


import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest

from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import ArrayaD, ClassLabel, Features, Image, Value
from datasets.features.features import ArrayaDExtensionType, cast_to_python_objects
from datasets.keyhash import DuplicatedKeysError, InvalidKeyError

from .utils import require_pil
class 	UpperCAmelCase_					(					_lowerCamelCase    ):

   '''simple docstring'''




   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					Tuple    =				pa.array(TypedSequence([1, 2, 3] ) )
     self.assertEqual(arr.type						,				pa.intaa() )






   def _snake_case    (		self ):






     """simple docstring"""





     with self.assertRaises(lowercase_ ):
       lowerCamelCase :					List[str]    =				pa.array(TypedSequence([1, 2, 3] )						,				type=pa.intaa() )






   def _snake_case    (		self ):






     """simple docstring"""





     with self.assertRaises(lowercase_ ):
       lowerCamelCase :					List[Any]    =				pa.array(TypedSequence([1, 2, 3]						,				try_type=Value("bool" )						,				type=Value("int64" ) ) )






   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					Dict    =				pa.array(TypedSequence([1, 2, 3]						,				type=Value("int32" ) ) )
     self.assertEqual(arr.type						,				pa.intaa() )






   def _snake_case    (		self ):






     """simple docstring"""





     with self.assertRaises((TypeError, pa.lib.ArrowInvalid) ):
       lowerCamelCase :					List[Any]    =				pa.array(TypedSequence(["foo", "bar"]						,				type=Value("int64" ) ) )






   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					str    =				pa.array(TypedSequence([1, 2, 3]						,				try_type=Value("int32" ) ) )
     self.assertEqual(arr.type						,				pa.intaa() )






   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					Optional[int]    =				pa.array(TypedSequence(["foo", "bar"]						,				try_type=Value("int64" ) ) )
     self.assertEqual(arr.type						,				pa.string() )






   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					Optional[int]    =				pa.array(TypedSequence([[[1, 2, 3]]]						,				type=ArrayaD((1, 3)						,				"int64" ) ) )
     self.assertEqual(arr.type						,				ArrayaDExtensionType((1, 3)						,				"int64" ) )






   def _snake_case    (		self ):






     """simple docstring"""





     with self.assertRaises((TypeError, pa.lib.ArrowInvalid) ):
       lowerCamelCase :					Optional[int]    =				pa.array(TypedSequence(["foo", "bar"]						,				type=ArrayaD((1, 3)						,				"int64" ) ) )






   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					int    =				pa.array(TypedSequence([[[1, 2, 3]]]						,				try_type=ArrayaD((1, 3)						,				"int64" ) ) )
     self.assertEqual(arr.type						,				ArrayaDExtensionType((1, 3)						,				"int64" ) )






   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					Optional[int]    =				pa.array(TypedSequence(["foo", "bar"]						,				try_type=ArrayaD((1, 3)						,				"int64" ) ) )
     self.assertEqual(arr.type						,				pa.string() )






   @require_pil
   def _snake_case    (		self ):






     """simple docstring"""





     import PIL.Image

     lowerCamelCase :					Any    =				PIL.Image.fromarray(np.arange(10						,				dtype=np.uinta ).reshape(2						,				5 ) )
     with patch(
         "datasets.arrow_writer.cast_to_python_objects"						,				side_effect=lowercase_ ) as mock_cast_to_python_objects:
       lowerCamelCase :					str    =				pa.array(TypedSequence([{"path": None, "bytes": B"image_bytes"}, pil_image]						,				type=Image() ) )
       lowerCamelCase    ,	lowerCamelCase :					Tuple    =				mock_cast_to_python_objects.call_args_list[-1]
       self.assertIn("optimize_list_casting"						,				lowercase_ )
       self.assertFalse(kwargs["optimize_list_casting"] )






def 		lowercase_(  SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					Union[str, Any]    =				pa.BufferReader(__UpperCAmelCase	) if isinstance(__UpperCAmelCase      ,						pa.Buffer	) else pa.memory_map(__UpperCAmelCase	)
  lowerCamelCase :					Optional[int]    =				pa.ipc.open_stream(__UpperCAmelCase	)
  lowerCamelCase :					Tuple    =				f.read_all()
  assert len(pa_table.to_batches()	) == expected_num_chunks
  assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}
  del pa_table






