






from PIL import Image







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Image     ):
	snake_case__,		snake_case__				:   Dict     =						image.size
	snake_case__				:   List[str]     =						0
	snake_case__				:   List[Any]     =						image.load()
	for i in range(snake_case_     ):
		for j in range(snake_case_     ):
			snake_case__				:   int     =						pixels[j, i]
			mean += pixel
	mean //= width * height

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


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











from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
	if not (is_transformers_available() and is_torch_available()):
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	from ...utils.dummy_torch_and_transformers_objects import KandinskyPipeline, KandinskyPriorPipeline
else:
	from .pipeline_kandinsky import KandinskyPipeline
	from .pipeline_kandinsky_imgaimg import KandinskyImgaImgPipeline
	from .pipeline_kandinsky_inpaint import KandinskyInpaintPipeline
	from .pipeline_kandinsky_prior import KandinskyPriorPipeline, KandinskyPriorPipelineOutput
	from .text_encoder import MultilingualCLIP



