from math import sqrt






def 				__lowerCamelCase		(						lowerCAmelCase__     ):
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ) and (
           number >= 0
       ), "'number' must been an int and positive"

       lowerCAmelCase__					     = True

       # 0 and 1 are none primes.
       if number <= 1:
              lowerCAmelCase__					     = False

       for divisor in range(2     ,  int(round(sqrt(lowerCAmelCase__     )     )     ) + 1     ):
              # if 'number' divisible by 'divisor' then sets 'status'
              # of false and break up the loop.
              if number % divisor == 0:
                     lowerCAmelCase__					     = False
                     break

    # precondition
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ), "'status' must been from type bool"

       return status






def 				__lowerCamelCase		(						lowerCAmelCase__     ):
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ) and (n > 2), "'N' must been an int and > 2"

       # beginList: contains all natural numbers from 2 up to N
       lowerCAmelCase__					     = list(range(2     ,  n + 1     )     )

       lowerCAmelCase__					     = []  # this list will be returns.

       # actual sieve of erathostenes
       for i in range(len(lowerCAmelCase__     )     ):
              for j in range(i + 1     ,  len(lowerCAmelCase__     )     ):
                     if (begin_list[i] != 0) and (begin_list[j] % begin_list[i] == 0):
                            lowerCAmelCase__					     = 0

    # filters actual prime numbers.
       lowerCAmelCase__					     = [x for x in begin_list if x != 0]

       # precondition
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ), "'ans' must been from type list"

       return ans






def 				__lowerCamelCase		(						lowerCAmelCase__     ):
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ) and (n > 2), "'N' must been an int and > 2"

       lowerCAmelCase__					     = []

       # iterates over all numbers between 2 up to N+1
       # if a number is prime then appends to list 'ans'
       for number in range(2     ,  n + 1     ):
              if is_prime(lowerCAmelCase__     ):
                     ans.append(lowerCAmelCase__     )

    # precondition
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ), "'ans' must been from type list"

       return ans






def 				__lowerCamelCase		(						lowerCAmelCase__     ):
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ) and number >= 0, "'number' must been an int and >= 0"

       lowerCAmelCase__					     = []  # this list will be returns of the function.

       # potential prime number factors.

       lowerCAmelCase__					     = 2

       lowerCAmelCase__					     = number

       if number == 0 or number == 1:
              ans.append(lowerCAmelCase__     )

       # if 'number' not prime then builds the prime factorization of 'number'
       elif not is_prime(lowerCAmelCase__     ):
              while quotient != 1:
                     if is_prime(lowerCAmelCase__     ) and (quotient % factor == 0):
                            ans.append(lowerCAmelCase__     )
                            quotient /= factor
                     else:
                            factor += 1

       else:
              ans.append(lowerCAmelCase__     )

       # precondition
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ), "'ans' must been from type list"

       return ans






def 				__lowerCamelCase		(						lowerCAmelCase__     ):
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ) and (
           number >= 0
       ), "'number' bust been an int and >= 0"

       lowerCAmelCase__					     = 0

       # prime factorization of 'number'
       lowerCAmelCase__					     = prime_factorization(lowerCAmelCase__     )

       lowerCAmelCase__					     = max(lowerCAmelCase__     )

       # precondition
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ), "'ans' must been from type int"

       return ans






def 				__lowerCamelCase		(						lowerCAmelCase__     ):
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ) and (
           number >= 0
       ), "'number' bust been an int and >= 0"

       lowerCAmelCase__					     = 0

       # prime factorization of 'number'
       lowerCAmelCase__					     = prime_factorization(lowerCAmelCase__     )

       lowerCAmelCase__					     = min(lowerCAmelCase__     )

       # precondition
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ), "'ans' must been from type int"

       return ans






def 				__lowerCamelCase		(						lowerCAmelCase__     ):
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ), "'number' must been an int"
       assert isinstance(number % 2 == 0     ,  lowerCAmelCase__     ), "compare bust been from type bool"

       return number % 2 == 0






def 				__lowerCamelCase		(						lowerCAmelCase__     ):
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ), "'number' must been an int"
       assert isinstance(number % 2 != 0     ,  lowerCAmelCase__     ), "compare bust been from type bool"

       return number % 2 != 0






def 				__lowerCamelCase		(						lowerCAmelCase__     ):
       assert (
           isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ) and (number > 2) and is_even(lowerCAmelCase__     )
       ), "'number' must been an int, even and > 2"

       lowerCAmelCase__					     = []  # this list will returned

       # creates a list of prime numbers between 2 up to 'number'
       lowerCAmelCase__					     = get_prime_numbers(lowerCAmelCase__     )
       lowerCAmelCase__					     = len(lowerCAmelCase__     )

