




'''simple docstring'''



import unittest

import numpy as np

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available

from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs


if is_torch_available():
     import torch

if is_vision_available():
     from PIL import Image

     from transformers import MobileViTImageProcessor





class      lowerCAmelCase (			unittest.TestCase):


       def __init__( self     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE=7     ,	__SCREAMING_SNAKE_CASE=3     ,	__SCREAMING_SNAKE_CASE=18     ,	__SCREAMING_SNAKE_CASE=30     ,	__SCREAMING_SNAKE_CASE=400     ,	__SCREAMING_SNAKE_CASE=True     ,	__SCREAMING_SNAKE_CASE=None     ,	__SCREAMING_SNAKE_CASE=True     ,	__SCREAMING_SNAKE_CASE=None     ,	__SCREAMING_SNAKE_CASE=True     ,	)   ->	Tuple:



            '''simple docstring'''




            __snake_case            =	size if size is not None else {'''shortest_edge''': 20}
            __snake_case            =	crop_size if crop_size is not None else {'''height''': 18, '''width''': 18}
            __snake_case            =	parent
            __snake_case            =	batch_size
            __snake_case            =	num_channels
            __snake_case            =	image_size
            __snake_case            =	min_resolution
            __snake_case            =	max_resolution
            __snake_case            =	do_resize
            __snake_case            =	size
            __snake_case            =	do_center_crop
            __snake_case            =	crop_size
            __snake_case            =	do_flip_channel_order




       def    lowerCAmelCase   ( self	)   ->	Union[str, Any]:



            '''simple docstring'''




            return {
                "do_resize": self.do_resize,
                "size": self.size,
                "do_center_crop": self.do_center_crop,
                "crop_size": self.crop_size,
                "do_flip_channel_order": self.do_flip_channel_order,
            }





@require_torch
@require_vision
class      lowerCAmelCase (			__lowerCAmelCase					, unittest.TestCase):
       __lowercase	:   Union[str, Any]										=      MobileViTImageProcessor if is_vision_available() else None


       def    lowerCAmelCase   ( self	)   ->	str:



            '''simple docstring'''




            __snake_case            =	MobileViTImageProcessingTester(self	)


       @property
       def    lowerCAmelCase   ( self	)   ->	Optional[int]:



            '''simple docstring'''




            return self.image_processor_tester.prepare_image_processor_dict()


       def    lowerCAmelCase   ( self	)   ->	Union[str, Any]:



            '''simple docstring'''




            __snake_case            =	self.image_processing_class(**self.image_processor_dict	)
            self.assertTrue(hasattr(__SCREAMING_SNAKE_CASE     ,	'''do_resize'''	)	)
            self.assertTrue(hasattr(__SCREAMING_SNAKE_CASE     ,	'''size'''	)	)
            self.assertTrue(hasattr(__SCREAMING_SNAKE_CASE     ,	'''do_center_crop'''	)	)
            self.assertTrue(hasattr(__SCREAMING_SNAKE_CASE     ,	'''center_crop'''	)	)
            self.assertTrue(hasattr(__SCREAMING_SNAKE_CASE     ,	'''do_flip_channel_order'''	)	)


       def    lowerCAmelCase   ( self	)   ->	Optional[int]:



            '''simple docstring'''




            __snake_case            =	self.image_processing_class.from_dict(self.image_processor_dict	)
            self.assertEqual(image_processor.size     ,	{'''shortest_edge''': 20}	)
            self.assertEqual(image_processor.crop_size     ,	{'''height''': 18, '''width''': 18}	)

            __snake_case            =	self.image_processing_class.from_dict(self.image_processor_dict     ,	size=42     ,	crop_size=84	)
            self.assertEqual(image_processor.size     ,	{'''shortest_edge''': 42}	)
            self.assertEqual(image_processor.crop_size     ,	{'''height''': 84, '''width''': 84}	)


       def    lowerCAmelCase   ( self	)   ->	Optional[Any]:



