

"""simple docstring"""




import unittest

from transformers import load_tool
from transformers.tools.agent_types import AGENT_TYPE_MAPPING

from .test_tools_common import ToolTesterMixin, output_types

class   __UpperCamelCase      (   unittest.TestCase       ,       lowercase  ):




	def  __A   (						self		:  List[Any]							):


		'''simple docstring'''







		UpperCAmelCase_    			=     load_tool("translation"							)
		self.tool.setup()
		UpperCAmelCase_    			=     load_tool("translation"						,		remote=lowerCAmelCase							)




	def  __A   (						self		:  Any							):


		'''simple docstring'''







		UpperCAmelCase_    			=     self.tool("Hey, what's up?"						,		src_lang="English"						,		tgt_lang="French"							)
		self.assertEqual(lowerCAmelCase						,		"- Hé, comment ça va?"							)




	def  __A   (						self		:  List[str]							):


		'''simple docstring'''







		UpperCAmelCase_    			=     self.remote_tool("Hey, what's up?"						,		src_lang="English"						,		tgt_lang="French"							)
		self.assertEqual(lowerCAmelCase						,		"- Hé, comment ça va?"							)




	def  __A   (						self		:  Tuple							):


		'''simple docstring'''







		UpperCAmelCase_    			=     self.tool(text="Hey, what's up?"						,		src_lang="English"						,		tgt_lang="French"							)
		self.assertEqual(lowerCAmelCase						,		"- Hé, comment ça va?"							)




	def  __A   (						self		:  Tuple							):


		'''simple docstring'''







		UpperCAmelCase_    			=     self.remote_tool(text="Hey, what's up?"						,		src_lang="English"						,		tgt_lang="French"							)
		self.assertEqual(lowerCAmelCase						,		"- Hé, comment ça va?"							)




	def  __A   (						self		:  Optional[int]							):


		'''simple docstring'''







		UpperCAmelCase_    			=     ["Hey, what's up?", "English", "Spanish"]
		UpperCAmelCase_    			=     self.tool(*lowerCAmelCase							)

		# There is a single output
		if len(self.tool.outputs							) == 1:
			UpperCAmelCase_    			=     [outputs]

		self.assertListEqual(output_types(lowerCAmelCase							)						,		self.tool.outputs							)




	def  __A   (						self		:  str							):


		'''simple docstring'''







		UpperCAmelCase_    			=     ["Hey, what's up?", "English", "Spanish"]
		UpperCAmelCase_    			=     self.tool(*lowerCAmelCase							)

		if not isinstance(lowerCAmelCase						,		lowerCAmelCase							):
			UpperCAmelCase_    			=     [outputs]

		self.assertEqual(len(lowerCAmelCase							)						,		len(self.tool.outputs							)							)

		for output, output_type in zip(lowerCAmelCase						,		self.tool.outputs							):
			UpperCAmelCase_    			=     AGENT_TYPE_MAPPING[output_type]
			self.assertTrue(isinstance(lowerCAmelCase						,		lowerCAmelCase							)							)




	def  __A   (						self		:  Optional[int]							):


		'''simple docstring'''







		UpperCAmelCase_    			=     ["Hey, what's up?", "English", "Spanish"]

		UpperCAmelCase_    			=     []

		for _input, input_type in zip(lowerCAmelCase						,		self.tool.inputs							):
			if isinstance(lowerCAmelCase						,		lowerCAmelCase							):
				_inputs.append([AGENT_TYPE_MAPPING[_input_type](_input							) for _input_type in input_type]							)
			else:
				_inputs.append(AGENT_TYPE_MAPPING[input_type](_input							)							)

        # Should not raise an error
		UpperCAmelCase_    			=     self.tool(*lowerCAmelCase							)

		if not isinstance(lowerCAmelCase						,		lowerCAmelCase							):
			UpperCAmelCase_    			=     [outputs]

		self.assertEqual(len(lowerCAmelCase							)						,		len(self.tool.outputs							)							)


from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import divide, inta, multiply, ravel, sort, zeros_like



def  __lowerCAmelCase (  A    ,       A=3      ):
	UpperCAmelCase_    			=     int(mask / 2      )
	# copy image size
	UpperCAmelCase_    			=     zeros_like(A      )
	for i in range(A    ,       gray_img.shape[0] - bd      ):
		for j in range(A    ,       gray_img.shape[1] - bd      ):
			# get mask according with mask
			UpperCAmelCase_    			=     ravel(gray_img[i - bd : i + bd + 1, j - bd : j + bd + 1]      )
			# calculate mask median
			UpperCAmelCase_    			=     sort(A      )[inta(divide((multiply(A    ,       A      ))    ,       2      ) + 1      )]
			UpperCAmelCase_    			=     median
	return median_img


if __name__ == "__main__":
				# read original image
				_a:      Optional[int]								=     imread("""../image_data/lena.jpg""")
				# turn image in gray scale value
				_a:      Dict								=     cvtColor(img, COLOR_BGR2GRAY)

				# get values with two different mask size
				_a:      Tuple								=     median_filter(gray, 3)
				_a:      Dict								=     median_filter(gray, 5)

				# show result images
				imshow("""median filter with 3x3 mask""", medianaxa)
				imshow("""median filter with 5x5 mask""", medianaxa)
				waitKey(0)