





"""simple docstring"""





from itertools import product

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->Any:





  """simple docstring"""


  lowerCAmelCase__     :Dict											=				k_size // 2
  lowerCAmelCase__				,							lowerCAmelCase__     :Tuple											=				mgrid[0 - center : k_size - center, 0 - center : k_size - center]
  lowerCAmelCase__     :List[Any]											=				1 / (2 * pi * sigma) * exp(-(square(_SCREAMING_SNAKE_CASE     ) + square(_SCREAMING_SNAKE_CASE     )) / (2 * square(_SCREAMING_SNAKE_CASE     ))     )
  return g
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->Optional[int]:





  """simple docstring"""


  lowerCAmelCase__				,							lowerCAmelCase__     :Optional[Any]											=				image.shape[0], image.shape[1]
  # dst image height and width
  lowerCAmelCase__     :Union[str, Any]											=				height - k_size + 1
  lowerCAmelCase__     :Optional[Any]											=				width - k_size + 1

  # im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
  lowerCAmelCase__     :Optional[int]											=				zeros((dst_height * dst_width, k_size * k_size)     )
  lowerCAmelCase__     :Tuple											=				0
  for i, j in product(range(_SCREAMING_SNAKE_CASE     )	,  range(_SCREAMING_SNAKE_CASE     )     ):
    lowerCAmelCase__     :Union[str, Any]											=				ravel(image[i : i + k_size, j : j + k_size]     )
    lowerCAmelCase__     :Optional[Any]											=				window
    row += 1

  #  turn the kernel into shape(k*k, 1)
  lowerCAmelCase__     :str											=				gen_gaussian_kernel(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )
  lowerCAmelCase__     :str											=				ravel(_SCREAMING_SNAKE_CASE     )

  # reshape and get the dst image
  lowerCAmelCase__     :Optional[Any]											=				dot(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     ).reshape(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     ).astype(_SCREAMING_SNAKE_CASE     )

  return dst


if __name__ == "__main__":
  # read original image
  __A											=						imread(R"""../image_data/lena.jpg""")
  # turn image in gray scale value
  __A											=						cvtColor(img, COLOR_BGR2GRAY)

  # get values with two different mask size
  __A											=						gaussian_filter(gray, 3, sigma=1)
  __A											=						gaussian_filter(gray, 5, sigma=0.8)

  # show result images
  imshow("""gaussian filter with 3x3 mask""", gaussianaxa)
  imshow("""gaussian filter with 5x5 mask""", gaussianaxa)
  waitKey()







"""simple docstring"""





import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
  from PIL import Image

  from transformers import (
      AutoProcessor,
      BertTokenizerFast,
      BlipImageProcessor,
      GPTaTokenizer,
      InstructBlipProcessor,
      PreTrainedTokenizerFast,
  )






@require_vision
class    _lowerCAmelCase  (	unittest.TestCase			):
       """simple docstring"""




       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Any											=				tempfile.mkdtemp()

         lowerCAmelCase__     :List[Any]											=				BlipImageProcessor()
         lowerCAmelCase__     :Union[str, Any]											=				GPTaTokenizer.from_pretrained('hf-internal-testing/tiny-random-GPT2Model' )
         lowerCAmelCase__     :Union[str, Any]											=				BertTokenizerFast.from_pretrained('hf-internal-testing/tiny-random-bert' )

         lowerCAmelCase__     :List[str]											=				InstructBlipProcessor(__UpperCAmelCase       ,					__UpperCAmelCase       ,					__UpperCAmelCase )

         processor.save_pretrained(self.tmpdirname )






       def 	snake_case		(       self       ,					**__UpperCAmelCase ):



         '''simple docstring'''

         return AutoProcessor.from_pretrained(self.tmpdirname       ,					**__UpperCAmelCase ).tokenizer






       def 	snake_case		(       self       ,					**__UpperCAmelCase ):



         '''simple docstring'''

         return AutoProcessor.from_pretrained(self.tmpdirname       ,					**__UpperCAmelCase ).image_processor






       def 	snake_case		(       self       ,					**__UpperCAmelCase ):



         '''simple docstring'''

         return AutoProcessor.from_pretrained(self.tmpdirname       ,					**__UpperCAmelCase ).qformer_tokenizer






       def 	snake_case		(       self ):



         '''simple docstring'''

         shutil.rmtree(self.tmpdirname )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Optional[Any]											=				[np.random.randint(2_5_5       ,					size=(3, 3_0, 4_0_0)       ,					dtype=np.uinta )]

         lowerCAmelCase__     :Dict											=				[Image.fromarray(np.moveaxis(__UpperCAmelCase       ,					0       ,					-1 ) ) for x in image_inputs]

         return image_inputs






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :List[str]											=				InstructBlipProcessor(
             tokenizer=self.get_tokenizer()       ,					image_processor=self.get_image_processor()       ,					qformer_tokenizer=self.get_qformer_tokenizer()       ,					)
         processor.save_pretrained(self.tmpdirname )

         lowerCAmelCase__     :Tuple											=				self.get_tokenizer(bos_token='(BOS)'       ,					eos_token='(EOS)' )
         lowerCAmelCase__     :str											=				self.get_image_processor(do_normalize=__UpperCAmelCase       ,					padding_value=1.0 )

         lowerCAmelCase__     :Dict											=				InstructBlipProcessor.from_pretrained(
             self.tmpdirname       ,					bos_token='(BOS)'       ,					eos_token='(EOS)'       ,					do_normalize=__UpperCAmelCase       ,					padding_value=1.0 )