            '''simple docstring'''




            pass


       def    lowerCAmelCase   ( self	)   ->	str:



            '''simple docstring'''




            __snake_case            =	self.image_processing_class(**self.image_processor_dict	)
            # create random PIL images
            __snake_case            =	prepare_image_inputs(self.image_processor_tester     ,	equal_resolution=__SCREAMING_SNAKE_CASE	)
            for image in image_inputs:
                 self.assertIsInstance(__SCREAMING_SNAKE_CASE     ,	Image.Image	)

            # Test not batched input
            __snake_case            =	image_processing(image_inputs[0]     ,	return_tensors='''pt'''	).pixel_values
            self.assertEqual(
                encoded_images.shape     ,	(
                    1,
                    self.image_processor_tester.num_channels,
                    self.image_processor_tester.crop_size['''height'''],
                    self.image_processor_tester.crop_size['''width'''],
                )     ,	)

            # Test batched
            __snake_case            =	image_processing(__SCREAMING_SNAKE_CASE     ,	return_tensors='''pt'''	).pixel_values
            self.assertEqual(
                encoded_images.shape     ,	(
                    self.image_processor_tester.batch_size,
                    self.image_processor_tester.num_channels,
                    self.image_processor_tester.crop_size['''height'''],
                    self.image_processor_tester.crop_size['''width'''],
                )     ,	)


       def    lowerCAmelCase   ( self	)   ->	Tuple:



            '''simple docstring'''




            __snake_case            =	self.image_processing_class(**self.image_processor_dict	)
            # create random numpy tensors
            __snake_case            =	prepare_image_inputs(self.image_processor_tester     ,	equal_resolution=__SCREAMING_SNAKE_CASE     ,	numpify=__SCREAMING_SNAKE_CASE	)
            for image in image_inputs:
                 self.assertIsInstance(__SCREAMING_SNAKE_CASE     ,	np.ndarray	)

            # Test not batched input
            __snake_case            =	image_processing(image_inputs[0]     ,	return_tensors='''pt'''	).pixel_values
            self.assertEqual(
                encoded_images.shape     ,	(
                    1,
                    self.image_processor_tester.num_channels,
                    self.image_processor_tester.crop_size['''height'''],
                    self.image_processor_tester.crop_size['''width'''],
                )     ,	)

            # Test batched
            __snake_case            =	image_processing(__SCREAMING_SNAKE_CASE     ,	return_tensors='''pt'''	).pixel_values
            self.assertEqual(
                encoded_images.shape     ,	(
                    self.image_processor_tester.batch_size,
                    self.image_processor_tester.num_channels,
                    self.image_processor_tester.crop_size['''height'''],
                    self.image_processor_tester.crop_size['''width'''],
                )     ,	)




       def    lowerCAmelCase   ( self	)   ->	Tuple:



            '''simple docstring'''




            __snake_case            =	self.image_processing_class(**self.image_processor_dict	)
            # create random PyTorch tensors
            __snake_case            =	prepare_image_inputs(self.image_processor_tester     ,	equal_resolution=__SCREAMING_SNAKE_CASE     ,	torchify=__SCREAMING_SNAKE_CASE	)
            for image in image_inputs:
                 self.assertIsInstance(__SCREAMING_SNAKE_CASE     ,	torch.Tensor	)

            # Test not batched input
            __snake_case            =	image_processing(image_inputs[0]     ,	return_tensors='''pt'''	).pixel_values
            self.assertEqual(
                encoded_images.shape     ,	(
                    1,
                    self.image_processor_tester.num_channels,
                    self.image_processor_tester.crop_size['''height'''],
                    self.image_processor_tester.crop_size['''width'''],
                )     ,	)

            # Test batched
            __snake_case            =	image_processing(__SCREAMING_SNAKE_CASE     ,	return_tensors='''pt'''	).pixel_values
            self.assertEqual(
                encoded_images.shape     ,	(
                    self.image_processor_tester.batch_size,
                    self.image_processor_tester.num_channels,
                    self.image_processor_tester.crop_size['''height'''],
                    self.image_processor_tester.crop_size['''width'''],
                )     ,	)








