


"""simple docstring"""






import os
import sys
import unittest


_lowerCAmelCase							:    Dict					   =	os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
_lowerCAmelCase							:    Union[str, Any]					   =	os.path.join(git_repo_path, '''src''', '''diffusers''')




class 							A_      (       unittest.TestCase ):


  def 							_lowercase					(			self:						List[Any]    ):







     '''simple docstring'''







     _lowerCamelCase   :				Optional[Any]							=     find_backend("    if not is_torch_available():"    )
     self.assertEqual(__lowerCAmelCase							,"torch"    )

     # backend_with_underscore = find_backend("    if not is_tensorflow_text_available():")
     # self.assertEqual(backend_with_underscore, "tensorflow_text")

     _lowerCamelCase   :				Union[str, Any]							=     find_backend("    if not (is_torch_available() and is_transformers_available()):"    )
     self.assertEqual(__lowerCAmelCase							,"torch_and_transformers"    )

     # double_backend_with_underscore = find_backend(
     #    "    if not (is_sentencepiece_available() and is_tensorflow_text_available()):"
     # )
     # self.assertEqual(double_backend_with_underscore, "sentencepiece_and_tensorflow_text")

     _lowerCamelCase   :				List[str]							=     find_backend(
         "    if not (is_torch_available() and is_transformers_available() and is_onnx_available()):"    )
     self.assertEqual(__lowerCAmelCase							,"torch_and_transformers_and_onnx"    )


  def 							_lowercase					(			self:						Optional[Any]    ):







     '''simple docstring'''







     _lowerCamelCase   :				List[Any]							=     read_init()
     # We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
     self.assertIn("torch"							,__lowerCAmelCase    )
     self.assertIn("torch_and_transformers"							,__lowerCAmelCase    )
     self.assertIn("flax_and_transformers"							,__lowerCAmelCase    )
     self.assertIn("torch_and_transformers_and_onnx"							,__lowerCAmelCase    )

     # Likewise, we can't assert on the exact content of a key
     self.assertIn("UNet2DModel"							,objects["torch"]    )
     self.assertIn("FlaxUNet2DConditionModel"							,objects["flax"]    )
     self.assertIn("StableDiffusionPipeline"							,objects["torch_and_transformers"]    )
     self.assertIn("FlaxStableDiffusionPipeline"							,objects["flax_and_transformers"]    )
     self.assertIn("LMSDiscreteScheduler"							,objects["torch_and_scipy"]    )
     self.assertIn("OnnxStableDiffusionPipeline"							,objects["torch_and_transformers_and_onnx"]    )


  def 							_lowercase					(			self:						List[str]    ):







     '''simple docstring'''







     _lowerCamelCase   :				Optional[int]							=     create_dummy_object("CONSTANT"							,"'torch'"    )
     self.assertEqual(__lowerCAmelCase							,"\nCONSTANT = None\n"    )

     _lowerCamelCase   :				List[str]							=     create_dummy_object("function"							,"'torch'"    )
     self.assertEqual(
         __lowerCAmelCase							,"\ndef function(*args, **kwargs):\n    requires_backends(function, 'torch')\n"    )

     _lowerCamelCase   :				Optional[int]							=     "\nclass FakeClass(metaclass=DummyObject):\n    _backends = 'torch'\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, 'torch')\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, 'torch')\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, 'torch')\n"
     _lowerCamelCase   :				Optional[int]							=     create_dummy_object("FakeClass"							,"'torch'"    )
     self.assertEqual(__lowerCAmelCase							,__lowerCAmelCase    )






  def 							_lowercase					(			self:						Dict    ):







     '''simple docstring'''







     _lowerCamelCase   :				Optional[int]							=     "# This file is autogenerated by the command `make fix-copies`, do not edit.\nfrom ..utils import DummyObject, requires_backends\n\n\nCONSTANT = None\n\n\ndef function(*args, **kwargs):\n    requires_backends(function, [\"torch\"])\n\n\nclass FakeClass(metaclass=DummyObject):\n    _backends = [\"torch\"]\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, [\"torch\"])\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, [\"torch\"])\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, [\"torch\"])\n"
     _lowerCamelCase   :				Union[str, Any]							=     create_dummy_files({"torch": ["CONSTANT", "function", "FakeClass"]}    )
     self.assertEqual(dummy_files["torch"]							,__lowerCAmelCase    )



