






'''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        a_		:

       @staticmethod
       def 						A__		(   *_SCREAMING_SNAKE_CASE    ,	**_SCREAMING_SNAKE_CASE   )						->   Optional[Any]:



             """simple docstring"""






             pass







def 					lowercase__				(   __UpperCamelCase					)->				str:
      UpperCamelCase       						=      hashlib.mda(image.tobytes()					)
      return m.hexdigest()[:10]







def 					lowercase__				(   __UpperCamelCase					)->				Dict:
      UpperCamelCase       						=      np.array(__UpperCamelCase					)
      UpperCamelCase       						=      npimg.shape
      return {"hash": hashimage(__UpperCamelCase					), "shape": shape}






@is_pipeline_test
@require_vision
@require_torch
class        a_		(    unittest.TestCase       ):
  lowercase  	=   dict(
      (list(MODEL_FOR_MASK_GENERATION_MAPPING.items()       ) if MODEL_FOR_MASK_GENERATION_MAPPING else [])       )
  lowercase  	=   dict(
      (list(TF_MODEL_FOR_MASK_GENERATION_MAPPING.items()       ) if TF_MODEL_FOR_MASK_GENERATION_MAPPING else [])       )

  def 						A__		(   self    ,	_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE   )						->   Tuple:



        """simple docstring"""






        UpperCamelCase       						=      MaskGenerationPipeline(model=_SCREAMING_SNAKE_CASE    ,	image_processor=_SCREAMING_SNAKE_CASE   )
        return image_segmenter, [
            "./tests/fixtures/tests_samples/COCO/000000039769.png",
            "./tests/fixtures/tests_samples/COCO/000000039769.png",
        ]

  def 						A__		(   self    ,	_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE   )						->   Optional[Any]:



        """simple docstring"""






        pass

  @require_tf
  @unittest.skip("""Image segmentation not implemented in TF"""   )
  def 						A__		(   self   )						->   Union[str, Any]:



        """simple docstring"""






        pass

  @slow
  @require_torch
  def 						A__		(   self   )						->   Dict:



        """simple docstring"""






        UpperCamelCase       						=      pipeline("""mask-generation"""    ,	model="""facebook/sam-vit-huge"""   )

        UpperCamelCase       						=      image_segmenter("""http://images.cocodataset.org/val2017/000000039769.jpg"""    ,	points_per_batch=256   )

