptor_HistogramNormType', "VolumeType", "Volume", "kinfu_VolumeType", "text_decoder_mode", "cuda_ConnectedComponentsAlgorithmsTypes" ] return argtype in int_types def is_list_type(argtype): list_types = [ 'ImageFeatures', 'MatchesInfo', 'CameraParams', 'MatShape' ] if argtype[:7] == 'vector_' or argtype[len('std::vector<'):] == 'std::vector<': return True return argtype in list_types def is_tuple_type(argtype): tuple_types = [ 'Rect', 'cv::Rect', 'Rect2d', 'Rect2f', 'Rect2i', 'RotatedRect', 'cv::RotatedRect', 'TermCriteria', 'cv::TermCriteria', 'CvTermCriteria', 'CvSlice', 'cv::Point', 'Point', 'Point2i', 'Point2f', 'Point2d', 'Point3i', 'Point3f', 'Point3d', 'Size', 'Scalar', 'cv::Scalar', ] return argtype in tuple_types def is_ref_or_struct(argtype: str): ref_or_struct_types = [ 'Mat', 'UMat', 'Net', 'DMatch', 'BFMatcher', 'BOWImgDescriptorExtractor', 'BOWKMeansTrainer', 'CascadeClassifier', 'FileStorage', 'FlannBasedMatcher', 'HOGDescriptor', 'KalmanFilter', 'PyRotationWarper', 'QRCodeDetector', 'Subdiv2D', 'TickMeter', 'VideoWriter', 'BufferPool', 'DeviceInfo', 'AffineBasedEstimator', 'AffineBestOf2NearestMatcher', 'BestOf2NearestMatcher', 'BestOf2NearestRangeMatcher', 'BlocksGainCompensator', 'BundleAdjusterAffine', 'BundleAdjusterAffinePartial', 'BundleAdjusterRay', 'BundleAdjusterReproj', 'ChannelsCompensator', 'DpSeamFinder', 'FeatherBlender', 'GainCompensator', 'GraphCutSeamFinder', 'HomographyBasedEstimator', 'MultiBandBlender', 'NoBundleAdjuster', 'DictValue', 'KeypointsModel', 'SegmentationModel', 'BlocksChannelsCompensator', 'QRCodeEncoder_Params', 'SimpleBlobDetector_Params', 'TrackerDaSiamRPN_Params', 'TrackerGOTURN_Params', 'TrackerMIL_Params', 'OriginalClassName_Params', 'HistogramPhaseUnwrapping_Params', 'ClassificationModel', 'TextRecognitionModel', 'DetectionModel', 'TextDetectionModel_EAST', 'TextDetectionModel_DB', 'IntelligentScissorsMB', 'Model', 'Event', 'AsyncArray', 'GpuMat_Allocator*', 'GpuMat::Allocator', 'GpuMat_Allocator', 'HostMem', 'FileNode', 'Stream' ] if argtype.startswith('Ptr<'): return True return argtype in ref_or_struct_types def get_elixir_module_name(cname, double_quote_if_has_dot=False): global module_name_map if cname.startswith('cv::'): module_name_classname = cname[4:].split("::", maxsplit=2) if len(module_name_classname) == 2: module_name = module_name_classname[0] if module_name in module_name_map: mapped_module_name = module_name_map[module_name] cname = "cv::" + mapped_module_name + cname[4+len(module_name):] # elif cname.startswith("cv::") and 'a' <= cname[4] <= 'z': # print("warning cname=", cname) wname = cname elixir_module_name = make_elixir_module_names(module_name=wname) inner_ns = [] if wname.startswith('cv::'): wname = wname[4:] inner_ns = wname.split('::') elixir_module_name = make_elixir_module_names(separated_ns=inner_ns) elixir_module_name = elixir_module_name.replace('_', '').strip() if double_quote_if_has_dot and '.' in elixir_module_name: elixir_module_name = f'"{elixir_module_name}"' return elixir_module_name def is_struct(argtype: str, also_get: Optional[str] = None, classname: Optional[str] = None, decl: list=None): argtype = argtype.replace("std::", "").replace("cv::", "").replace("::", "_") special_structs = { # todo: UMat should be in its own module 'UMat': 'Evision.Mat' } struct_types = { 'Mat': 'Evision.Mat', 'GpuMat': 'Evision.CUDA.GpuMat', 'cuda_GpuMat': 'Evision.CUDA.GpuMat', 'AKAZE': 'Evision.AKAZE', 'AffineFeature': 'Evision.AffineFeature', 'AgastFeatureDetector': 'Evision.AgastFeatureDetector', 'Algorithm': 'Evision.Algorithm', 'AlignExposures': 'Evision.AlignExposures', 'AlignMTB': 'Evision.AlignMTB', 'AsyncArray': 'Evision.AsyncArray', 'BFMatcher': 'Evision.BFMatcher', 'BOWImgDescriptorExtractor': 'Evision.BOWImgDescriptorExtractor', 'BOWKMeansTrainer': 'Evision.BOWKMeansTrainer', 'BOWTrainer': 'Evision.BOWTrainer', 'BRISK': 'Evision.BRISK', 'BaseCascadeClassifier': 'Evision.BaseCascadeClassifier', 'BackgroundSubtractor': 'Evision.BackgroundSubtractor', 'BackgroundSubtractorKNN': 'Evision.BackgroundSubtractorKNN', 'BackgroundSubtractorMOG2': 'Evision.BackgroundSubtractorMOG2', 'CLAHE': 'Evision.CLAHE', 'CalibrateCRF': 'Evision.CalibrateCRF', 'CalibrateDebevec': 'Evision.CalibrateDebevec', 'CalibrateRobertson': 'Evision.CalibrateRobertson', 'CascadeClassifier': 'Evision.CascadeClassifier', 'CirclesGridFinderParameters': 'Evision.CirclesGridFinderParameters', 'DISOpticalFlow': 'Evision.DISOpticalFlow', 'DMatch': 'Evision.DMatch', 'DenseOpticalFlow': 'Evision.DenseOpticalFlow', 'DescriptorMatcher': 'Evision.DescriptorMatcher', 'FaceDetectorYN': 'Evision.FaceDetectorYN', 'FaceRecognizerSF': 'Evision.FaceRecognizerSF', 'FarnebackOpticalFlow': 'Evision.FarnebackOpticalFlow', 'FastFeatureDetector': 'Evision.FastFeatureDetector', 'Feature2D': 'Evision.Feature2D', 'FileNode': 'Evision.FileNode', 'FileStorage': 'Evision.FileStorage', 'FlannBasedMatcher': 'Evision.FlannBasedMatcher', 'GFTTDetector': 'Evision.GFTTDetector', 'GeneralizedHough': 'Evision.GeneralizedHough', 'GeneralizedHoughBallard': 'Evision.GeneralizedHoughBallard', 'GeneralizedHoughGuil': 'Evision.GeneralizedHoughGuil', 'HOGDescriptor': 'Evision.HOGDescriptor', 'KAZE': 'Evision.KAZE', 'KalmanFilter': 'Evision.KalmanFilter', 'KeyPoint': 'Evision.KeyPoint', 'LineSegmentDetector': 'Evision.LineSegmentDetector', 'MSER': 'Evision.MSER', 'MergeDebevec': 'Evision.MergeDebevec', 'MergeExposures': 'Evision.MergeExposures', 'MergeMertens': 'Evision.MergeMertens', 'MergeRobertson': 'Evision.MergeRobertson', 'ORB': 'Evision.ORB', 'PyRotationWarper': 'Evision.PyRotationWarper', 'QRCodeDetector': 'Evision.QRCodeDetector', 'QRCodeEncoder': 'Evision.QRCodeEncoder', 'QRCodeEncoder_Params': 