import glob
import os
import random
from string import ascii_lowercase, digits

import cva
import numpy as np

# Parrameters
SCREAMING_SNAKE_CASE__     					=			(720, 1_280)  # Height, Width
SCREAMING_SNAKE_CASE__     					=			(0.4, 0.6)  # if height or width lower than this scale, drop it.
SCREAMING_SNAKE_CASE__     					=			1 / 100
SCREAMING_SNAKE_CASE__     					=			""
SCREAMING_SNAKE_CASE__     					=			""
SCREAMING_SNAKE_CASE__     					=			""
SCREAMING_SNAKE_CASE__     					=			250


def     lowercase	(    ):



		'''simple docstring'''




		SCREAMING_SNAKE_CASE_     ,				SCREAMING_SNAKE_CASE_				:str				     =						get_dataset(a     , a )
		for index in range(a ):
				SCREAMING_SNAKE_CASE_				:Any				     =						random.sample(range(len(a ) )     , 4 )
				SCREAMING_SNAKE_CASE_     ,				SCREAMING_SNAKE_CASE_     ,				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						update_image_and_anno(
				    a     , a     , a     , a     , a     , filter_scale=a     , )

				# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
				SCREAMING_SNAKE_CASE_				:int				     =						random_chars(32 )
				SCREAMING_SNAKE_CASE_				:Dict				     =						path.split(os.sep )[-1].rsplit("."     , 1 )[0]
				SCREAMING_SNAKE_CASE_				:Dict				     =						F"{OUTPUT_DIR}/{file_name}_MOSAIC_{letter_code}"
				cva.imwrite(F"{file_root}.jpg"     , a     , [cva.IMWRITE_JPEG_QUALITY, 85] )
				print(F"Succeeded {index+1}/{NUMBER_IMAGES} with {file_name}" )
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						[]
				for anno in new_annos:
						SCREAMING_SNAKE_CASE_				:Any				     =						anno[3] - anno[1]
						SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						anno[4] - anno[2]
						SCREAMING_SNAKE_CASE_				:Any				     =						anno[1] + width / 2
						SCREAMING_SNAKE_CASE_				:Optional[int]				     =						anno[2] + height / 2
						SCREAMING_SNAKE_CASE_				:Optional[int]				     =						F"{anno[0]} {x_center} {y_center} {width} {height}"
						annos_list.append(a )
				with open(F"{file_root}.txt"     , "w" ) as outfile:
						outfile.write("\n".join(line for line in annos_list ) )


def     lowercase	(    a     , a ):



		'''simple docstring'''




		SCREAMING_SNAKE_CASE_				:int				     =						[]
		SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						[]
		for label_file in glob.glob(os.path.join(a     , "*.txt" ) ):
				SCREAMING_SNAKE_CASE_				:List[str]				     =						label_file.split(os.sep )[-1].rsplit("."     , 1 )[0]
				with open(a ) as in_file:
						SCREAMING_SNAKE_CASE_				:List[Any]				     =						in_file.readlines()
				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						os.path.join(a     , F"{label_name}.jpg" )

				SCREAMING_SNAKE_CASE_				:Dict				     =						[]
				for obj_list in obj_lists:
						SCREAMING_SNAKE_CASE_				:Dict				     =						obj_list.rstrip("\n" ).split(" " )
						SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						float(obj[1] ) - float(obj[3] ) / 2
						SCREAMING_SNAKE_CASE_				:Dict				     =						float(obj[2] ) - float(obj[4] ) / 2
						SCREAMING_SNAKE_CASE_				:List[Any]				     =						float(obj[1] ) + float(obj[3] ) / 2
						SCREAMING_SNAKE_CASE_				:List[str]				     =						float(obj[2] ) + float(obj[4] ) / 2

						boxes.append([int(obj[0] ), xmin, ymin, xmax, ymax] )
				if not boxes:
						continue
				img_paths.append(a )
				labels.append(a )
		return img_paths, labels


def     lowercase	(    a     , a     , a     , a     , a     , a = 0.0     , ):



		'''simple docstring'''




