from pathlib import Path

import numpy as np
from PIL import Image




def   lowerCAmelCase_					(	__A				)	->							np.ndarray:







      '''simple docstring'''


      UpperCAmelCase__								=    rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
      return 0.2989 * r + 0.5870 * g + 0.1140 * b




def   lowerCAmelCase_					(	__A				)	->							np.ndarray:







      '''simple docstring'''


      return (gray > 127) & (gray <= 255)




def   lowerCAmelCase_					(	__A,    __A				)	->							np.ndarray:







      '''simple docstring'''


      UpperCAmelCase__								=    np.zeros_like(_lowercase				)
      UpperCAmelCase__								=    np.zeros(
          (image.shape[0] + kernel.shape[0] - 1, image.shape[1] + kernel.shape[1] - 1)				)

      # Copy image to padded image
      UpperCAmelCase__								=    image

      # Iterate over image & apply kernel
      for x in range(image.shape[1]				):
            for y in range(image.shape[0]				):
                  UpperCAmelCase__								=    (
                      kernel * image_padded[y : y + kernel.shape[0], x : x + kernel.shape[1]]
                  ).sum()
                  UpperCAmelCase__								=    int(summation > 0				)
      return output


if __name__ == "__main__":
      # read original image
      UpperCamelCase__											=   Path(__file__).resolve().parent / '''image_data''' / '''lena.jpg'''
      UpperCamelCase__											=   np.array(Image.open(lena_path))
      # kernel to be applied
      UpperCamelCase__											=   np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])
      UpperCamelCase__											=   dilation(gray_to_binary(rgb_to_gray(lena)), structuring_element)
      # Save the output image
      UpperCamelCase__											=   Image.fromarray(output).convert('RGB')
      pil_img.save('result_dilation.png')










"""simple docstring"""




from ..utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_scipy_available,
    is_torch_available,
    is_torchsde_available,
)


try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		from ..utils.dummy_pt_objects import *  # noqa F403
else:
		from .scheduling_consistency_models import CMStochasticIterativeScheduler
		from .scheduling_ddim import DDIMScheduler
		from .scheduling_ddim_inverse import DDIMInverseScheduler
		from .scheduling_ddim_parallel import DDIMParallelScheduler
		from .scheduling_ddpm import DDPMScheduler
		from .scheduling_ddpm_parallel import DDPMParallelScheduler
		from .scheduling_deis_multistep import DEISMultistepScheduler
		from .scheduling_dpmsolver_multistep import DPMSolverMultistepScheduler
		from .scheduling_dpmsolver_multistep_inverse import DPMSolverMultistepInverseScheduler
		from .scheduling_dpmsolver_singlestep import DPMSolverSinglestepScheduler
		from .scheduling_euler_ancestral_discrete import EulerAncestralDiscreteScheduler
		from .scheduling_euler_discrete import EulerDiscreteScheduler
		from .scheduling_heun_discrete import HeunDiscreteScheduler
		from .scheduling_ipndm import IPNDMScheduler
		from .scheduling_k_dpm_2_ancestral_discrete import KDPMaAncestralDiscreteScheduler
		from .scheduling_k_dpm_2_discrete import KDPMaDiscreteScheduler
		from .scheduling_karras_ve import KarrasVeScheduler
		from .scheduling_pndm import PNDMScheduler
		from .scheduling_repaint import RePaintScheduler
		from .scheduling_sde_ve import ScoreSdeVeScheduler
		from .scheduling_sde_vp import ScoreSdeVpScheduler
		from .scheduling_unclip import UnCLIPScheduler
		from .scheduling_unipc_multistep import UniPCMultistepScheduler
		from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin
		from .scheduling_vq_diffusion import VQDiffusionScheduler

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		from ..utils.dummy_flax_objects import *  # noqa F403
else:
		from .scheduling_ddim_flax import FlaxDDIMScheduler
		from .scheduling_ddpm_flax import FlaxDDPMScheduler
		from .scheduling_dpmsolver_multistep_flax import FlaxDPMSolverMultistepScheduler
		from .scheduling_karras_ve_flax import FlaxKarrasVeScheduler
		from .scheduling_lms_discrete_flax import FlaxLMSDiscreteScheduler
		from .scheduling_pndm_flax import FlaxPNDMScheduler
		from .scheduling_sde_ve_flax import FlaxScoreSdeVeScheduler
		from .scheduling_utils_flax import (
		    FlaxKarrasDiffusionSchedulers,
		    FlaxSchedulerMixin,
		    FlaxSchedulerOutput,
		    broadcast_to_shape_from_left,
		)


try:
		if not (is_torch_available() and is_scipy_available()):
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		from ..utils.dummy_torch_and_scipy_objects import *  # noqa F403
else:
		from .scheduling_lms_discrete import LMSDiscreteScheduler

try:
		if not (is_torch_available() and is_torchsde_available()):
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		from ..utils.dummy_torch_and_torchsde_objects import *  # noqa F403
else:
		from .scheduling_dpmsolver_sde import DPMSolverSDEScheduler


