






"""simple docstring"""
import hashlib
import unittest
from typing import Dict

import numpy as np

from transformers import (
    MODEL_FOR_MASK_GENERATION_MAPPING,
    TF_MODEL_FOR_MASK_GENERATION_MAPPING,
    is_vision_available,
    pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_torch,
    require_vision,
    slow,
)


if is_vision_available():
							from PIL import Image
else:



							class   SCREAMING_SNAKE_CASE	:





								"""simple docstring"""




								@staticmethod
								def  lowerCamelCase(*lowerCAmelCase_  ,  **lowerCAmelCase_				):
									pass






def       __UpperCamelCase						(		snake_case__       ):
	A_		:    int						     = hashlib.mda(image.tobytes()       )
	return m.hexdigest()[:10]






def       __UpperCamelCase						(		snake_case__       ):
	A_		:    str						     = np.array(snake_case__       )
	A_		:    int						     = npimg.shape
	return {"hash": hashimage(snake_case__       ), "shape": shape}




@is_pipeline_test
@require_vision
@require_torch
class   SCREAMING_SNAKE_CASE	(					unittest.TestCase    ):





	"""simple docstring"""




	_A							:					Tuple 			=					dict(
	    (list(MODEL_FOR_MASK_GENERATION_MAPPING.items()    ) if MODEL_FOR_MASK_GENERATION_MAPPING else [])    )
	_A							:					int 			=					dict(
	    (list(TF_MODEL_FOR_MASK_GENERATION_MAPPING.items()    ) if TF_MODEL_FOR_MASK_GENERATION_MAPPING else [])    )





	def  lowerCamelCase(self  ,  lowerCAmelCase_  ,  lowerCAmelCase_  ,  lowerCAmelCase_				):
		A_		:    Tuple						     = MaskGenerationPipeline(model=lowerCAmelCase_  ,  image_processor=lowerCAmelCase_				)
		return image_segmenter, [
		    "./tests/fixtures/tests_samples/COCO/000000039769.png",
		    "./tests/fixtures/tests_samples/COCO/000000039769.png",
		]





	def  lowerCamelCase(self  ,  lowerCAmelCase_  ,  lowerCAmelCase_				):
		pass





	@require_tf
	@unittest.skip("""Image segmentation not implemented in TF"""				)
	def  lowerCamelCase(self				):
		pass





	@slow
	@require_torch
	def  lowerCamelCase(self				):
		A_		:    Dict						     = pipeline("""mask-generation"""  ,  model="""facebook/sam-vit-huge"""				)

		A_		:    Optional[Any]						     = image_segmenter("""http://images.cocodataset.org/val2017/000000039769.jpg"""  ,  points_per_batch=256				)

		# Shortening by hashing
		A_		:    Tuple						     = []
		for i, o in enumerate(outputs["""masks"""]				):
			new_outupt += [{"mask": mask_to_test_readable(lowerCAmelCase_				), "scores": outputs["scores"][i]}]

