
'''simple docstring'''



from PIL import Image





def 			_A		(				lowercase__						):
						lowercase__							=							image.size
						lowercase__							=							0
						lowercase__							=							image.load()
						for i in range(UpperCAmelCase_						):
												for j in range(UpperCAmelCase_						):
																		lowercase__							=							pixels[j, i]
																		mean += pixel
						mean //= width * height

						for j in range(UpperCAmelCase_						):
												for i in range(UpperCAmelCase_						):
																		lowercase__							=							255 if pixels[i, j] > mean else 0
						return image


if __name__ == "__main__":
				__A        =     mean_threshold(Image.open("path_to_image").convert("L"))
				image.save("output_image_path")











'''simple docstring'''
import os
from pathlib import Path






def A__       (	):
						from torch.utils.cpp_extension import load

						_UpperCamelCase   :						Optional[Any]												=  Path(UpperCAmelCase_				).resolve().parent.parent.parent / 'kernels' / 'deformable_detr'
						_UpperCamelCase   :						Tuple												=  [
						    root / filename
						    for filename in [
						        'vision.cpp',
						        os.path.join('cpu'    ,    'ms_deform_attn_cpu.cpp'				),
						        os.path.join('cuda'    ,    'ms_deform_attn_cuda.cu'				),
						    ]
						]

						load(
						    'MultiScaleDeformableAttention'    ,    UpperCAmelCase_    ,    with_cuda=UpperCAmelCase_    ,    extra_include_paths=[str(UpperCAmelCase_				)]    ,    extra_cflags=['-DWITH_CUDA=1']    ,    extra_cuda_cflags=[
						        '-DCUDA_HAS_FP16=1',
						        '-D__CUDA_NO_HALF_OPERATORS__',
						        '-D__CUDA_NO_HALF_CONVERSIONS__',
						        '-D__CUDA_NO_HALF2_OPERATORS__',
						    ]    ,    )

						import MultiScaleDeformableAttention as MSDA

						return MSDA