       # run variable for while-loops.
       lowerCAmelCase__					     = 0
       lowerCAmelCase__					     = None

       # exit variable. for break up the loops
       lowerCAmelCase__					     = True

       while i < len_pn and loop:
              lowerCAmelCase__					     = i + 1

              while j < len_pn and loop:
                     if prime_numbers[i] + prime_numbers[j] == number:
                            lowerCAmelCase__					     = False
                            ans.append(prime_numbers[i]     )
                            ans.append(prime_numbers[j]     )

                     j += 1

              i += 1

       # precondition
       assert (
           isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     )
           and (len(lowerCAmelCase__     ) == 2)
           and (ans[0] + ans[1] == number)
           and is_prime(ans[0]     )
           and is_prime(ans[1]     )
       ), "'ans' must contains two primes. And sum of elements must been eq 'number'"

       return ans






def 				__lowerCamelCase		(						lowerCAmelCase__     ,  lowerCAmelCase__     ):
       assert (
           isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     )
           and isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     )
           and (numbera >= 0)
           and (numbera >= 0)
       ), "'number1' and 'number2' must been positive integer."

       lowerCAmelCase__					     = 0

       while numbera != 0:
              lowerCAmelCase__					     = numbera % numbera
              lowerCAmelCase__					     = numbera
              lowerCAmelCase__					     = rest

       # precondition
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ) and (
           numbera >= 0
       ), "'number' must been from type int and positive"

       return numbera






def 				__lowerCamelCase		(						lowerCAmelCase__     ,  lowerCAmelCase__     ):
       assert (
           isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     )
           and isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     )
           and (numbera >= 1)
           and (numbera >= 1)
       ), "'number1' and 'number2' must been positive integer."

       lowerCAmelCase__					     = 1  # actual answer that will be return.

       # for kgV (x,1)
       if numbera > 1 and numbera > 1:
              # builds the prime factorization of 'number1' and 'number2'
              lowerCAmelCase__					     = prime_factorization(lowerCAmelCase__     )
              lowerCAmelCase__					     = prime_factorization(lowerCAmelCase__     )

       elif numbera == 1 or numbera == 1:
              lowerCAmelCase__					     = []
              lowerCAmelCase__					     = []
              lowerCAmelCase__					     = max(lowerCAmelCase__     ,  lowerCAmelCase__     )

       lowerCAmelCase__					     = 0
       lowerCAmelCase__					     = 0

       lowerCAmelCase__					     = []  # captured numbers int both 'primeFac1' and 'primeFac2'

       # iterates through primeFac1
       for n in prime_fac_a:
              if n not in done:
                     if n in prime_fac_a:
                            lowerCAmelCase__					     = prime_fac_a.count(lowerCAmelCase__     )
                            lowerCAmelCase__					     = prime_fac_a.count(lowerCAmelCase__     )

                            for _ in range(max(lowerCAmelCase__     ,  lowerCAmelCase__     )     ):
                                   ans *= n

                     else:
                            lowerCAmelCase__					     = prime_fac_a.count(lowerCAmelCase__     )

                            for _ in range(lowerCAmelCase__     ):
                                   ans *= n

                     done.append(lowerCAmelCase__     )

    # iterates through primeFac2
       for n in prime_fac_a:
              if n not in done:
                     lowerCAmelCase__					     = prime_fac_a.count(lowerCAmelCase__     )

                     for _ in range(lowerCAmelCase__     ):
                            ans *= n

                     done.append(lowerCAmelCase__     )

    # precondition
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ) and (
           ans >= 0
       ), "'ans' must been from type int and positive"

       return ans






def 				__lowerCamelCase		(						lowerCAmelCase__     ):
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ) and (n >= 0), "'number' must been a positive int"

       lowerCAmelCase__					     = 0
       lowerCAmelCase__					     = 2  # this variable holds the answer

       while index < n:
              index += 1

              ans += 1  # counts to the next number

              # if ans not prime then
              # runs to the next prime number.
              while not is_prime(lowerCAmelCase__     ):
                     ans += 1

    # precondition
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ) and is_prime(
           lowerCAmelCase__     ), "'ans' must been a prime number and from type int"

       return ans






def 				__lowerCamelCase		(						lowerCAmelCase__     ,  lowerCAmelCase__     ):
       assert (
           is_prime(lowerCAmelCase__     ) and is_prime(lowerCAmelCase__     ) and (p_number_a < p_number_a)
       ), "The arguments must been prime numbers and 'pNumber1' < 'pNumber2'"

       lowerCAmelCase__					     = p_number_a + 1  # jump to the next number

       lowerCAmelCase__					     = []  # this list will be returns.

