





"""simple docstring"""



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

import cva
import numpy as np

# Parrameters
a_					=     (720, 1280)  # Height, Width
a_					=     (0.4, 0.6)  # if height or width lower than this scale, drop it.
a_					=     1 / 100
a_					=     """"""
a_					=     """"""
a_					=     """"""
a_					=     250







def 						__lowercase	(  )  ->None:



    '''simple docstring'''







    __A					,			__A       :		Tuple							=	get_dataset(snake_case_							,snake_case_		)
    for index in range(snake_case_		):
        __A       :		List[Any]							=	random.sample(range(len(snake_case_		)		)							,4		)
        __A					,			__A					,			__A       :		Tuple							=	update_image_and_anno(
            snake_case_							,snake_case_							,snake_case_							,snake_case_							,snake_case_							,filter_scale=snake_case_							,)

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







def 						__lowercase	(  snake_case_    :    str							,snake_case_    :    str		)  ->tuple[list, list]:



    '''simple docstring'''







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

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

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







def 						__lowercase	(  snake_case_    :    list							,snake_case_    :    list							,snake_case_    :    list[int]							,snake_case_    :    tuple[int, int]							,snake_case_    :    tuple[float, float]							,snake_case_    :    float = 0.0							,)  ->tuple[list, list, str]:



    '''simple docstring'''







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

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



    '''simple docstring'''







    assert number_char > 1, "The number of character should greater than 1"
    __A       :		Optional[Any]							=	ascii_lowercase + digits
    return "".join(random.choice(snake_case_		) for _ in range(snake_case_		)		)


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











"""simple docstring"""



from collections import defaultdict
from math import gcd







def 						__lowercase	(  snake_case_    :    int = 1500000		)  ->int:



    '''simple docstring'''







    __A       :		defaultdict							=	defaultdict(snake_case_		)
    __A       :		Any							=	2
    while 2 * euclid_m * (euclid_m + 1) <= limit:
        for euclid_n in range((euclid_m % 2) + 1							,snake_case_							,2		):
            if gcd(snake_case_							,snake_case_		) > 1:
                continue
            __A       :		List[Any]							=	2 * euclid_m * (euclid_m + euclid_n)
            for perimeter in range(snake_case_							,limit + 1							,snake_case_		):
                frequencies[perimeter] += 1
        euclid_m += 1
    return sum(1 for frequency in frequencies.values() if frequency == 1		)


if __name__ == "__main__":
       print(f'''{solution() = }''')