# Imports
import numpy as np





class   UpperCamelCase_      :







						'''simple docstring'''



						def __init__(			self							:Optional[int]		,    lowerCAmelCase__							:int=None		,    lowerCAmelCase__							:List[str]=None		,    lowerCAmelCase__							:int=None		,    lowerCAmelCase__							:Optional[int]=None		,    lowerCAmelCase__							:List[str]=None     )  ->int:
										self.set_matricies(red=lowerCAmelCase__		,    green=lowerCAmelCase__		,    blue=lowerCAmelCase__		,    red_edge=lowerCAmelCase__		,    nir=lowerCAmelCase__     )





						def        SCREAMING_SNAKE_CASE(			self							:Optional[Any]		,    lowerCAmelCase__							:List[Any]=None		,    lowerCAmelCase__							:Any=None		,    lowerCAmelCase__							:Tuple=None		,    lowerCAmelCase__							:Optional[Any]=None		,    lowerCAmelCase__							:Optional[Any]=None     )  ->List[Any]:
										if red is not None:
														lowercase         =      red
										if green is not None:
														lowercase         =      green
										if blue is not None:
														lowercase         =      blue
										if red_edge is not None:
														lowercase         =      red_edge
										if nir is not None:
														lowercase         =      nir
										return True





						def        SCREAMING_SNAKE_CASE(			self							:Optional[Any]		,    lowerCAmelCase__							:Dict=""		,    lowerCAmelCase__							:Optional[Any]=None		,    lowerCAmelCase__							:Union[str, Any]=None		,    lowerCAmelCase__							:int=None		,    lowerCAmelCase__							:int=None		,    lowerCAmelCase__							:Union[str, Any]=None     )  ->Optional[Any]:
										self.set_matricies(red=lowerCAmelCase__		,    green=lowerCAmelCase__		,    blue=lowerCAmelCase__		,    red_edge=lowerCAmelCase__		,    nir=lowerCAmelCase__     )
										lowercase         =      {
										    "ARVI2": self.arvaa,
										    "CCCI": self.ccci,
										    "CVI": self.cvi,
										    "GLI": self.gli,
										    "NDVI": self.ndvi,
										    "BNDVI": self.bndvi,
										    "redEdgeNDVI": self.red_edge_ndvi,
										    "GNDVI": self.gndvi,
										    "GBNDVI": self.gbndvi,
										    "GRNDVI": self.grndvi,
										    "RBNDVI": self.rbndvi,
										    "PNDVI": self.pndvi,
										    "ATSAVI": self.atsavi,
										    "BWDRVI": self.bwdrvi,
										    "CIgreen": self.ci_green,
										    "CIrededge": self.ci_rededge,
										    "CI": self.ci,
										    "CTVI": self.ctvi,
										    "GDVI": self.gdvi,
										    "EVI": self.evi,
										    "GEMI": self.gemi,
										    "GOSAVI": self.gosavi,
										    "GSAVI": self.gsavi,
										    "Hue": self.hue,
										    "IVI": self.ivi,
										    "IPVI": self.ipvi,
										    "I": self.i,
										    "RVI": self.rvi,
										    "MRVI": self.mrvi,
										    "MSAVI": self.m_savi,
										    "NormG": self.norm_g,
										    "NormNIR": self.norm_nir,
										    "NormR": self.norm_r,
										    "NGRDI": self.ngrdi,
										    "RI": self.ri,
										    "S": self.s,
										    "IF": self._if,
										    "DVI": self.dvi,
										    "TVI": self.tvi,
										    "NDRE": self.ndre,
										}

										try:
														return funcs[index]()
										except KeyError:
														print("Index not in the list!"     )
														return False