		# fmt: off
		self.assertEqual(
		    nested_simplify(lowerCAmelCase_  ,  decimals=4				)  ,  [
		        {"""mask""": {"""hash""": """115ad19f5f""", """shape""": (480, 640)}, """scores""": 1.0444},
		        {"""mask""": {"""hash""": """6affa964c6""", """shape""": (480, 640)}, """scores""": 1.021},
		        {"""mask""": {"""hash""": """dfe28a0388""", """shape""": (480, 640)}, """scores""": 1.0167},
		        {"""mask""": {"""hash""": """c0a5f4a318""", """shape""": (480, 640)}, """scores""": 1.0132},
		        {"""mask""": {"""hash""": """fe8065c197""", """shape""": (480, 640)}, """scores""": 1.0053},
		        {"""mask""": {"""hash""": """e2d0b7a0b7""", """shape""": (480, 640)}, """scores""": 0.9967},
		        {"""mask""": {"""hash""": """453c7844bd""", """shape""": (480, 640)}, """scores""": 0.993},
		        {"""mask""": {"""hash""": """3d44f2926d""", """shape""": (480, 640)}, """scores""": 0.9909},
		        {"""mask""": {"""hash""": """64033ddc3f""", """shape""": (480, 640)}, """scores""": 0.9879},
		        {"""mask""": {"""hash""": """801064ff79""", """shape""": (480, 640)}, """scores""": 0.9834},
		        {"""mask""": {"""hash""": """6172f276ef""", """shape""": (480, 640)}, """scores""": 0.9716},
		        {"""mask""": {"""hash""": """b49e60e084""", """shape""": (480, 640)}, """scores""": 0.9612},
		        {"""mask""": {"""hash""": """a811e775fd""", """shape""": (480, 640)}, """scores""": 0.9599},
		        {"""mask""": {"""hash""": """a6a8ebcf4b""", """shape""": (480, 640)}, """scores""": 0.9552},
		        {"""mask""": {"""hash""": """9d8257e080""", """shape""": (480, 640)}, """scores""": 0.9532},
		        {"""mask""": {"""hash""": """32de6454a8""", """shape""": (480, 640)}, """scores""": 0.9516},
		        {"""mask""": {"""hash""": """af3d4af2c8""", """shape""": (480, 640)}, """scores""": 0.9499},
		        {"""mask""": {"""hash""": """3c6db475fb""", """shape""": (480, 640)}, """scores""": 0.9483},
		        {"""mask""": {"""hash""": """c290813fb9""", """shape""": (480, 640)}, """scores""": 0.9464},
		        {"""mask""": {"""hash""": """b6f0b8f606""", """shape""": (480, 640)}, """scores""": 0.943},
		        {"""mask""": {"""hash""": """92ce16bfdf""", """shape""": (480, 640)}, """scores""": 0.943},
		        {"""mask""": {"""hash""": """c749b25868""", """shape""": (480, 640)}, """scores""": 0.9408},
		        {"""mask""": {"""hash""": """efb6cab859""", """shape""": (480, 640)}, """scores""": 0.9335},
		        {"""mask""": {"""hash""": """1ff2eafb30""", """shape""": (480, 640)}, """scores""": 0.9326},
		        {"""mask""": {"""hash""": """788b798e24""", """shape""": (480, 640)}, """scores""": 0.9262},
		        {"""mask""": {"""hash""": """abea804f0e""", """shape""": (480, 640)}, """scores""": 0.8999},
		        {"""mask""": {"""hash""": """7b9e8ddb73""", """shape""": (480, 640)}, """scores""": 0.8986},
		        {"""mask""": {"""hash""": """cd24047c8a""", """shape""": (480, 640)}, """scores""": 0.8984},
		        {"""mask""": {"""hash""": """6943e6bcbd""", """shape""": (480, 640)}, """scores""": 0.8873},
		        {"""mask""": {"""hash""": """b5f47c9191""", """shape""": (480, 640)}, """scores""": 0.8871}
		    ]  ,  )
		# fmt: on





	@require_torch
	@slow
	def  lowerCamelCase(self				):
		A_		:    Union[str, Any]						     = """facebook/sam-vit-huge"""
		A_		:    List[str]						     = pipeline("""mask-generation"""  ,  model=lowerCAmelCase_				)

		A_		:    Optional[int]						     = image_segmenter(
		    """http://images.cocodataset.org/val2017/000000039769.jpg"""  ,  pred_iou_thresh=1  ,  points_per_batch=256				)

		# Shortening by hashing
		A_		:    Dict						     = []
		for i, o in enumerate(outputs["""masks"""]				):
			new_outupt += [{"mask": mask_to_test_readable(lowerCAmelCase_				), "scores": outputs["scores"][i]}]

		self.assertEqual(
		    nested_simplify(lowerCAmelCase_  ,  decimals=4				)  ,  [
		        {"""mask""": {"""hash""": """115ad19f5f""", """shape""": (480, 640)}, """scores""": 1.0444},
		        {"""mask""": {"""hash""": """6affa964c6""", """shape""": (480, 640)}, """scores""": 1.0210},
		        {"""mask""": {"""hash""": """dfe28a0388""", """shape""": (480, 640)}, """scores""": 1.0167},
		        {"""mask""": {"""hash""": """c0a5f4a318""", """shape""": (480, 640)}, """scores""": 1.0132},
		        {"""mask""": {"""hash""": """fe8065c197""", """shape""": (480, 640)}, """scores""": 1.0053},
		    ]  ,  )









"""simple docstring"""
from __future__ import annotations






def       __UpperCamelCase						(		snake_case__ , snake_case__ = None , snake_case__ = None       ):
	if start is None:
		A_		:    Dict						     = 0

	if end is None:
		A_		:    Dict						     = len(snake_case__       ) - 1

	if start >= end:
		return

	A_		:    List[Any]						     = (start + end) // 2

	slowsort(snake_case__ , snake_case__ , snake_case__       )
	slowsort(snake_case__ , mid + 1 , snake_case__       )

	if sequence[end] < sequence[mid]:
		A_     ,  A_		:    Dict						     = sequence[mid], sequence[end]

	slowsort(snake_case__ , snake_case__ , end - 1       )


if __name__ == "__main__":
							from doctest import testmod

							testmod()