'Evision.QRCodeEncoder.Params', 'SIFT': 'Evision.SIFT', 'SimpleBlobDetector': 'Evision.SimpleBlobDetector', 'SimpleBlobDetector_Params': 'Evision.SimpleBlobDetector.Params', 'SparseOpticalFlow': 'Evision.SparseOpticalFlow', 'SparsePyrLKOpticalFlow': 'Evision.SparsePyrLKOpticalFlow', 'StereoBM': 'Evision.StereoBM', 'StereoMatcher': 'Evision.StereoMatcher', 'StereoSGBM': 'Evision.StereoSGBM', 'Stitcher': 'Evision.Stitcher', 'Subdiv2D': 'Evision.Subdiv2D', 'TickMeter': 'Evision.TickMeter', 'Tonemap': 'Evision.Tonemap', 'TonemapDrago': 'Evision.TonemapDrago', 'TonemapMantiuk': 'Evision.TonemapMantiuk', 'TonemapReinhard': 'Evision.TonemapReinhard', 'Tracker': 'Evision.Tracker', 'TrackerDaSiamRPN': 'Evision.TrackerDaSiamRPN', 'TrackerDaSiamRPN_Params': 'Evision.TrackerDaSiamRPN.Params', 'TrackerGOTURN': 'Evision.TrackerGOTURN', 'TrackerGOTURN_Params': 'Evision.TrackerGOTURN.Params', 'TrackerMIL': 'Evision.TrackerMIL', 'TrackerMIL_Params': 'Evision.TrackerMIL.Params', 'UsacParams': 'Evision.UsacParams', 'VariationalRefinement': 'Evision.VariationalRefinement', 'VideoCapture': 'Evision.VideoCapture', 'VideoWriter': 'Evision.VideoWriter', "BufferPool": "Evision.CUDA.BufferPool", "DeviceInfo": "Evision.CUDA.DeviceInfo", "Event": "Evision.CUDA.Event", "GpuMat": "Evision.CUDA.GpuMat", "HostMem": "Evision.CUDA.HostMem", "Stream": "Evision.CUDA.Stream", "TargetArchs": "Evision.CUDA.TargetArchs", "AffineBasedEstimator": "Evision.Detail.AffineBasedEstimator", "AffineBestOf2NearestMatcher": "Evision.Detail.AffineBestOf2NearestMatcher", "BestOf2NearestMatcher": "Evision.Detail.BestOf2NearestMatcher", "BestOf2NearestRangeMatcher": "Evision.Detail.BestOf2NearestRangeMatcher", "Blender": "Evision.Detail.Blender", "BlocksChannelsCompensator": "Evision.Detail.BlocksChannelsCompensator", "BlocksCompensator": "Evision.Detail.BlocksCompensator", "BlocksGainCompensator": "Evision.Detail.BlocksGainCompensator", "BundleAdjusterAffine": "Evision.Detail.BundleAdjusterAffine", "BundleAdjusterAffinePartial": "Evision.Detail.BundleAdjusterAffinePartial", "BundleAdjusterBase": "Evision.Detail.BundleAdjusterBase", "BundleAdjusterRay": "Evision.Detail.BundleAdjusterRay", "BundleAdjusterReproj": "Evision.Detail.BundleAdjusterReproj", "CameraParams": "Evision.Detail.CameraParams", "ChannelsCompensator": "Evision.Detail.ChannelsCompensator", "DpSeamFinder": "Evision.Detail.DpSeamFinder", "Estimator": "Evision.Detail.Estimator", "ExposureCompensator": "Evision.Detail.ExposureCompensator", "FeatherBlender": "Evision.Detail.FeatherBlender", "FeaturesMatcher": "Evision.Detail.FeaturesMatcher", "GainCompensator": "Evision.Detail.GainCompensator", "GraphCutSeamFinder": "Evision.Detail.GraphCutSeamFinder", "HomographyBasedEstimator": "Evision.Detail.HomographyBasedEstimator", "ImageFeatures": "Evision.Detail.ImageFeatures", "MatchesInfo": "Evision.Detail.MatchesInfo", "MultiBandBlender": "Evision.Detail.MultiBandBlender", "NoBundleAdjuster": "Evision.Detail.NoBundleAdjuster", "NoExposureCompensator": "Evision.Detail.NoExposureCompensator", "NoSeamFinder": "Evision.Detail.NoSeamFinder", "PairwiseSeamFinder": "Evision.Detail.PairwiseSeamFinder", "SeamFinder": "Evision.Detail.SeamFinder", "SphericalProjector": "Evision.Detail.SphericalProjector", "Timelapser": "Evision.Detail.Timelapser", "VoronoiSeamFinder": "Evision.Detail.VoronoiSeamFinder", "ClassificationModel": "Evision.DNN.ClassificationModel", "DetectionModel": "Evision.DNN.DetectionModel", "DictValue": "Evision.DNN.DictValue", "KeypointsModel": "Evision.DNN.KeypointsModel", "Layer": "Evision.DNN.Layer", "Model": "Evision.DNN.Model", "Net": "Evision.DNN.Net", "SegmentationModel": "Evision.DNN.SegmentationModel", "TextDetectionModel": "Evision.DNN.TextDetectionModel", "TextDetectionModel_DB": "Evision.DNN.TextDetectionModelDB", "TextDetectionModel_EAST": "Evision.DNN.TextDetectionModelEAST", "TextRecognitionModel": "Evision.DNN.TextRecognitionModel", "Index": "Evision.Flann.Index", "ANN_MLP": "Evision.ML.ANNMLP", "Boost": "Evision.ML.Boost", "DTrees": "Evision.ML.DTrees", "EM": "Evision.ML.EM", "KNearest": "Evision.ML.KNearest", "LogisticRegression": "Evision.ML.LogisticRegression", "NormalBayesClassifier": "Evision.ML.NormalBayesClassifier", "ParamGrid": "Evision.ML.ParamGrid", "RTrees": "Evision.ML.RTrees", "SVM": "Evision.ML.SVM", "SVMSGD": "Evision.ML.SVMSGD", "StatModel": "Evision.ML.StatModel", "TrainData": "Evision.ML.TrainData", "Device": "Evision.OCL.Device", "IntelligentScissorsMB": "Evision.Segmentation.IntelligentScissorsMB", "OriginalClassName": "Evision.Utils.Nested.OriginalClassName", "OriginalClassName_Params": "Evision.Utils.Nested.OriginalClassName.Params", # opencv_contrib "CharucoBoard": "Evision.ArUco.CharucoBoard", "AffineTransformer": "Evision.AffineTransformer", "EMDHistogramCostExtractor": "Evision.EMDHistogramCostExtractor", "HausdorffDistanceExtractor": "Evision.HausdorffDistanceExtractor", "HistogramCostExtractor": "Evision.HistogramCostExtractor", "NormHistogramCostExtractor": "Evision.NormHistogramCostExtractor", "ShapeContextDistanceExtractor": "Evision.ShapeContextDistanceExtractor", "ShapeDistanceExtractor": "Evision.ShapeDistanceExtractor", "ShapeTransformer": "Evision.ShapeTransformer", "ThinPlateSplineShapeTransformer": "Evision.ThinPlateSplineShapeTransformer", "TrackerCSRT": "Evision.TrackerCSRT", "TrackerCSRT_Params": "Evision.TrackerCSRT.Params", "TrackerKCF": "Evision.TrackerKCF", "TrackerKCF_Params": "Evision.TrackerKCF.Params", "HistogramPhaseUnwrapping": "Evision.HistogramPhaseUnwrapping", "HistogramPhaseUnwrapping_Params": "Evision.HistogramPhaseUnwrapping.Params", "Facemark": "Evision.Face.Facemark", "ImgHashBase": "Evision.ImgHash.ImgHashBase", "ColorMomentHash": "Evision.ImgHash.ColorMomentHash", "MarrHildrethHash": "Evision.ImgHash.MarrHildrethHash", "PHash": "Evision.ImgHash.PHash", "RadialVarianceHash": "Evision.ImgHash.RadialVarianceHash", "GrayCodePattern": "Evision.StructuredLight.GrayCodePattern", "SinusoidalPattern": "Evision.StructuredLight.SinusoidalPattern", "SinusoidalPattern_Params": "Evision.StructuredLight.SinusoidalPattern.Params", "StructuredLightPattern": "Evision.StructuredLight.StructuredLightPattern", "DnnSuperResImpl": "Evision.DNNSuperRes.DNNSuperResImpl", "legacy_Tracker": "Evision.Legacy.MultiTracker", "ERFilter": "Evision.Text.ERFilter", "ERFilter_Callback": "Evision.Text.ERFilter.Callback", "OCRBeamSearchDecoder_ClassifierCallback": "Evision.Text.OCRBeamSearchDecoder.ClassifierCallback", "OCRHMMDecoder_ClassifierCallback": "Evision.Text.OCRHMMDecoder.ClassifierCallback", "AdaptiveManifoldFilter": "Evision.XImgProc.AdaptiveManifoldFilter", "ContourFitting": "Evision.XImgProc.ContourFitting", "DisparityWLSFilter": "Evision.XImgProc.DisparityWLSFilter", "DTFilter": "Evision.XImgProc.DTFilter", "EdgeAwareInterpolator": "Evision.XImgProc.EdgeAwareInterpolator", "EdgeBoxes": "Evision.XImgProc.EdgeBoxes", "EdgeDrawing": "Evision.XImgProc.EdgeDrawing", "EdgeDrawing_Params": "Evision.XImgProc.EdgeDrawing.Params", "FastBilateralSolverFilter": "Evision.XImgProc.FastBilateralSolverFilter", "FastGlobalSmootherFilter": "Evision.XImgProc.FastGlobalSmootherFilter", "FastLineDetector": "Evision.XImgProc.FastLineDetector", "GraphSegmentation": "Evision.XImgProc.GraphSegmentation", "GuidedFilter": "Evision.XImgProc.GuidedFilter", "RFFeatureGetter": "Evision.XImgProc.RFFeatureGetter", "RICInterpolator": "Evision.XImgProc.RICInterpolator", "ScanSegment": "Evision.XImgProc.ScanSegment", "SelectiveSearchSegmentation": "Evision.XImgProc.SelectiveSearchSegmentation", "SelectiveSearchSegmentationStrategyColor": "Evision.XImgProc.SelectiveSearchSegmentationStrategyColor", "SelectiveSearchSegmentationStrategyFill": "Evision.XImgProc.SelectiveSearchSegmentationStrategyFill", "SelectiveSearchSegmentationStrategy": "Evision.XImgProc.SelectiveSearchSegmentationStrategy", "SelectiveSearchSegmentationStrategyMultiple": "Evision.XImgProc.SelectiveSearchSegmentationStrategyMultiple", "SelectiveSearchSegmentationStrategySize": "Evision.XImgProc.SelectiveSearchSegmentationStrategySize", "SelectiveSearchSegmentationStrategyTexture": "Evision.XImgProc.SelectiveSearchSegmentationStrategyTexture", "StructuredEdgeDetection": "Evision.XImgProc.StructuredEdgeDetection", "SuperpixelLSC": "Evision.XImgProc.SuperpixelLSC", "SuperpixelSEEDS": "Evision.XImgProc.SuperpixelSEEDS", "SuperpixelSLIC": "Evision.XImgProc.SuperpixelSLIC", "GrayworldWB": "Evision.XPhoto.GrayworldWB", "LearningBasedWB": "Evision.XPhoto.LearningBasedWB", "SimpleWB": "Evision.XPhoto.SimpleWB", "TonemapDurand": "Evision.XPhoto.TonemapDurand", "BackgroundSubtractorCNT": "Evision.BgSegm.BackgroundSubtractorCNT", "BackgroundSubtractorGMG": "Evision.BgSegm.BackgroundSubtractorGMG", "BackgroundSubtractorGSOC": "Evision.BgSegm.BackgroundSubtractorGSOC", "BackgroundSubtractorLSBP": "Evision.BgSegm.BackgroundSubtractorLSBP", "BackgroundSubtractorMOG": "Evision.BgSegm.BackgroundSubtractorMOG", "SyntheticSequenceGenerator": "Evision.BgSegm.SyntheticSequenceGenerator", "ColoredKinFu": "Evision.ColoredKinFu", "LargeKinfu": "Evision.LargeKinfu", "linemod_Detector": "Evision.LineMod.Detector", "Template": "Evision.LineMod.Template", "Matx33f": "Evision.Mat", "Matx33d": "Evision.Mat", "Matx44f": "Evision.Mat", "Matx44d": "Evision.Mat", "TrackerNano": "Evision.TrackerNano", "TrackerNano_Params": "Evision.TrackerNano.Params", "ArucoDetector": "Evision.ArUco.ArucoDetector", "mcc_CChecker": "Evision.MCC.CCheckerDetector", "dnn_Net": "Evision.DNN.Net", "BinaryDescriptor": "Evision.LineDescriptor.BinaryDescriptor", "KeyLine": "Evision.LineDescriptor.BinaryDescriptor.KeyLine", "BinaryDescriptorMatcher": "Evision.LineDescriptor.BinaryDescriptorMatcher", "LSDParam": "Evision.LineDescriptor.LSDParam", "LSDDetectorWithParams": "Evision.LineDescriptor.LSDDetector", "LSDDetector": "Evision.LineDescriptor.LSDDetector", "Pose3DPtr": "Evision.PPFMatch3D.Pose3D", "Pose3D": "Evision.PPFMatch3D.Pose3D", "PPF3DDetector": "Evision.PPFMatch3D.PPF3DDetector", "WeChatQRCode": "Evision.WeChatQRCode.WeChatQRCode", # CUDA "cuda_BackgroundSubtractorMOG": "Evision.CUDA.BackgroundSubtractorMOG", "cuda_BackgroundSubtractorMOG2": "Evision.CUDA.BackgroundSubtractorMOG2", "cuda_CascadeClassifier": "Evision.CUDA.CascadeClassifier", "cuda_CLAHE": "Evision.CUDA.CLAHE", "cudacodec_VideoWriter": "Evision.CUDACodec.VideoWriter", "cuda_DescriptorMatcher": "Evision.CUDA.DescriptorMatcher", "cuda_DisparityBilateralFilter": "Evision.CUDA.DisparityBilateralFilter", "cuda_FastFeatureDetector": "Evision.CUDA.FastFeatureDetector", "cuda_ORB": "Evision.CUDA.ORB", "cuda_StereoBeliefPropagation": "Evision.CUDA.StereoBeliefPropagation", "cuda_StereoBM": "Evision.CUDA.StereoBM", "cuda_StereoConstantSpaceBP": "Evision.CUDA.StereoConstantSpaceBP", "cuda_StereoSGM": "Evision.CUDA.StereoSGM", } # argtype => classname => module name strict_match = { "Board": {"aruco_Board": "Evision.ArUco.Board"}, "DetectorParameters": {"aruco_DetectorParameters": "Evision.ArUco.DetectorParameters"}, "AverageHash": {"img_hash_AverageHash": "Evision.ImgHash.AverageHash"}, "BlockMeanHash": {"img_hash_BlockMeanHash": "Evision.ImgHash.BlockMeanHash"}, "PhaseUnwrapping": {"phase_unwrapping_PhaseUnwrapping": "Evision.PhaseUnwrapping.PhaseUnwrapping"}, "MACE": {"face_MACE": "Evision.Face.MACE"}, "ml_SVM": {"quality_QualityBRISQUE": "Evision.ML.SVM"}, "legacy_TrackerBoosting": {"legacy_TrackerBoosting": "Evision.Legacy.TrackerBoosting"}, "legacy_TrackerCSRT": {"legacy_TrackerCSRT": "Evision.Legacy.TrackerCSRT"}, "legacy_TrackerKCF": {"legacy_TrackerKCF": "Evision.Legacy.TrackerKCF"}, "legacy_TrackerMIL": {"legacy_TrackerMIL": "Evision.Legacy.TrackerMIL"}, "legacy_TrackerMOSSE": {"legacy_TrackerMOSSE": "Evision.Legacy.TrackerMOSSE"}, "legacy_TrackerMedianFlow": {"legacy_TrackerMedianFlow": "Evision.Legacy.TrackerMedianFlow"}, "legacy_TrackerTLD": {"legacy_TrackerTLD": "Evision.Legacy.TrackerTLD"}, "CUDA": {"cuda_SURF_CUDA": "Evision.CUDA.SURFCUDA"}, "SURF_CUDA": {"cuda_SURF_CUDA": "Evision.CUDA.SURFCUDA"}, "Params": { "large_kinfu_LargeKinfu": "Evision.LargeKinfu.Params", "large_kinfu_Params": "Evision.LargeKinfu.Params", "colored_kinfu_Params": "Evision.ColoredKinFu.Params", "colored_kinfu_ColoredKinFu": "Evision.ColoredKinFu.Params", }, "large_kinfu_Params": {"large_kinfu_Params": "Evision.LargeKinfu.Params"}, "colored_kinfu_Params": { "colored_kinfu_Params": "Evision.ColoredKinFu.Params", }, "kinfu_Params": { "kinfu_Params": "Evision.KinFu.Params", "dynafu_DynaFu": "Evision.DynaFu.Params" }, "ICP": { "ppf_match_3d_ICP": "Evision.PPFMatch3D.ICP" } } second_ret = None argtype = argtype.strip() second_ret = None if argtype.startswith('Ptr<'): argtype = argtype[len('Ptr<'):-1].strip() arg_is_struct = argtype in struct_types or argtype in special_structs if argtype in ["pair", "Scalar", "kinfu_VolumeType", "VolumeType", "Volume"]: return False is_strict_match = False if not arg_is_struct and argtype in strict_match and classname is not None: arg_is_struct = classname in strict_match[argtype] is_strict_match = arg_is_struct if not arg_is_struct: if is_basic_types(argtype): return False if classname is not None and decl is not None and len(classname) == 0 and len(decl) > 0: if decl[0].startswith('cv.'): classname = decl[0][3:].replace('.', '_') if classname: module_class = classname.split("_", maxsplit=2) if len(module_class) == 2: module_name, class_name = module_class[0], module_class[1] struct_name = None lowercase_start = 'a' <= argtype[0] <= 'z' if lowercase_start and not argtype.startswith("vector_"): if module_name == 'ml' and (argtype == 'float*' or argtype == 'TermCriteria'): pass elif module_name == 'legacy' and argtype.startswith('legacy_'): argtype = argtype[len('legacy_'):] elif module_name == 'cuda' and argtype == "cuda_GpuMat": arg_is_struct = True argtype = "Evision.CUDA.GpuMat" elif module_name == 'cuda' and class_name == "Filter": arg_is_struct = True argtype = "Evision.CUDA.Filter" elif module_name == 'detail' and argtype in ['vector', 'vector']: arg_is_struct = True if argtype == 'vector': struct_name = "[Evision.KeyPoint.t()]" elif argtype == 'vector': struct_name = "[Evision.DMatch.t()]" elif argtype == 'vector': arg_is_struct = True struct_name = "[Evision.Mat.t()]" elif argtype == 'vector< pair >': arg_is_struct = False elif argtype == 'vector