@pytest.mark.parametrize("writer_batch_size"      ,						[None, 1, 10]	)
@pytest.mark.parametrize(
    "fields"      ,						[None, {"col_1": pa.string(), "col_2": pa.intaa()}, {"col_1": pa.string(), "col_2": pa.intaa()}]	)
def 		lowercase_(  SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					Union[str, Any]    =				pa.BufferOutputStream()
  lowerCamelCase :					int    =				pa.schema(__UpperCAmelCase	) if fields else None
  with ArrowWriter(stream=__UpperCAmelCase      ,						schema=__UpperCAmelCase      ,						writer_batch_size=__UpperCAmelCase	) as writer:
    writer.write({"col_1": "foo", "col_2": 1}	)
    writer.write({"col_1": "bar", "col_2": 2}	)
    lowerCamelCase    ,	lowerCamelCase :					Optional[int]    =				writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  if not fields:
    lowerCamelCase :					Tuple    =				{"col_1": pa.string(), "col_2": pa.intaa()}
  assert writer._schema == pa.schema(__UpperCAmelCase      ,						metadata=writer._schema.metadata	)
  _check_output(output.getvalue()      ,						expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)






def 		lowercase_(  ):


  '''simple docstring'''

  lowerCamelCase :					Tuple    =				pa.BufferOutputStream()
  lowerCamelCase :					Optional[Any]    =				Features({"labels": ClassLabel(names=["neg", "pos"]	)}	)
  with ArrowWriter(stream=__UpperCAmelCase      ,						features=__UpperCAmelCase	) as writer:
    writer.write({"labels": 0}	)
    writer.write({"labels": 1}	)
    lowerCamelCase    ,	lowerCamelCase :					Optional[int]    =				writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  assert writer._schema == features.arrow_schema
  assert writer._schema.metadata == features.arrow_schema.metadata
  lowerCamelCase :					Optional[Any]    =				pa.BufferReader(output.getvalue()	)
  lowerCamelCase :					int    =				pa.ipc.open_stream(__UpperCAmelCase	)
  lowerCamelCase :					Optional[Any]    =				f.read_all()
  lowerCamelCase :					Optional[Any]    =				pa_table.schema
  assert pa_table.num_rows == 2
  assert schema == features.arrow_schema
  assert schema.metadata == features.arrow_schema.metadata
  assert features == Features.from_arrow_schema(__UpperCAmelCase	)






@pytest.mark.parametrize("writer_batch_size"      ,						[None, 1, 10]	)
def 		lowercase_(  SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					List[Any]    =				pa.BufferOutputStream()
  with ArrowWriter(
      stream=__UpperCAmelCase      ,						writer_batch_size=__UpperCAmelCase      ,						hash_salt="split_name"      ,						check_duplicates=__UpperCAmelCase      ,						) as writer:
    with pytest.raises(__UpperCAmelCase	):
      writer.write({"col_1": "foo", "col_2": 1}      ,						key=[1, 2]	)
      lowerCamelCase    ,	lowerCamelCase :					Dict    =				writer.finalize()






@pytest.mark.parametrize("writer_batch_size"      ,						[None, 2, 10]	)
def 		lowercase_(  SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					Any    =				pa.BufferOutputStream()
  with ArrowWriter(
      stream=__UpperCAmelCase      ,						writer_batch_size=__UpperCAmelCase      ,						hash_salt="split_name"      ,						check_duplicates=__UpperCAmelCase      ,						) as writer:
    with pytest.raises(__UpperCAmelCase	):
      writer.write({"col_1": "foo", "col_2": 1}      ,						key=10	)
      writer.write({"col_1": "bar", "col_2": 2}      ,						key=10	)
      lowerCamelCase    ,	lowerCamelCase :					List[Any]    =				writer.finalize()






