
'''simple docstring'''







import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union

import numpy as np
def 					snake_case_		(				__SCREAMING_SNAKE_CASE					: bytes      ,      __SCREAMING_SNAKE_CASE					: int							):



						"""simple docstring"""





						lowercase_	:     Any													=       F'''{sampling_rate}'''
						lowercase_	:     Union[str, Any]													=       '''1'''
						lowercase_	:     Optional[Any]													=       '''f32le'''
						lowercase_	:     Optional[Any]													=       [
						    '''ffmpeg''',
						    '''-i''',
						    '''pipe:0''',
						    '''-ac''',
						    ac,
						    '''-ar''',
						    ar,
						    '''-f''',
						    format_for_conversion,
						    '''-hide_banner''',
						    '''-loglevel''',
						    '''quiet''',
						    '''pipe:1''',
						]

						try:
												with subprocess.Popen(__SCREAMING_SNAKE_CASE      ,      stdin=subprocess.PIPE      ,      stdout=subprocess.PIPE							) as ffmpeg_process:
																		lowercase_	:     List[str]													=       ffmpeg_process.communicate(__SCREAMING_SNAKE_CASE							)
						except FileNotFoundError as error:
												raise ValueError('''ffmpeg was not found but is required to load audio files from filename'''							) from error
						lowercase_	:     int													=       output_stream[0]
						lowercase_	:     Dict													=       np.frombuffer(__SCREAMING_SNAKE_CASE      ,      np.floataa							)
						if audio.shape[0] == 0:
												raise ValueError('''Malformed soundfile'''							)
						return audio
def 					snake_case_		(				__SCREAMING_SNAKE_CASE					: int      ,      __SCREAMING_SNAKE_CASE					: float      ,      __SCREAMING_SNAKE_CASE					: str = "f32le"      ,      ):



						"""simple docstring"""





						lowercase_	:     str													=       F'''{sampling_rate}'''
						lowercase_	:     Optional[Any]													=       '''1'''
						if format_for_conversion == "s16le":
												lowercase_	:     Any													=       2
						elif format_for_conversion == "f32le":
												lowercase_	:     Optional[int]													=       4
						else:
												raise ValueError(F'''Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'''							)

						lowercase_	:     List[Any]													=       platform.system()
						if system == "Linux":
												lowercase_	:     Optional[int]													=       '''alsa'''
												lowercase_	:     Dict													=       '''default'''
						elif system == "Darwin":
												lowercase_	:     int													=       '''avfoundation'''
												lowercase_	:     str													=       ''':0'''
						elif system == "Windows":
												lowercase_	:     int													=       '''dshow'''
												lowercase_	:     Optional[Any]													=       '''default'''

						lowercase_	:     Dict													=       [
						    '''ffmpeg''',
						    '''-f''',
						    format_,
						    '''-i''',
						    input_,
						    '''-ac''',
						    ac,
						    '''-ar''',
						    ar,
						    '''-f''',
						    format_for_conversion,
						    '''-fflags''',
						    '''nobuffer''',
						    '''-hide_banner''',
						    '''-loglevel''',
						    '''quiet''',
						    '''pipe:1''',
						]
						lowercase_	:     Any													=       int(round(sampling_rate * chunk_length_s							)							) * size_of_sample
						lowercase_	:     int													=       _ffmpeg_stream(__SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE							)
						for item in iterator:
												yield item
def 					snake_case_		(				__SCREAMING_SNAKE_CASE					: int      ,      __SCREAMING_SNAKE_CASE					: float      ,      __SCREAMING_SNAKE_CASE					: Optional[int] = None      ,      __SCREAMING_SNAKE_CASE					: Optional[Union[Tuple[float, float], float]] = None      ,      __SCREAMING_SNAKE_CASE					: str = "f32le"      ,      ):



						"""simple docstring"""





						if stream_chunk_s is not None:
												lowercase_	:     List[str]													=       stream_chunk_s
						else:
												lowercase_	:     Optional[int]													=       chunk_length_s

						lowercase_	:     List[Any]													=       ffmpeg_microphone(__SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE      ,      format_for_conversion=__SCREAMING_SNAKE_CASE							)
						if format_for_conversion == "s16le":
												lowercase_	:     Tuple													=       np.intaa
												lowercase_	:     Dict													=       2
						elif format_for_conversion == "f32le":
												lowercase_	:     List[Any]													=       np.floataa
												lowercase_	:     List[Any]													=       4
						else:
												raise ValueError(F'''Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'''							)

						if stride_length_s is None:
												lowercase_	:     List[str]													=       chunk_length_s / 6
						lowercase_	:     Any													=       int(round(sampling_rate * chunk_length_s							)							) * size_of_sample
						if isinstance(__SCREAMING_SNAKE_CASE      ,      (int, float)							):
												lowercase_	:     Tuple													=       [stride_length_s, stride_length_s]