						def        SCREAMING_SNAKE_CASE(			self							:Any     )  ->int:
										return -0.18 + (1.17 * ((self.nir - self.red) / (self.nir + self.red)))





						def        SCREAMING_SNAKE_CASE(			self							:List[str]     )  ->int:
										return ((self.nir - self.redEdge) / (self.nir + self.redEdge)) / (
										    (self.nir - self.red) / (self.nir + self.red)
										)





						def        SCREAMING_SNAKE_CASE(			self							:int     )  ->Tuple:
										return self.nir * (self.red / (self.green**2))





						def        SCREAMING_SNAKE_CASE(			self							:List[str]     )  ->Dict:
										return (2 * self.green - self.red - self.blue) / (
										    2 * self.green + self.red + self.blue
										)





						def        SCREAMING_SNAKE_CASE(			self							:str     )  ->Optional[int]:
										return (self.nir - self.red) / (self.nir + self.red)





						def        SCREAMING_SNAKE_CASE(			self							:str     )  ->int:
										return (self.nir - self.blue) / (self.nir + self.blue)





						def        SCREAMING_SNAKE_CASE(			self							:List[str]     )  ->List[str]:
										return (self.redEdge - self.red) / (self.redEdge + self.red)





						def        SCREAMING_SNAKE_CASE(			self							:Optional[int]     )  ->str:
										return (self.nir - self.green) / (self.nir + self.green)





						def        SCREAMING_SNAKE_CASE(			self							:int     )  ->Any:
										return (self.nir - (self.green + self.blue)) / (
										    self.nir + (self.green + self.blue)
										)





						def        SCREAMING_SNAKE_CASE(			self							:Union[str, Any]     )  ->List[Any]:
										return (self.nir - (self.green + self.red)) / (
										    self.nir + (self.green + self.red)
										)





						def        SCREAMING_SNAKE_CASE(			self							:Optional[Any]     )  ->Union[str, Any]:
										return (self.nir - (self.blue + self.red)) / (self.nir + (self.blue + self.red))





						def        SCREAMING_SNAKE_CASE(			self							:Any     )  ->Union[str, Any]:
										return (self.nir - (self.green + self.red + self.blue)) / (
										    self.nir + (self.green + self.red + self.blue)
										)





						def        SCREAMING_SNAKE_CASE(			self							:Tuple		,    lowerCAmelCase__							:Union[str, Any]=0.08		,    lowerCAmelCase__							:Dict=1.22		,    lowerCAmelCase__							:Tuple=0.03     )  ->Tuple:
										return a * (
										    (self.nir - a * self.red - b)
										    / (a * self.nir + self.red - a * b + x * (1 + a**2))
										)





						def        SCREAMING_SNAKE_CASE(			self							:Dict     )  ->Any:
										return (0.1 * self.nir - self.blue) / (0.1 * self.nir + self.blue)





						def        SCREAMING_SNAKE_CASE(			self							:Optional[Any]     )  ->int:
										return (self.nir / self.green) - 1





						def        SCREAMING_SNAKE_CASE(			self							:int     )  ->List[str]:
										return (self.nir / self.redEdge) - 1





						def        SCREAMING_SNAKE_CASE(			self							:Union[str, Any]     )  ->List[Any]:
										return (self.red - self.blue) / self.red





						def        SCREAMING_SNAKE_CASE(			self							:Any     )  ->int:
										lowercase         =      self.ndvi()
										return ((ndvi + 0.5) / (abs(ndvi + 0.5     ))) * (abs(ndvi + 0.5     ) ** (1 / 2))





						def        SCREAMING_SNAKE_CASE(			self							:List[str]     )  ->Optional[Any]:
										return self.nir - self.green





						def        SCREAMING_SNAKE_CASE(			self							:str     )  ->int:
										return 2.5 * (
										    (self.nir - self.red) / (self.nir + 6 * self.red - 7.5 * self.blue + 1)
										)





