'''simple docstring'''
import warnings
from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


a=  logging.get_logger(__name__)

a=  {
    '''nvidia/segformer-b0-finetuned-ade-512-512''': (
        '''https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json'''
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}






class 			__lowercase		(						_lowerCamelCase						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						'''segformer'''







     def __init__(		self     ,			_lowerCamelCase=3     ,			_lowerCamelCase=4     ,			_lowerCamelCase=[2, 2, 2, 2]     ,			_lowerCamelCase=[8, 4, 2, 1]     ,			_lowerCamelCase=[3_2, 6_4, 1_6_0, 2_5_6]     ,			_lowerCamelCase=[7, 3, 3, 3]     ,			_lowerCamelCase=[4, 2, 2, 2]     ,			_lowerCamelCase=[1, 2, 5, 8]     ,			_lowerCamelCase=[4, 4, 4, 4]     ,			_lowerCamelCase="gelu"     ,			_lowerCamelCase=0.0     ,			_lowerCamelCase=0.0     ,			_lowerCamelCase=0.1     ,			_lowerCamelCase=0.0_2     ,			_lowerCamelCase=0.1     ,			_lowerCamelCase=1E-6     ,			_lowerCamelCase=2_5_6     ,			_lowerCamelCase=2_5_5     ,			**_lowerCamelCase     ,			):
         super().__init__(**_lowerCamelCase    )

         if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
             warnings.warn(
                 'Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be'
                 ' removed, as the behaviour will default to that of reshape_last_stage = True.'     ,			_lowerCamelCase     ,			)

         __UpperCamelCase	:	List[str]		    =  num_channels
         __UpperCamelCase	:	Optional[int]		    =  num_encoder_blocks
         __UpperCamelCase	:	List[str]		    =  depths
         __UpperCamelCase	:	Optional[int]		    =  sr_ratios
         __UpperCamelCase	:	int		    =  hidden_sizes
         __UpperCamelCase	:	Union[str, Any]		    =  patch_sizes
         __UpperCamelCase	:	str		    =  strides
         __UpperCamelCase	:	int		    =  mlp_ratios
         __UpperCamelCase	:	Optional[int]		    =  num_attention_heads
         __UpperCamelCase	:	str		    =  hidden_act
         __UpperCamelCase	:	Dict		    =  hidden_dropout_prob
         __UpperCamelCase	:	Optional[int]		    =  attention_probs_dropout_prob
         __UpperCamelCase	:	int		    =  classifier_dropout_prob
         __UpperCamelCase	:	Union[str, Any]		    =  initializer_range
         __UpperCamelCase	:	Optional[int]		    =  drop_path_rate
         __UpperCamelCase	:	List[Any]		    =  layer_norm_eps
         __UpperCamelCase	:	Optional[Any]		    =  decoder_hidden_size
         __UpperCamelCase	:	int		    =  kwargs.get('reshape_last_stage'     ,			_lowerCamelCase    )
         __UpperCamelCase	:	List[str]		    =  semantic_loss_ignore_index






class 			__lowercase		(						_lowerCamelCase						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						version.parse('''1.11'''						)







     @property
     def lowerCAmelCase     (		self    ):
         return OrderedDict(
             [
                 ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
             ]    )







     @property
     def lowerCAmelCase     (		self    ):
         return 1E-4







     @property
     def lowerCAmelCase     (		self    ):
         return 1_2




'''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits

import cva
a=  ''''''
a=  ''''''
a=  ''''''
a=  1  # (0 is vertical, 1 is horizontal)







def  _UpperCamelCase (     ):




    """simple docstring"""



    __UpperCamelCase    ,					__UpperCamelCase	:	str		    =  get_dataset(_a				,     _a			)
    print('Processing...'			)
    __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	List[Any]		    =  update_image_and_anno(_a				,     _a				,     _a			)

    for index, image in enumerate(_a			):
        # Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
        __UpperCamelCase	:	Tuple		    =  random_chars(3_2			)
        __UpperCamelCase	:	Tuple		    =  paths[index].split(os.sep			)[-1].rsplit('.'				,     1			)[0]
        __UpperCamelCase	:	List[str]		    =  f"""{OUTPUT_DIR}/{file_name}_FLIP_{letter_code}"""
        cva.imwrite(f"""/{file_root}.jpg"""				,     _a				,     [cva.IMWRITE_JPEG_QUALITY, 8_5]			)
        print(f"""Success {index+1}/{len(_a			)} with {file_name}"""			)
        __UpperCamelCase	:	Tuple		    =  []
        for anno in new_annos[index]:
            __UpperCamelCase	:	Any		    =  f"""{anno[0]} {anno[1]} {anno[2]} {anno[3]} {anno[4]}"""
            annos_list.append(_a			)
        with open(f"""/{file_root}.txt"""				,     'w'			) as outfile:
            outfile.write('\n'.join(line for line in annos_list			)			)







def  _UpperCamelCase (     _a	:	str				,     _a	:	str			):




    """simple docstring"""



    __UpperCamelCase	:	List[str]		    =  []
    __UpperCamelCase	:	Union[str, Any]		    =  []
    for label_file in glob.glob(os.path.join(_a				,     '*.txt'			)			):
        __UpperCamelCase	:	Any		    =  label_file.split(os.sep			)[-1].rsplit('.'				,     1			)[0]
        with open(_a			) as in_file:
            __UpperCamelCase	:	Tuple		    =  in_file.readlines()
        __UpperCamelCase	:	Dict		    =  os.path.join(_a				,     f"""{label_name}.jpg"""			)

        __UpperCamelCase	:	Optional[Any]		    =  []
        for obj_list in obj_lists:
            __UpperCamelCase	:	Optional[Any]		    =  obj_list.rstrip('\n'			).split(' '			)
            boxes.append(
                [
                    int(obj[0]			),
                    float(obj[1]			),
                    float(obj[2]			),
                    float(obj[3]			),
                    float(obj[4]			),
                ]			)
        if not boxes:
            continue
        img_paths.append(_a			)
        labels.append(_a			)
    return img_paths, labels







def  _UpperCamelCase (     _a	:	list				,     _a	:	list				,     _a	:	int = 1			):




    """simple docstring"""



    __UpperCamelCase	:	List[str]		    =  []
    __UpperCamelCase	:	str		    =  []
    __UpperCamelCase	:	str		    =  []
    for idx in range(len(_a			)			):
        __UpperCamelCase	:	Union[str, Any]		    =  []
        __UpperCamelCase	:	List[str]		    =  img_list[idx]
        path_list.append(_a			)
        __UpperCamelCase	:	Dict		    =  anno_list[idx]
        __UpperCamelCase	:	List[str]		    =  cva.imread(_a			)
        if flip_type == 1:
            __UpperCamelCase	:	List[Any]		    =  cva.flip(_a				,     _a			)
            for bbox in img_annos:
                __UpperCamelCase	:	List[str]		    =  1 - bbox[1]
                new_annos.append([bbox[0], x_center_new, bbox[2], bbox[3], bbox[4]]			)
        elif flip_type == 0:
            __UpperCamelCase	:	Optional[Any]		    =  cva.flip(_a				,     _a			)
            for bbox in img_annos:
                __UpperCamelCase	:	List[str]		    =  1 - bbox[2]
                new_annos.append([bbox[0], bbox[1], y_center_new, bbox[3], bbox[4]]			)
        new_annos_lists.append(_a			)
        new_imgs_list.append(_a			)
    return new_imgs_list, new_annos_lists, path_list







def  _UpperCamelCase (     _a	:	int = 3_2			):




    """simple docstring"""



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


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