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

        # fmt: off
        self.assertEqual(
            nested_simplify(_SCREAMING_SNAKE_CASE    ,	decimals=4   )    ,	[
                {"""mask""": {"""hash""": """115ad19f5f""", """shape""": (480, 640)}, """scores""": 1.0_4_4_4},
                {"""mask""": {"""hash""": """6affa964c6""", """shape""": (480, 640)}, """scores""": 1.0_2_1},
                {"""mask""": {"""hash""": """dfe28a0388""", """shape""": (480, 640)}, """scores""": 1.0_1_6_7},
                {"""mask""": {"""hash""": """c0a5f4a318""", """shape""": (480, 640)}, """scores""": 1.0_1_3_2},
                {"""mask""": {"""hash""": """fe8065c197""", """shape""": (480, 640)}, """scores""": 1.0_0_5_3},
                {"""mask""": {"""hash""": """e2d0b7a0b7""", """shape""": (480, 640)}, """scores""": 0.9_9_6_7},
                {"""mask""": {"""hash""": """453c7844bd""", """shape""": (480, 640)}, """scores""": 0.9_9_3},
                {"""mask""": {"""hash""": """3d44f2926d""", """shape""": (480, 640)}, """scores""": 0.9_9_0_9},
                {"""mask""": {"""hash""": """64033ddc3f""", """shape""": (480, 640)}, """scores""": 0.9_8_7_9},
                {"""mask""": {"""hash""": """801064ff79""", """shape""": (480, 640)}, """scores""": 0.9_8_3_4},
                {"""mask""": {"""hash""": """6172f276ef""", """shape""": (480, 640)}, """scores""": 0.9_7_1_6},
                {"""mask""": {"""hash""": """b49e60e084""", """shape""": (480, 640)}, """scores""": 0.9_6_1_2},
                {"""mask""": {"""hash""": """a811e775fd""", """shape""": (480, 640)}, """scores""": 0.9_5_9_9},
                {"""mask""": {"""hash""": """a6a8ebcf4b""", """shape""": (480, 640)}, """scores""": 0.9_5_5_2},
                {"""mask""": {"""hash""": """9d8257e080""", """shape""": (480, 640)}, """scores""": 0.9_5_3_2},
                {"""mask""": {"""hash""": """32de6454a8""", """shape""": (480, 640)}, """scores""": 0.9_5_1_6},
                {"""mask""": {"""hash""": """af3d4af2c8""", """shape""": (480, 640)}, """scores""": 0.9_4_9_9},
                {"""mask""": {"""hash""": """3c6db475fb""", """shape""": (480, 640)}, """scores""": 0.9_4_8_3},
                {"""mask""": {"""hash""": """c290813fb9""", """shape""": (480, 640)}, """scores""": 0.9_4_6_4},
                {"""mask""": {"""hash""": """b6f0b8f606""", """shape""": (480, 640)}, """scores""": 0.9_4_3},
                {"""mask""": {"""hash""": """92ce16bfdf""", """shape""": (480, 640)}, """scores""": 0.9_4_3},
                {"""mask""": {"""hash""": """c749b25868""", """shape""": (480, 640)}, """scores""": 0.9_4_0_8},
                {"""mask""": {"""hash""": """efb6cab859""", """shape""": (480, 640)}, """scores""": 0.9_3_3_5},
                {"""mask""": {"""hash""": """1ff2eafb30""", """shape""": (480, 640)}, """scores""": 0.9_3_2_6},
                {"""mask""": {"""hash""": """788b798e24""", """shape""": (480, 640)}, """scores""": 0.9_2_6_2},
                {"""mask""": {"""hash""": """abea804f0e""", """shape""": (480, 640)}, """scores""": 0.8_9_9_9},
                {"""mask""": {"""hash""": """7b9e8ddb73""", """shape""": (480, 640)}, """scores""": 0.8_9_8_6},
                {"""mask""": {"""hash""": """cd24047c8a""", """shape""": (480, 640)}, """scores""": 0.8_9_8_4},
                {"""mask""": {"""hash""": """6943e6bcbd""", """shape""": (480, 640)}, """scores""": 0.8_8_7_3},
                {"""mask""": {"""hash""": """b5f47c9191""", """shape""": (480, 640)}, """scores""": 0.8_8_7_1}
            ]    ,	)
        # fmt: on


  @require_torch
  @slow
  def 						A__		(   self   )						->   List[Any]:



        """simple docstring"""






        UpperCamelCase       						=      """facebook/sam-vit-huge"""
        UpperCamelCase       						=      pipeline("""mask-generation"""    ,	model=_SCREAMING_SNAKE_CASE   )

        UpperCamelCase       						=      image_segmenter(
            """http://images.cocodataset.org/val2017/000000039769.jpg"""    ,	pred_iou_thresh=1    ,	points_per_batch=256   )

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

        self.assertEqual(
            nested_simplify(_SCREAMING_SNAKE_CASE    ,	decimals=4   )    ,	[
                {"""mask""": {"""hash""": """115ad19f5f""", """shape""": (480, 640)}, """scores""": 1.0_4_4_4},
                {"""mask""": {"""hash""": """6affa964c6""", """shape""": (480, 640)}, """scores""": 1.0_2_1_0},
                {"""mask""": {"""hash""": """dfe28a0388""", """shape""": (480, 640)}, """scores""": 1.0_1_6_7},
                {"""mask""": {"""hash""": """c0a5f4a318""", """shape""": (480, 640)}, """scores""": 1.0_1_3_2},
                {"""mask""": {"""hash""": """fe8065c197""", """shape""": (480, 640)}, """scores""": 1.0_0_5_3},
            ]    ,	)








'''simple docstring'''

import fire

from utils import calculate_rouge, save_json







def 					lowercase__				(   __UpperCamelCase	,		__UpperCamelCase	,		__UpperCamelCase=None	,		**__UpperCamelCase					)->				int:
      UpperCamelCase       						=      [x.strip() for x in open(__UpperCamelCase					).readlines()]
      UpperCamelCase       						=      [x.strip() for x in open(__UpperCamelCase					).readlines()][: len(__UpperCamelCase					)]
      UpperCamelCase       						=      calculate_rouge(__UpperCamelCase	,		__UpperCamelCase	,		**__UpperCamelCase					)
      if save_path is not None:
            save_json(__UpperCamelCase	,		__UpperCamelCase	,		indent=__UpperCamelCase					)
      return metrics  # these print nicely


if __name__ == "__main__":
     fire.Fire(calculate_rouge_path)