						lowercase_	:     str													=       int(round(sampling_rate * stride_length_s[0]							)							) * size_of_sample
						lowercase_	:     int													=       int(round(sampling_rate * stride_length_s[1]							)							) * size_of_sample
						lowercase_	:     Tuple													=       datetime.datetime.now()
						lowercase_	:     Dict													=       datetime.timedelta(seconds=__SCREAMING_SNAKE_CASE							)
						for item in chunk_bytes_iter(__SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE      ,      stride=(stride_left, stride_right)      ,      stream=__SCREAMING_SNAKE_CASE							):
												# Put everything back in numpy scale
												lowercase_	:     int													=       np.frombuffer(item['''raw''']      ,      dtype=__SCREAMING_SNAKE_CASE							)
												lowercase_	:     Union[str, Any]													=       (
												    item['''stride'''][0] // size_of_sample,
												    item['''stride'''][1] // size_of_sample,
												)
												lowercase_	:     Optional[Any]													=       sampling_rate
												audio_time += delta
												if datetime.datetime.now() > audio_time + 10 * delta:
																		# We're late !! SKIP
																		continue
												yield item
def 					snake_case_		(				__SCREAMING_SNAKE_CASE					: List[Any]      ,      __SCREAMING_SNAKE_CASE					: int      ,      __SCREAMING_SNAKE_CASE					: Tuple[int, int]      ,      __SCREAMING_SNAKE_CASE					: bool = False							):



						"""simple docstring"""





						lowercase_	:     Optional[int]													=       B''''''
						lowercase_						, lowercase_	:     Dict													=       stride
						if stride_left + stride_right >= chunk_len:
												raise ValueError(
												    F'''Stride needs to be strictly smaller than chunk_len: ({stride_left}, {stride_right}) vs {chunk_len}'''							)
						lowercase_	:     Any													=       0
						for raw in iterator:
												acc += raw
												if stream and len(__SCREAMING_SNAKE_CASE							) < chunk_len:
																		lowercase_	:     List[str]													=       (_stride_left, 0)
																		yield {"raw": acc[:chunk_len], "stride": stride, "partial": True}
												else:
																		while len(__SCREAMING_SNAKE_CASE							) >= chunk_len:
																								# We are flushing the accumulator
																								lowercase_	:     Tuple													=       (_stride_left, stride_right)
																								lowercase_	:     List[str]													=       {'''raw''': acc[:chunk_len], '''stride''': stride}
																								if stream:
																														lowercase_	:     int													=       False
																								yield item
																								lowercase_	:     Optional[Any]													=       stride_left
																								lowercase_	:     Union[str, Any]													=       acc[chunk_len - stride_left - stride_right :]
    # Last chunk
						if len(__SCREAMING_SNAKE_CASE							) > stride_left:
												lowercase_	:     Union[str, Any]													=       {'''raw''': acc, '''stride''': (_stride_left, 0)}
												if stream:
																		lowercase_	:     Union[str, Any]													=       False
												yield item




def 					snake_case_		(				__SCREAMING_SNAKE_CASE					: int      ,      __SCREAMING_SNAKE_CASE					: int							):



						"""simple docstring"""





						lowercase_	:     str													=       2**24  # 16Mo
						try:
												with subprocess.Popen(__SCREAMING_SNAKE_CASE      ,      stdout=subprocess.PIPE      ,      bufsize=__SCREAMING_SNAKE_CASE							) as ffmpeg_process:
																		while True:
																								lowercase_	:     Any													=       ffmpeg_process.stdout.read(__SCREAMING_SNAKE_CASE							)
																								if raw == b"":
																														break
																								yield raw
						except FileNotFoundError as error:
												raise ValueError('''ffmpeg was not found but is required to stream audio files from filename'''							) from error





'''simple docstring'''







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

import cva
import numpy as np

# Parrameters
_lowercase :  Any    							=       (7_2_0, 1_2_8_0)  # Height, Width
_lowercase :  List[Any]    							=       (0.4, 0.6)  # if height or width lower than this scale, drop it.
_lowercase :  str    							=       1 / 1_0_0
_lowercase :  Any    							=       ""
_lowercase :  Union[str, Any]    							=       ""
_lowercase :  Optional[int]    							=       ""
_lowercase :  List[Any]    							=       2_5_0
def 					snake_case_		(				):



						"""simple docstring"""





						lowercase_						, lowercase_	:     Any													=       get_dataset(__SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE							)
						for index in range(__SCREAMING_SNAKE_CASE							):
												lowercase_	:     str													=       random.sample(range(len(__SCREAMING_SNAKE_CASE							)							)      ,      4							)
												lowercase_						, lowercase_						, lowercase_	:     Any													=       update_image_and_anno(
												    __SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE      ,      filter_scale=__SCREAMING_SNAKE_CASE      ,      )

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



						"""simple docstring"""





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

												lowercase_	:     Optional[int]													=       []
												for obj_list in obj_lists:
																		lowercase_	:     List[str]													=       obj_list.rstrip('''\n'''							).split(''' '''							)
																		lowercase_	:     Optional[int]													=       float(obj[1]							) - float(obj[3]							) / 2
																		lowercase_	:     Any													=       float(obj[2]							) - float(obj[4]							) / 2
																		lowercase_	:     str													=       float(obj[1]							) + float(obj[3]							) / 2
																		lowercase_	:     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(__SCREAMING_SNAKE_CASE							)
												labels.append(__SCREAMING_SNAKE_CASE							)
						return img_paths, labels
def 					snake_case_		(				__SCREAMING_SNAKE_CASE					: list      ,      __SCREAMING_SNAKE_CASE					: list      ,      __SCREAMING_SNAKE_CASE					: list[int]      ,      __SCREAMING_SNAKE_CASE					: tuple[int, int]      ,      __SCREAMING_SNAKE_CASE					: tuple[float, float]      ,      __SCREAMING_SNAKE_CASE					: float = 0.0      ,      ):



						"""simple docstring"""





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

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



						"""simple docstring"""





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


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



