"""simple docstring"""





import numpy as np
import torch

from ..models.clipseg import CLIPSegForImageSegmentation
from ..utils import is_vision_available, requires_backends
from .base import PipelineTool


if is_vision_available():
				from PIL import Image
class  _snake_case     (					a__		):
						snake_case__			  =			(
						    "This is a tool that creates a segmentation mask of an image according to a label. It cannot create an image."
						    "It takes two arguments named `image` which should be the original image, and `label` which should be a text "
						    "describing the elements what should be identified in the segmentation mask. The tool returns the mask."
						)
						snake_case__			  =			"CIDAS/clipseg-rd64-refined"
						snake_case__			  =			"image_segmenter"
						snake_case__			  =			CLIPSegForImageSegmentation

						snake_case__			  =			["image", "text"]
						snake_case__			  =			["image"]






						def __init__(       self      :			Dict							,					*UpperCAmelCase      :			List[str]							,					**UpperCAmelCase      :			Dict    ):
													requires_backends(self							,					["vision"]    )
													super().__init__(*UpperCAmelCase							,					**UpperCAmelCase    )






						def       lowerCamelCase__     (       self      :			Tuple							,					UpperCAmelCase      :			"Image"							,					UpperCAmelCase      :			str    ):
													return self.pre_processor(text=[label]							,					images=[image]							,					padding=UpperCAmelCase							,					return_tensors="pt"    )






						def       lowerCamelCase__     (       self      :			Any							,					UpperCAmelCase      :			Any    ):
													with torch.no_grad():
																				__lowerCamelCase					:		Tuple							   =     self.model(**UpperCAmelCase    ).logits
													return logits







						def       lowerCamelCase__     (       self      :			Any							,					UpperCAmelCase      :			int    ):
													__lowerCamelCase					:		List[str]							   =     outputs.cpu().detach().numpy()
													__lowerCamelCase					:		str							   =     0
													__lowerCamelCase					:		Union[str, Any]							   =     1
													return Image.fromarray((array * 255).astype(np.uinta    )    )
"""simple docstring"""





import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class  _snake_case     :
						snake_case__			  =			None
						snake_case__			  =			False
						snake_case__			  =			False
						snake_case__			  =			False
						snake_case__			  =			None
						snake_case__			  =			None
						snake_case__			  =			False
						snake_case__			  =			False
						snake_case__			  =			False
						snake_case__			  =			True
						snake_case__			  =			None
						snake_case__			  =			1
						snake_case__			  =			None
						snake_case__			  =			False
						snake_case__			  =			None
						snake_case__			  =			None






						def       lowerCamelCase__     (       self      :			Any    ):
													return self.__class__(**{k: copy.deepcopy(UpperCAmelCase    ) for k, v in self.__dict__.items()}    )