         self.assertEqual(processor.tokenizer.get_vocab()       ,					tokenizer_add_kwargs.get_vocab() )
         self.assertIsInstance(processor.tokenizer       ,					__UpperCAmelCase )

         self.assertEqual(processor.image_processor.to_json_string()       ,					image_processor_add_kwargs.to_json_string() )
         self.assertIsInstance(processor.image_processor       ,					__UpperCAmelCase )
         self.assertIsInstance(processor.qformer_tokenizer       ,					__UpperCAmelCase )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Optional[Any]											=				self.get_image_processor()
         lowerCAmelCase__     :List[Any]											=				self.get_tokenizer()
         lowerCAmelCase__     :Optional[int]											=				self.get_qformer_tokenizer()

         lowerCAmelCase__     :str											=				InstructBlipProcessor(
             tokenizer=__UpperCAmelCase       ,					image_processor=__UpperCAmelCase       ,					qformer_tokenizer=__UpperCAmelCase )

         lowerCAmelCase__     :Dict											=				self.prepare_image_inputs()

         lowerCAmelCase__     :List[str]											=				image_processor(__UpperCAmelCase       ,					return_tensors='np' )
         lowerCAmelCase__     :Optional[Any]											=				processor(images=__UpperCAmelCase       ,					return_tensors='np' )

         for key in input_feat_extract.keys():
           self.assertAlmostEqual(input_feat_extract[key].sum()       ,					input_processor[key].sum()       ,					delta=1E-2 )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Union[str, Any]											=				self.get_image_processor()
         lowerCAmelCase__     :Optional[int]											=				self.get_tokenizer()
         lowerCAmelCase__     :Optional[int]											=				self.get_qformer_tokenizer()

         lowerCAmelCase__     :Any											=				InstructBlipProcessor(
             tokenizer=__UpperCAmelCase       ,					image_processor=__UpperCAmelCase       ,					qformer_tokenizer=__UpperCAmelCase )

         lowerCAmelCase__     :Optional[int]											=				'lower newer'

         lowerCAmelCase__     :Dict											=				processor(text=__UpperCAmelCase )

         lowerCAmelCase__     :Union[str, Any]											=				tokenizer(__UpperCAmelCase       ,					return_token_type_ids=__UpperCAmelCase )
         lowerCAmelCase__     :Tuple											=				qformer_tokenizer(__UpperCAmelCase       ,					return_token_type_ids=__UpperCAmelCase )

         for key in encoded_tokens.keys():
           self.assertListEqual(encoded_tokens[key]       ,					encoded_processor[key] )

         for key in encoded_tokens_qformer.keys():
           self.assertListEqual(encoded_tokens_qformer[key]       ,					encoded_processor['qformer_' + key] )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Optional[Any]											=				self.get_image_processor()
         lowerCAmelCase__     :Optional[int]											=				self.get_tokenizer()
         lowerCAmelCase__     :str											=				self.get_qformer_tokenizer()

         lowerCAmelCase__     :Dict											=				InstructBlipProcessor(
             tokenizer=__UpperCAmelCase       ,					image_processor=__UpperCAmelCase       ,					qformer_tokenizer=__UpperCAmelCase )

         lowerCAmelCase__     :Union[str, Any]											=				'lower newer'
         lowerCAmelCase__     :Dict											=				self.prepare_image_inputs()

         lowerCAmelCase__     :Tuple											=				processor(text=__UpperCAmelCase       ,					images=__UpperCAmelCase )

         self.assertListEqual(
             list(inputs.keys() )       ,					['input_ids', 'attention_mask', 'qformer_input_ids', 'qformer_attention_mask', 'pixel_values']       ,					)

         # test if it raises when no input is passed
         with pytest.raises(__UpperCAmelCase ):
           processor()






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Tuple											=				self.get_image_processor()
         lowerCAmelCase__     :Dict											=				self.get_tokenizer()
         lowerCAmelCase__     :Optional[int]											=				self.get_qformer_tokenizer()

         lowerCAmelCase__     :int											=				InstructBlipProcessor(
             tokenizer=__UpperCAmelCase       ,					image_processor=__UpperCAmelCase       ,					qformer_tokenizer=__UpperCAmelCase )

         lowerCAmelCase__     :List[str]											=				[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

         lowerCAmelCase__     :Tuple											=				processor.batch_decode(__UpperCAmelCase )
         lowerCAmelCase__     :Optional[int]											=				tokenizer.batch_decode(__UpperCAmelCase )

         self.assertListEqual(__UpperCAmelCase       ,					__UpperCAmelCase )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Tuple											=				self.get_image_processor()
         lowerCAmelCase__     :Optional[int]											=				self.get_tokenizer()
         lowerCAmelCase__     :Dict											=				self.get_qformer_tokenizer()

         lowerCAmelCase__     :Optional[Any]											=				InstructBlipProcessor(
             tokenizer=__UpperCAmelCase       ,					image_processor=__UpperCAmelCase       ,					qformer_tokenizer=__UpperCAmelCase )

         lowerCAmelCase__     :Optional[int]											=				'lower newer'
         lowerCAmelCase__     :Optional[int]											=				self.prepare_image_inputs()

         lowerCAmelCase__     :int											=				processor(text=__UpperCAmelCase       ,					images=__UpperCAmelCase )

         self.assertListEqual(
             list(inputs.keys() )       ,					['input_ids', 'attention_mask', 'qformer_input_ids', 'qformer_attention_mask', 'pixel_values']       ,					)