       # if number is not prime then
       # fetch the next prime number.
       while not is_prime(lowerCAmelCase__     ):
              number += 1

       while number < p_number_a:
              ans.append(lowerCAmelCase__     )

              number += 1

              # fetch the next prime number.
              while not is_prime(lowerCAmelCase__     ):
                     number += 1

    # precondition
       assert (
           isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     )
           and ans[0] != p_number_a
           and ans[len(lowerCAmelCase__     ) - 1] != p_number_a
       ), "'ans' must been a list without the arguments"

       # 'ans' contains not 'pNumber1' and 'pNumber2' !
       return ans






def 				__lowerCamelCase		(						lowerCAmelCase__     ):
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ) and (n >= 1), "'n' must been int and >= 1"

       lowerCAmelCase__					     = []  # will be returned.

       for divisor in range(1     ,  n + 1     ):
              if n % divisor == 0:
                     ans.append(lowerCAmelCase__     )

    # precondition
       assert ans[0] == 1 and ans[len(lowerCAmelCase__     ) - 1] == n, "Error in function getDivisiors(...)"

       return ans






def 				__lowerCamelCase		(						lowerCAmelCase__     ):
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ) and (
           number > 1
       ), "'number' must been an int and >= 1"

       lowerCAmelCase__					     = get_divisors(lowerCAmelCase__     )

       # precondition
       assert (
           isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     )
           and (divisors[0] == 1)
           and (divisors[len(lowerCAmelCase__     ) - 1] == number)
       ), "Error in help-function getDivisiors(...)"

       # summed all divisors up to 'number' (exclusive), hence [:-1]
       return sum(divisors[:-1]     ) == number






def 				__lowerCamelCase		(						lowerCAmelCase__     ,  lowerCAmelCase__     ):
       assert (
           isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     )
           and isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     )
           and (denominator != 0)
       ), "The arguments must been from type int and 'denominator' != 0"

       # build the greatest common divisor of numerator and denominator.
       lowerCAmelCase__					     = gcd(abs(lowerCAmelCase__     )     ,  abs(lowerCAmelCase__     )     )

       # precondition
       assert (
           isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     )
           and (numerator % gcd_of_fraction == 0)
           and (denominator % gcd_of_fraction == 0)
       ), "Error in function gcd(...,...)"

       return (numerator // gcd_of_fraction, denominator // gcd_of_fraction)






def 				__lowerCamelCase		(						lowerCAmelCase__     ):
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ) and (n >= 0), "'n' must been a int and >= 0"

       lowerCAmelCase__					     = 1  # this will be return.

       for factor in range(1     ,  n + 1     ):
              ans *= factor

       return ans






def 				__lowerCamelCase		(						lowerCAmelCase__     ):
       assert isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ) and (n >= 0), "'n' must been an int and >= 0"

       lowerCAmelCase__					     = 0
       lowerCAmelCase__					     = 1
       lowerCAmelCase__					     = 1  # this will be return

       for _ in range(n - 1     ):
              lowerCAmelCase__					     = ans
              ans += fiba
              lowerCAmelCase__					     = tmp

       return ans

from copy import deepcopy
from typing import Optional, Union

import numpy as np

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available


if is_torch_available():
    import torch

if is_tf_available():
    import tensorflow as tf
class     a_			(						SCREAMING_SNAKE_CASE						):






 '''simple docstring'''






 UpperCAmelCase_     			= ['image_processor']
 UpperCAmelCase_     			= 'SamImageProcessor'




 def __init__(      self :  Tuple      ,   lowercase__ :  Dict):







        '''simple docstring'''



        super().__init__(lowercase__)
        lowerCAmelCase__					     = self.image_processor
        lowerCAmelCase__					     = -10
        lowerCAmelCase__					     = self.image_processor.size['longest_edge']




 def __call__(      self :  List[Any]      ,   lowercase__ :  Optional[int]=None      ,   lowercase__ :  Any=None      ,   lowercase__ :  Tuple=None      ,   lowercase__ :  List[str]=None      ,   lowercase__ :  Optional[Union[str, TensorType]] = None      ,   **lowercase__ :  Dict      ,   ):