@pytest.mark.parametrize("writer_batch_size"      ,						[None, 2, 10]	)
def 		lowercase_(  SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					Any    =				pa.BufferOutputStream()
  with ArrowWriter(
      stream=__UpperCAmelCase      ,						writer_batch_size=__UpperCAmelCase      ,						hash_salt="split_name"      ,						check_duplicates=__UpperCAmelCase      ,						) as writer:
    writer.write({"col_1": "foo", "col_2": 1}      ,						key=1	)
    writer.write({"col_1": "bar", "col_2": 2}      ,						key=2	)
    lowerCamelCase    ,	lowerCamelCase :					int    =				writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  _check_output(output.getvalue()      ,						expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)






@pytest.mark.parametrize("writer_batch_size"      ,						[None, 1, 10]	)
@pytest.mark.parametrize(
    "fields"      ,						[None, {"col_1": pa.string(), "col_2": pa.intaa()}, {"col_1": pa.string(), "col_2": pa.intaa()}]	)
def 		lowercase_(  SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					Tuple    =				pa.BufferOutputStream()
  lowerCamelCase :					str    =				pa.schema(__UpperCAmelCase	) if fields else None
  with ArrowWriter(stream=__UpperCAmelCase      ,						schema=__UpperCAmelCase      ,						writer_batch_size=__UpperCAmelCase	) as writer:
    writer.write_batch({"col_1": ["foo", "bar"], "col_2": [1, 2]}	)
    writer.write_batch({"col_1": [], "col_2": []}	)
    lowerCamelCase    ,	lowerCamelCase :					Optional[int]    =				writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  if not fields:
    lowerCamelCase :					Dict    =				{"col_1": pa.string(), "col_2": pa.intaa()}
  assert writer._schema == pa.schema(__UpperCAmelCase      ,						metadata=writer._schema.metadata	)
  _check_output(output.getvalue()      ,						expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)






@pytest.mark.parametrize("writer_batch_size"      ,						[None, 1, 10]	)
@pytest.mark.parametrize(
    "fields"      ,						[None, {"col_1": pa.string(), "col_2": pa.intaa()}, {"col_1": pa.string(), "col_2": pa.intaa()}]	)
def 		lowercase_(  SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					Any    =				pa.BufferOutputStream()
  lowerCamelCase :					str    =				pa.schema(__UpperCAmelCase	) if fields else None
  with ArrowWriter(stream=__UpperCAmelCase      ,						schema=__UpperCAmelCase      ,						writer_batch_size=__UpperCAmelCase	) as writer:
    writer.write_table(pa.Table.from_pydict({"col_1": ["foo", "bar"], "col_2": [1, 2]}	)	)
    lowerCamelCase    ,	lowerCamelCase :					Union[str, Any]    =				writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  if not fields:
    lowerCamelCase :					Tuple    =				{"col_1": pa.string(), "col_2": pa.intaa()}
  assert writer._schema == pa.schema(__UpperCAmelCase      ,						metadata=writer._schema.metadata	)
  _check_output(output.getvalue()      ,						expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)






@pytest.mark.parametrize("writer_batch_size"      ,						[None, 1, 10]	)
@pytest.mark.parametrize(
    "fields"      ,						[None, {"col_1": pa.string(), "col_2": pa.intaa()}, {"col_1": pa.string(), "col_2": pa.intaa()}]	)
def 		lowercase_(  SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					Tuple    =				pa.BufferOutputStream()
  lowerCamelCase :					List[Any]    =				pa.schema(__UpperCAmelCase	) if fields else None
  with ArrowWriter(stream=__UpperCAmelCase      ,						schema=__UpperCAmelCase      ,						writer_batch_size=__UpperCAmelCase	) as writer:
    writer.write_row(pa.Table.from_pydict({"col_1": ["foo"], "col_2": [1]}	)	)
    writer.write_row(pa.Table.from_pydict({"col_1": ["bar"], "col_2": [2]}	)	)
    lowerCamelCase    ,	lowerCamelCase :					Union[str, Any]    =				writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  if not fields:
    lowerCamelCase :					Dict    =				{"col_1": pa.string(), "col_2": pa.intaa()}
  assert writer._schema == pa.schema(__UpperCAmelCase      ,						metadata=writer._schema.metadata	)
  _check_output(output.getvalue()      ,						expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)






def 		lowercase_(  ):


