



'''simple docstring'''




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

import cva
import numpy as np

# Parrameters
UpperCamelCase__ :			Any												=				(7_20, 12_80)  # Height, Width
UpperCamelCase__ :			Optional[Any]												=				(0.4, 0.6)  # if height or width lower than this scale, drop it.
UpperCamelCase__ :			List[Any]												=				1 / 1_00
UpperCamelCase__ :			Optional[int]												=				''''''
UpperCamelCase__ :			str												=				''''''
UpperCamelCase__ :			str												=				''''''
UpperCamelCase__ :			List[Any]												=				2_50


def        lowerCAmelCase_     (			):
		__SCREAMING_SNAKE_CASE ,		__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	get_dataset(_lowerCamelCase ,   _lowerCamelCase      )
		for index in range(_lowerCamelCase      ):
				__SCREAMING_SNAKE_CASE :	Tuple					 =	random.sample(range(len(_lowerCamelCase      )      ) ,   4      )
				__SCREAMING_SNAKE_CASE ,		__SCREAMING_SNAKE_CASE ,		__SCREAMING_SNAKE_CASE :	str					 =	update_image_and_anno(
				    _lowerCamelCase ,   _lowerCamelCase ,   _lowerCamelCase ,   _lowerCamelCase ,   _lowerCamelCase ,   filter_scale=_lowerCamelCase ,   )

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


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

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

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


def        lowerCAmelCase_     (			_lowerCamelCase:     list ,   _lowerCamelCase:     list ,   _lowerCamelCase:     list[int] ,   _lowerCamelCase:     tuple[int, int] ,   _lowerCamelCase:     tuple[float, float] ,   _lowerCamelCase:     float = 0.0 ,   ):
		__SCREAMING_SNAKE_CASE :	int					 =	np.zeros([output_size[0], output_size[1], 3] ,   dtype=np.uinta      )
		__SCREAMING_SNAKE_CASE :	int					 =	scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
		__SCREAMING_SNAKE_CASE :	str					 =	scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
		__SCREAMING_SNAKE_CASE :	int					 =	int(scale_x * output_size[1]      )
		__SCREAMING_SNAKE_CASE :	List[Any]					 =	int(scale_y * output_size[0]      )

		__SCREAMING_SNAKE_CASE :	Optional[int]					 =	[]
		__SCREAMING_SNAKE_CASE :	Any					 =	[]
		for i, index in enumerate(_lowerCamelCase      ):
				__SCREAMING_SNAKE_CASE :	Union[str, Any]					 =	all_img_list[index]
				path_list.append(_lowerCamelCase      )
				__SCREAMING_SNAKE_CASE :	Any					 =	all_annos[index]
				__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	cva.imread(_lowerCamelCase      )
				if i == 0:  # top-left
						__SCREAMING_SNAKE_CASE :	List[str]					 =	cva.resize(_lowerCamelCase ,   (divid_point_x, divid_point_y)      )
						__SCREAMING_SNAKE_CASE :	Tuple					 =	img
						for bbox in img_annos:
								__SCREAMING_SNAKE_CASE :	List[str]					 =	bbox[1] * scale_x
								__SCREAMING_SNAKE_CASE :	int					 =	bbox[2] * scale_y
								__SCREAMING_SNAKE_CASE :	List[str]					 =	bbox[3] * scale_x
								__SCREAMING_SNAKE_CASE :	str					 =	bbox[4] * scale_y
								new_anno.append([bbox[0], xmin, ymin, xmax, ymax]      )
				elif i == 1:  # top-right
						__SCREAMING_SNAKE_CASE :	Dict					 =	cva.resize(_lowerCamelCase ,   (output_size[1] - divid_point_x, divid_point_y)      )
						__SCREAMING_SNAKE_CASE :	Tuple					 =	img
						for bbox in img_annos:
								__SCREAMING_SNAKE_CASE :	Tuple					 =	scale_x + bbox[1] * (1 - scale_x)
								__SCREAMING_SNAKE_CASE :	Dict					 =	bbox[2] * scale_y
								__SCREAMING_SNAKE_CASE :	int					 =	scale_x + bbox[3] * (1 - scale_x)
								__SCREAMING_SNAKE_CASE :	Optional[int]					 =	bbox[4] * scale_y
								new_anno.append([bbox[0], xmin, ymin, xmax, ymax]      )
				elif i == 2:  # bottom-left
						__SCREAMING_SNAKE_CASE :	Any					 =	cva.resize(_lowerCamelCase ,   (divid_point_x, output_size[0] - divid_point_y)      )
						__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	img
						for bbox in img_annos:
								__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	bbox[1] * scale_x
								__SCREAMING_SNAKE_CASE :	Any					 =	scale_y + bbox[2] * (1 - scale_y)
								__SCREAMING_SNAKE_CASE :	List[str]					 =	bbox[3] * scale_x
								__SCREAMING_SNAKE_CASE :	Dict					 =	scale_y + bbox[4] * (1 - scale_y)
								new_anno.append([bbox[0], xmin, ymin, xmax, ymax]      )
				else:  # bottom-right
						__SCREAMING_SNAKE_CASE :	Dict					 =	cva.resize(
						    _lowerCamelCase ,   (output_size[1] - divid_point_x, output_size[0] - divid_point_y)      )
						__SCREAMING_SNAKE_CASE :	List[str]					 =	img
						for bbox in img_annos:
								__SCREAMING_SNAKE_CASE :	List[Any]					 =	scale_x + bbox[1] * (1 - scale_x)
								__SCREAMING_SNAKE_CASE :	List[Any]					 =	scale_y + bbox[2] * (1 - scale_y)
								__SCREAMING_SNAKE_CASE :	List[Any]					 =	scale_x + bbox[3] * (1 - scale_x)
								__SCREAMING_SNAKE_CASE :	List[str]					 =	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[Any]					 =	[
				    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        lowerCAmelCase_     (			_lowerCamelCase:     int      ):
		assert number_char > 1, "The number of character should greater than 1"
		__SCREAMING_SNAKE_CASE :	Dict					 =	ascii_lowercase + digits
		return "".join(random.choice(_lowerCamelCase      ) for _ in range(_lowerCamelCase      )      )


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




'''simple docstring'''




import qiskit


def        lowerCAmelCase_     (			_lowerCamelCase:     int = 2      ):
		__SCREAMING_SNAKE_CASE :	Dict					 =	qubits

		# Using Aer's simulator
		__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	qiskit.Aer.get_backend("""aer_simulator"""      )

		# Creating a Quantum Circuit acting on the q register
		__SCREAMING_SNAKE_CASE :	str					 =	qiskit.QuantumCircuit(_lowerCamelCase ,   _lowerCamelCase      )

		# Adding a H gate on qubit 0 (now q0 in superposition)
		circuit.h(0      )

		for i in range(1 ,   _lowerCamelCase      ):
				# Adding CX (CNOT) gate
				circuit.cx(i - 1 ,   _lowerCamelCase      )

		# Mapping the quantum measurement to the classical bits
		circuit.measure(list(range(_lowerCamelCase      )      ) ,   list(range(_lowerCamelCase      )      )      )

		# Now measuring any one qubit would affect other qubits to collapse
		# their super position and have same state as the measured one.

		# Executing the circuit on the simulator
		__SCREAMING_SNAKE_CASE :	str					 =	qiskit.execute(_lowerCamelCase ,   _lowerCamelCase ,   shots=10_00      )

		return job.result().get_counts(_lowerCamelCase      )


if __name__ == "__main__":
						print(f"Total count for various states are: {quantum_entanglement(3)}")