        '''simple docstring'''



        lowerCAmelCase__					     = self.image_processor(
            lowercase__      ,   return_tensors=lowercase__      ,   **lowercase__      ,   )

        # pop arguments that are not used in the foward but used nevertheless
        lowerCAmelCase__					     = encoding_image_processor['original_sizes']

        if hasattr(lowercase__      ,   'numpy'):  # Checks if Torch or TF tensor
               lowerCAmelCase__					     = original_sizes.numpy()

        lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__					     = self._check_and_preprocess_points(
            input_points=lowercase__      ,   input_labels=lowercase__      ,   input_boxes=lowercase__      ,   )

        lowerCAmelCase__					     = self._normalize_and_convert(
            lowercase__      ,   lowercase__      ,   input_points=lowercase__      ,   input_labels=lowercase__      ,   input_boxes=lowercase__      ,   return_tensors=lowercase__      ,   )

        return encoding_image_processor




 def 		__snake_case						(      self :  Optional[Any]      ,   lowercase__ :  List[str]      ,   lowercase__ :  List[str]      ,   lowercase__ :  str=None      ,   lowercase__ :  Optional[int]=None      ,   lowercase__ :  str=None      ,   lowercase__ :  Optional[Any]="pt"      ,   ):







        '''simple docstring'''



        if input_points is not None:
               if len(lowercase__) != len(lowercase__):
                      lowerCAmelCase__					     = [
                          self._normalize_coordinates(self.target_size      ,   lowercase__      ,   original_sizes[0]) for point in input_points
                      ]
               else:
                      lowerCAmelCase__					     = [
                          self._normalize_coordinates(self.target_size      ,   lowercase__      ,   lowercase__)
                          for point, original_size in zip(lowercase__      ,   lowercase__)
                      ]
               # check that all arrays have the same shape
               if not all(point.shape == input_points[0].shape for point in input_points):
                      if input_labels is not None:
                             lowerCAmelCase__     , lowerCAmelCase__					     = self._pad_points_and_labels(lowercase__      ,   lowercase__)

               lowerCAmelCase__					     = np.array(lowercase__)

        if input_labels is not None:
               lowerCAmelCase__					     = np.array(lowercase__)

        if input_boxes is not None:
               if len(lowercase__) != len(lowercase__):
                      lowerCAmelCase__					     = [
                          self._normalize_coordinates(self.target_size      ,   lowercase__      ,   original_sizes[0]      ,   is_bounding_box=lowercase__)
                          for box in input_boxes
                      ]
               else:
                      lowerCAmelCase__					     = [
                          self._normalize_coordinates(self.target_size      ,   lowercase__      ,   lowercase__      ,   is_bounding_box=lowercase__)
                          for box, original_size in zip(lowercase__      ,   lowercase__)
                      ]
               lowerCAmelCase__					     = np.array(lowercase__)

        if input_boxes is not None:
               if return_tensors == "pt":
                      lowerCAmelCase__					     = torch.from_numpy(lowercase__)
                      # boxes batch size of 1 by default
                      lowerCAmelCase__					     = input_boxes.unsqueeze(1) if len(input_boxes.shape) != 3 else input_boxes
               elif return_tensors == "tf":
                      lowerCAmelCase__					     = tf.convert_to_tensor(lowercase__)
                      # boxes batch size of 1 by default
                      lowerCAmelCase__					     = tf.expand_dims(lowercase__      ,   1) if len(input_boxes.shape) != 3 else input_boxes
               encoding_image_processor.update({'input_boxes': input_boxes})
        if input_points is not None:
               if return_tensors == "pt":
                      lowerCAmelCase__					     = torch.from_numpy(lowercase__)
                      # point batch size of 1 by default
                      lowerCAmelCase__					     = input_points.unsqueeze(1) if len(input_points.shape) != 4 else input_points
               elif return_tensors == "tf":
                      lowerCAmelCase__					     = tf.convert_to_tensor(lowercase__)
                      # point batch size of 1 by default
                      lowerCAmelCase__					     = tf.expand_dims(lowercase__      ,   1) if len(input_points.shape) != 4 else input_points
               encoding_image_processor.update({'input_points': input_points})
        if input_labels is not None:
               if return_tensors == "pt":
                      lowerCAmelCase__					     = torch.from_numpy(lowercase__)
                      # point batch size of 1 by default
                      lowerCAmelCase__					     = input_labels.unsqueeze(1) if len(input_labels.shape) != 3 else input_labels
               elif return_tensors == "tf":
                      lowerCAmelCase__					     = tf.convert_to_tensor(lowercase__)
                      # point batch size of 1 by default
                      lowerCAmelCase__					     = tf.expand_dims(lowercase__      ,   1) if len(input_labels.shape) != 3 else input_labels
               encoding_image_processor.update({'input_labels': input_labels})

        return encoding_image_processor




 def 		__snake_case						(      self :  str      ,   lowercase__ :  Optional[int]      ,   lowercase__ :  Optional[Any]):