  '''simple docstring'''

  with tempfile.TemporaryDirectory() as tmp_dir:
    lowerCamelCase :					Optional[int]    =				{"col_1": pa.string(), "col_2": pa.intaa()}
    lowerCamelCase :					Tuple    =				os.path.join(__UpperCAmelCase      ,						"test.arrow"	)
    with ArrowWriter(path=__UpperCAmelCase      ,						schema=pa.schema(__UpperCAmelCase	)	) as writer:
      writer.write_batch({"col_1": ["foo", "bar"], "col_2": [1, 2]}	)
      lowerCamelCase    ,	lowerCamelCase :					int    =				writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    assert writer._schema == pa.schema(__UpperCAmelCase      ,						metadata=writer._schema.metadata	)
    _check_output(__UpperCAmelCase      ,						1	)






def 		lowercase_(  SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  if pa.types.is_list(__UpperCAmelCase	):
    return get_base_dtype(arr_type.value_type	)
  else:
    return arr_type






def 		lowercase_(  SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  if isinstance(lst[0]      ,						__UpperCAmelCase	):
    change_first_primitive_element_in_list(lst[0]      ,						__UpperCAmelCase	)
  else:
    lowerCamelCase :					Any    =				value






@pytest.mark.parametrize("optimized_int_type, expected_dtype"      ,						[(None, pa.intaa()), (Value("int32"	), pa.intaa())]	)
@pytest.mark.parametrize("sequence"      ,						[[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]	)
def 		lowercase_(  SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					Optional[int]    =				pa.array(TypedSequence(__UpperCAmelCase      ,						optimized_int_type=__UpperCAmelCase	)	)
  assert get_base_dtype(arr.type	) == expected_dtype






@pytest.mark.parametrize(
    "col, expected_dtype"      ,						[
        ("attention_mask", pa.inta()),
        ("special_tokens_mask", pa.inta()),
        ("token_type_ids", pa.inta()),
        ("input_ids", pa.intaa()),
        ("other", pa.intaa()),
    ]      ,						)
@pytest.mark.parametrize("sequence"      ,						[[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]	)
def 		lowercase_(  SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					int    =				pa.array(OptimizedTypedSequence(__UpperCAmelCase      ,						col=__UpperCAmelCase	)	)
  assert get_base_dtype(arr.type	) == expected_dtype

  # not in range
  if col != "other":
    # avoids errors due to in-place modifications
    lowerCamelCase :					List[str]    =				copy.deepcopy(__UpperCAmelCase	)
    lowerCamelCase :					Dict    =				np.iinfo(expected_dtype.to_pandas_dtype()	).max + 1
    change_first_primitive_element_in_list(__UpperCAmelCase      ,						__UpperCAmelCase	)
    lowerCamelCase :					List[Any]    =				pa.array(OptimizedTypedSequence(__UpperCAmelCase      ,						col=__UpperCAmelCase	)	)
    assert get_base_dtype(arr.type	) == pa.intaa()






@pytest.mark.parametrize("raise_exception"      ,						[False, True]	)
def 		lowercase_(  SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					Any    =				str(tmp_path / "dataset-train.arrow"	)
  try:
    with ArrowWriter(path=__UpperCAmelCase	) as writer:
      if raise_exception:
        raise pa.lib.ArrowInvalid()
      else:
        writer.stream.close()
  except pa.lib.ArrowInvalid:
    pass
  finally:
    assert writer.stream.closed






def 		lowercase_(  SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					List[Any]    =				"mock://dataset-train.arrow"
  with ArrowWriter(path=__UpperCAmelCase      ,						storage_options=mockfs.storage_options	) as writer:
    assert isinstance(writer._fs      ,						type(__UpperCAmelCase	)	)
    assert writer._fs.storage_options == mockfs.storage_options
    writer.write({"col_1": "foo", "col_2": 1}	)
    writer.write({"col_1": "bar", "col_2": 2}	)
    lowerCamelCase    ,	lowerCamelCase :					Optional[int]    =				writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  assert mockfs.exists(__UpperCAmelCase	)






def 		lowercase_(  ):


