


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


A   :					Dict	=      {
    "configuration_wav2vec2": ["WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Wav2Vec2Config"],
    "feature_extraction_wav2vec2": ["Wav2Vec2FeatureExtractor"],
    "processing_wav2vec2": ["Wav2Vec2Processor"],
    "tokenization_wav2vec2": ["Wav2Vec2CTCTokenizer", "Wav2Vec2Tokenizer"],
}


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A   :					List[str]	=      [
        "WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST",
        "Wav2Vec2ForAudioFrameClassification",
        "Wav2Vec2ForCTC",
        "Wav2Vec2ForMaskedLM",
        "Wav2Vec2ForPreTraining",
        "Wav2Vec2ForSequenceClassification",
        "Wav2Vec2ForXVector",
        "Wav2Vec2Model",
        "Wav2Vec2PreTrainedModel",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A   :					List[str]	=      [
        "TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFWav2Vec2ForCTC",
        "TFWav2Vec2Model",
        "TFWav2Vec2PreTrainedModel",
        "TFWav2Vec2ForSequenceClassification",
    ]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A   :					Union[str, Any]	=      [
        "FlaxWav2Vec2ForCTC",
        "FlaxWav2Vec2ForPreTraining",
        "FlaxWav2Vec2Model",
        "FlaxWav2Vec2PreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_wavaveca import WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP, WavaVecaConfig
    from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
    from .processing_wavaveca import WavaVecaProcessor
    from .tokenization_wavaveca import WavaVecaCTCTokenizer, WavaVecaTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_wavaveca import (
            WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
            WavaVecaForAudioFrameClassification,
            WavaVecaForCTC,
            WavaVecaForMaskedLM,
            WavaVecaForPreTraining,
            WavaVecaForSequenceClassification,
            WavaVecaForXVector,
            WavaVecaModel,
            WavaVecaPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_wavaveca import (
            TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFWavaVecaForCTC,
            TFWavaVecaForSequenceClassification,
            TFWavaVecaModel,
            TFWavaVecaPreTrainedModel,
        )

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_wavaveca import (
            FlaxWavaVecaForCTC,
            FlaxWavaVecaForPreTraining,
            FlaxWavaVecaModel,
            FlaxWavaVecaPreTrainedModel,
        )


else:
    import sys

    A   :					List[Any]	=      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






import cva
import numpy as np







class     _lowercase				:


       """simple docstring"""




       def __init__(     self							:    Union[str, Any]      ,   __lowerCamelCase							:    float      ,   __lowerCamelCase							:    int ):


             '''simple docstring'''



             if k in (0.0_4, 0.0_6):
                   lowerCamelCase__	:       int					=						k
                   lowerCamelCase__	:       List[str]					=						window_size
             else:
                   raise ValueError("invalid k value" )





       def __str__(     self							:    str ):


             '''simple docstring'''



             return str(self.k )





       def 		lowerCAmelCase  (     self							:    Tuple      ,   __lowerCamelCase							:    str ):


             '''simple docstring'''



             lowerCamelCase__	:       Union[str, Any]					=						cva.imread(__lowerCamelCase      ,   0 )
             lowerCamelCase__					,     lowerCamelCase__	:       Any					=						img.shape
             lowerCamelCase__	:       list[list[int]]					=						[]
             lowerCamelCase__	:       List[Any]					=						img.copy()
             lowerCamelCase__	:       int					=						cva.cvtColor(__lowerCamelCase      ,   cva.COLOR_GRAY2RGB )
             lowerCamelCase__					,     lowerCamelCase__	:       int					=						np.gradient(__lowerCamelCase )
             lowerCamelCase__	:       Dict					=						dx**2
             lowerCamelCase__	:       Optional[Any]					=						dy**2
             lowerCamelCase__	:       int					=						dx * dy
             lowerCamelCase__	:       Union[str, Any]					=						0.0_4
             lowerCamelCase__	:       Any					=						self.window_size // 2
             for y in range(__lowerCamelCase      ,   h - offset ):
                   for x in range(__lowerCamelCase      ,   w - offset ):
                         lowerCamelCase__	:       Optional[Any]					=						ixx[
                             y - offset : y + offset + 1, x - offset : x + offset + 1
                         ].sum()
                         lowerCamelCase__	:       Optional[Any]					=						iyy[
                             y - offset : y + offset + 1, x - offset : x + offset + 1
                         ].sum()
                         lowerCamelCase__	:       str					=						ixy[
                             y - offset : y + offset + 1, x - offset : x + offset + 1
                         ].sum()

                         lowerCamelCase__	:       Optional[Any]					=						(wxx * wyy) - (wxy**2)
                         lowerCamelCase__	:       List[str]					=						wxx + wyy
                         lowerCamelCase__	:       List[Any]					=						det - k * (trace**2)
                         # Can change the value
                         if r > 0.5:
                               corner_list.append([x, y, r] )
                               color_img.itemset((y, x, 0)      ,   0 )
                               color_img.itemset((y, x, 1)      ,   0 )
                               color_img.itemset((y, x, 2)      ,   255 )
             return color_img, corner_list


if __name__ == "__main__":
    A   :					Tuple	=      HarrisCorner(0.0_4, 3)
    A,						A   :					Optional[int]	=      edge_detect.detect("path_to_image")
    cva.imwrite("detect.png", color_img)