		SCREAMING_SNAKE_CASE_				:int				     =						np.zeros([output_size[0], output_size[1], 3]     , dtype=np.uinta )
		SCREAMING_SNAKE_CASE_				:Tuple				     =						scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
		SCREAMING_SNAKE_CASE_				:List[str]				     =						scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
		SCREAMING_SNAKE_CASE_				:Any				     =						int(scale_x * output_size[1] )
		SCREAMING_SNAKE_CASE_				:List[Any]				     =						int(scale_y * output_size[0] )

		SCREAMING_SNAKE_CASE_				:Any				     =						[]
		SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						[]
		for i, index in enumerate(a ):
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						all_img_list[index]
				path_list.append(a )
				SCREAMING_SNAKE_CASE_				:Tuple				     =						all_annos[index]
				SCREAMING_SNAKE_CASE_				:Any				     =						cva.imread(a )
				if i == 0:  # top-left
						SCREAMING_SNAKE_CASE_				:int				     =						cva.resize(a     , (divid_point_x, divid_point_y) )
						SCREAMING_SNAKE_CASE_				:Any				     =						img
						for bbox in img_annos:
								SCREAMING_SNAKE_CASE_				:Tuple				     =						bbox[1] * scale_x
								SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						bbox[2] * scale_y
								SCREAMING_SNAKE_CASE_				:List[Any]				     =						bbox[3] * scale_x
								SCREAMING_SNAKE_CASE_				:Tuple				     =						bbox[4] * scale_y
								new_anno.append([bbox[0], xmin, ymin, xmax, ymax] )
				elif i == 1:  # top-right
						SCREAMING_SNAKE_CASE_				:Dict				     =						cva.resize(a     , (output_size[1] - divid_point_x, divid_point_y) )
						SCREAMING_SNAKE_CASE_				:Optional[int]				     =						img
						for bbox in img_annos:
								SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						scale_x + bbox[1] * (1 - scale_x)
								SCREAMING_SNAKE_CASE_				:Dict				     =						bbox[2] * scale_y
								SCREAMING_SNAKE_CASE_				:Optional[int]				     =						scale_x + bbox[3] * (1 - scale_x)
								SCREAMING_SNAKE_CASE_				:Tuple				     =						bbox[4] * scale_y
								new_anno.append([bbox[0], xmin, ymin, xmax, ymax] )
				elif i == 2:  # bottom-left
						SCREAMING_SNAKE_CASE_				:List[str]				     =						cva.resize(a     , (divid_point_x, output_size[0] - divid_point_y) )
						SCREAMING_SNAKE_CASE_				:int				     =						img
						for bbox in img_annos:
								SCREAMING_SNAKE_CASE_				:Tuple				     =						bbox[1] * scale_x
								SCREAMING_SNAKE_CASE_				:Dict				     =						scale_y + bbox[2] * (1 - scale_y)
								SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						bbox[3] * scale_x
								SCREAMING_SNAKE_CASE_				:List[str]				     =						scale_y + bbox[4] * (1 - scale_y)
								new_anno.append([bbox[0], xmin, ymin, xmax, ymax] )
				else:  # bottom-right
						SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						cva.resize(
						    a     , (output_size[1] - divid_point_x, output_size[0] - divid_point_y) )
						SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						img
						for bbox in img_annos:
								SCREAMING_SNAKE_CASE_				:Optional[int]				     =						scale_x + bbox[1] * (1 - scale_x)
								SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						scale_y + bbox[2] * (1 - scale_y)
								SCREAMING_SNAKE_CASE_				:Dict				     =						scale_x + bbox[3] * (1 - scale_x)
								SCREAMING_SNAKE_CASE_				:List[Any]				     =						scale_y + bbox[4] * (1 - scale_y)
								new_anno.append([bbox[0], xmin, ymin, xmax, ymax] )

    # Remove bounding box small than scale of filter
		if filter_scale > 0:
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						[
				    anno
				    for anno in new_anno
				    if filter_scale < (anno[3] - anno[1]) and filter_scale < (anno[4] - anno[2])
				]

		return output_img, new_anno, path_list[0]


def     lowercase	(    a ):



		'''simple docstring'''




		assert number_char > 1, "The number of character should greater than 1"
		SCREAMING_SNAKE_CASE_				:Dict				     =						ascii_lowercase + digits
		return "".join(random.choice(a ) for _ in range(a ) )


if __name__ == "__main__":
		main()
		print("DONE ✅")