        '''simple docstring'''



        lowerCAmelCase__					     = max([point.shape[0] for point in input_points])
        lowerCAmelCase__					     = []
        for i, point in enumerate(lowercase__):
               if point.shape[0] != expected_nb_points:
                      lowerCAmelCase__					     = np.concatenate(
                          [point, np.zeros((expected_nb_points - point.shape[0], 2)) + self.point_pad_value]      ,   axis=0)
                      lowerCAmelCase__					     = np.append(input_labels[i]      ,   [self.point_pad_value])
               processed_input_points.append(lowercase__)
        lowerCAmelCase__					     = processed_input_points
        return input_points, input_labels




 def 		__snake_case						(      self :  Optional[Any]      ,   lowercase__ :  int      ,   lowercase__ :  np.ndarray      ,   lowercase__ :  int      ,   lowercase__ :  Optional[Any]=False):







        '''simple docstring'''



        lowerCAmelCase__     , lowerCAmelCase__					     = original_size
        lowerCAmelCase__     , lowerCAmelCase__					     = self.image_processor._get_preprocess_shape(lowercase__      ,   longest_edge=lowercase__)
        lowerCAmelCase__					     = deepcopy(lowercase__).astype(lowercase__)

        if is_bounding_box:
               lowerCAmelCase__					     = coords.reshape(-1      ,   2      ,   2)

        lowerCAmelCase__					     = coords[..., 0] * (new_w / old_w)
        lowerCAmelCase__					     = coords[..., 1] * (new_h / old_h)

        if is_bounding_box:
               lowerCAmelCase__					     = coords.reshape(-1      ,   4)

        return coords




 def 		__snake_case						(      self :  Dict      ,   lowercase__ :  Optional[Any]=None      ,   lowercase__ :  Tuple=None      ,   lowercase__ :  int=None      ,   ):







        '''simple docstring'''



        if input_points is not None:
               if hasattr(lowercase__      ,   'numpy'):  # Checks for TF or Torch tensor
                      lowerCAmelCase__					     = input_points.numpy().tolist()

               if not isinstance(lowercase__      ,   lowercase__) or not isinstance(input_points[0]      ,   lowercase__):
                      raise ValueError('Input points must be a list of list of floating points.')
               lowerCAmelCase__					     = [np.array(lowercase__) for input_point in input_points]
        else:
               lowerCAmelCase__					     = None

        if input_labels is not None:
               if hasattr(lowercase__      ,   'numpy'):
                      lowerCAmelCase__					     = input_labels.numpy().tolist()

               if not isinstance(lowercase__      ,   lowercase__) or not isinstance(input_labels[0]      ,   lowercase__):
                      raise ValueError('Input labels must be a list of list integers.')
               lowerCAmelCase__					     = [np.array(lowercase__) for label in input_labels]
        else:
               lowerCAmelCase__					     = None

        if input_boxes is not None:
               if hasattr(lowercase__      ,   'numpy'):
                      lowerCAmelCase__					     = input_boxes.numpy().tolist()

               if (
                   not isinstance(lowercase__      ,   lowercase__)
                   or not isinstance(input_boxes[0]      ,   lowercase__)
                   or not isinstance(input_boxes[0][0]      ,   lowercase__)
               ):
                      raise ValueError('Input boxes must be a list of list of list of floating points.')
               lowerCAmelCase__					     = [np.array(lowercase__).astype(np.floataa) for box in input_boxes]
        else:
               lowerCAmelCase__					     = None

        return input_points, input_labels, input_boxes




 @property
 def 		__snake_case						(      self :  List[Any]):







        '''simple docstring'''



        lowerCAmelCase__					     = self.image_processor.model_input_names
        return list(dict.fromkeys(lowercase__))




 def 		__snake_case						(      self :  int      ,   *lowercase__ :  int      ,   **lowercase__ :  int):







        '''simple docstring'''



        return self.image_processor.post_process_masks(*lowercase__      ,   **lowercase__)