  '''simple docstring'''

  lowerCamelCase :					Union[str, Any]    =				pa.BufferOutputStream()
  with ParquetWriter(stream=__UpperCAmelCase	) as writer:
    writer.write({"col_1": "foo", "col_2": 1}	)
    writer.write({"col_1": "bar", "col_2": 2}	)
    lowerCamelCase    ,	lowerCamelCase :					Optional[Any]    =				writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  lowerCamelCase :					Optional[Any]    =				pa.BufferReader(output.getvalue()	)
  lowerCamelCase :					Any    =				pq.read_table(__UpperCAmelCase	)
  assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}






@require_pil
@pytest.mark.parametrize("embed_local_files"      ,						[False, True]	)
def 		lowercase_(  SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  import PIL.Image

  lowerCamelCase :					str    =				str(tmp_path / "test_image_rgb.jpg"	)
  PIL.Image.fromarray(np.zeros((5, 5)      ,						dtype=np.uinta	)	).save(__UpperCAmelCase      ,						format="png"	)
  lowerCamelCase :					Tuple    =				pa.BufferOutputStream()
  with ParquetWriter(
      stream=__UpperCAmelCase      ,						features=Features({"image": Image()}	)      ,						embed_local_files=__UpperCAmelCase	) as writer:
    writer.write({"image": image_path}	)
    writer.finalize()
  lowerCamelCase :					int    =				pa.BufferReader(output.getvalue()	)
  lowerCamelCase :					int    =				pq.read_table(__UpperCAmelCase	)
  lowerCamelCase :					Union[str, Any]    =				pa_table.to_pydict()
  if embed_local_files:
    assert isinstance(out["image"][0]["path"]      ,						__UpperCAmelCase	)
    with open(__UpperCAmelCase      ,						"rb"	) as f:
      assert out["image"][0]["bytes"] == f.read()
  else:
    assert out["image"][0]["path"] == image_path
    assert out["image"][0]["bytes"] is None







def 		lowercase_(  ):


  '''simple docstring'''

  lowerCamelCase :					Union[str, Any]    =				pa.schema([pa.field("col_1"      ,						pa.string()      ,						nullable=__UpperCAmelCase	)]	)
  lowerCamelCase :					Dict    =				pa.BufferOutputStream()
  with ArrowWriter(stream=__UpperCAmelCase	) as writer:
    writer._build_writer(inferred_schema=__UpperCAmelCase	)
    assert writer._schema == pa.schema([pa.field("col_1"      ,						pa.string()	)]	)









'''simple docstring'''

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

import cva
import numpy as np

# Parrameters
a  :				Dict									=  (720, 1280)  # Height, Width
a  :				Tuple									=  (0.4, 0.6)  # if height or width lower than this scale, drop it.
a  :				Dict									=  1 / 100
a  :				str									=  ''
a  :				Any									=  ''
a  :				Optional[int]									=  ''
a  :				List[str]									=  250


def 		__magic_name__    (	)		->					None:

					'''simple docstring'''

					snake_case_			,snake_case_									=				get_dataset(__UpperCAmelCase,      __UpperCAmelCase	)
					for index in range(__UpperCAmelCase	):
										snake_case_									=				random.sample(range(len(__UpperCAmelCase	)	),      4	)
										snake_case_			,snake_case_			,snake_case_									=				update_image_and_anno(
										    __UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase,      filter_scale=__UpperCAmelCase,      )

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


def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase	)		->					tuple[list, list]:

					'''simple docstring'''

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

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

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


def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase = 0.0,      )		->					tuple[list, list, str]:

					'''simple docstring'''

					snake_case_									=				np.zeros([output_size[0], output_size[1], 3],      dtype=np.uinta	)
					snake_case_									=				scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
					snake_case_									=				scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
					snake_case_									=				int(scale_x * output_size[1]	)
					snake_case_									=				int(scale_y * output_size[0]	)

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

					'''simple docstring'''

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


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