						def        SCREAMING_SNAKE_CASE(			self							:List[str]     )  ->Optional[Any]:
										lowercase         =      (2 * (self.nir**2 - self.red**2) + 1.5 * self.nir + 0.5 * self.red) / (
										    self.nir + self.red + 0.5
										)
										return n * (1 - 0.25 * n) - (self.red - 0.1_25) / (1 - self.red)





						def        SCREAMING_SNAKE_CASE(			self							:Union[str, Any]		,    lowerCAmelCase__							:Tuple=0.16     )  ->Any:
										return (self.nir - self.green) / (self.nir + self.green + y)





						def        SCREAMING_SNAKE_CASE(			self							:Dict		,    lowerCAmelCase__							:Any=0.5     )  ->str:
										return ((self.nir - self.green) / (self.nir + self.green + n)) * (1 + n)





						def        SCREAMING_SNAKE_CASE(			self							:int     )  ->List[str]:
										return np.arctan(
										    ((2 * self.red - self.green - self.blue) / 30.5) * (self.green - self.blue)     )





						def        SCREAMING_SNAKE_CASE(			self							:Any		,    lowerCAmelCase__							:str=None		,    lowerCAmelCase__							:Tuple=None     )  ->Dict:
										return (self.nir - b) / (a * self.red)





						def        SCREAMING_SNAKE_CASE(			self							:Optional[Any]     )  ->Dict:
										return (self.nir / ((self.nir + self.red) / 2)) * (self.ndvi() + 1)





						def        SCREAMING_SNAKE_CASE(			self							:str     )  ->List[Any]:
										return (self.red + self.green + self.blue) / 30.5





						def        SCREAMING_SNAKE_CASE(			self							:Tuple     )  ->Optional[Any]:
										return self.nir / self.red





						def        SCREAMING_SNAKE_CASE(			self							:Optional[int]     )  ->Dict:
										return (self.rvi() - 1) / (self.rvi() + 1)





						def        SCREAMING_SNAKE_CASE(			self							:Optional[Any]     )  ->Dict:
										return (
										    (2 * self.nir + 1)
										    - ((2 * self.nir + 1) ** 2 - 8 * (self.nir - self.red)) ** (1 / 2)
										) / 2





						def        SCREAMING_SNAKE_CASE(			self							:str     )  ->int:
										return self.green / (self.nir + self.red + self.green)





						def        SCREAMING_SNAKE_CASE(			self							:Any     )  ->Any:
										return self.nir / (self.nir + self.red + self.green)





						def        SCREAMING_SNAKE_CASE(			self							:int     )  ->Tuple:
										return self.red / (self.nir + self.red + self.green)





						def        SCREAMING_SNAKE_CASE(			self							:List[Any]     )  ->List[Any]:
										return (self.green - self.red) / (self.green + self.red)





						def        SCREAMING_SNAKE_CASE(			self							:List[str]     )  ->str:
										return (self.red - self.green) / (self.red + self.green)





						def        SCREAMING_SNAKE_CASE(			self							:Union[str, Any]     )  ->List[str]:
										lowercase         =      np.max([np.max(self.red     ), np.max(self.green     ), np.max(self.blue     )]     )
										lowercase         =      np.min([np.min(self.red     ), np.min(self.green     ), np.min(self.blue     )]     )
										return (max_value - min_value) / max_value





						def        SCREAMING_SNAKE_CASE(			self							:List[str]     )  ->Any:
										return (2 * self.red - self.green - self.blue) / (self.green - self.blue)





						def        SCREAMING_SNAKE_CASE(			self							:List[str]     )  ->List[Any]:
										return self.nir / self.red





						def        SCREAMING_SNAKE_CASE(			self							:Any     )  ->List[str]:
										return (self.ndvi() + 0.5) ** (1 / 2)





						def        SCREAMING_SNAKE_CASE(			self							:Optional[int]     )  ->Union[str, Any]:
										return (self.nir - self.redEdge) / (self.nir + self.redEdge)
