

import colorsys
import io

import cva
import matplotlib as mpl
import matplotlib.colors as mplc
import matplotlib.figure as mplfigure
import numpy as np
import torch
from matplotlib.backends.backend_agg import FigureCanvasAgg

from utils import img_tensorize


lowerCamelCase									= 1000







class 						__magic_name__      :

   '''simple docstring'''




   def __init__(    self,   lowercase_,   lowercase_=1.2,   lowercase_="g",   lowercase_=0.5,   lowercase_="-",   lowercase_="test_out.jpg",   lowercase_=True,   lowercase_=False,   lowercase_=None,   lowercase_=None,   lowercase_=0.7,   )							->   Optional[Any]:






     """simple docstring"""






     if isinstance(lowercase_,   torch.Tensor	):
       a__  =img.numpy().astype('''np.uint8'''	)
     if isinstance(lowercase_,   lowercase_	):
       a__  =img_tensorize(lowercase_	)
     assert isinstance(lowercase_,   np.ndarray	)

     a__,				a__  =img.shape[1], img.shape[0]
     a__  =mplfigure.Figure(frameon=lowercase_	)
     a__  =fig.get_dpi()
     a__  =(width * scale + 1E-2) / dpi
     a__  =(height * scale + 1E-2) / dpi
     fig.set_size_inches(lowercase_,   lowercase_	)
     a__  =fig.add_axes([0.0, 0.0, 1.0, 1.0]	)
     ax.axis('''off'''	)
     ax.set_xlim(0.0,   lowercase_	)
     ax.set_ylim(lowercase_	)

     a__  =saveas
     a__  =rgb
     a__  =pynb
     a__  =img
     a__  =edgecolor
     a__  =0.5
     a__  =linestyle
     a__  =int(np.sqrt(min(lowercase_,   lowercase_	)	) * scale // 3	)
     a__  =width
     a__  =height
     a__  =scale
     a__  =fig
     a__  =ax
     a__  =pad
     a__  =idaobj
     a__  =idaattr
     a__  =FigureCanvasAgg(lowercase_	)



   def 			_UpperCAmelCase			(    self,   lowercase_,   lowercase_=None	)							->   Dict:






     """simple docstring"""






     if color is None:
       a__  =self.edgecolor
     ((a__),				(a__),				(a__),				(a__))  =box
     a__  =xa - xa
     a__  =ya - ya
     self.ax.add_patch(
         mpl.patches.Rectangle(
             (xa, ya),   lowercase_,   lowercase_,   fill=lowercase_,   edgecolor=lowercase_,   linewidth=self.font_size // 3,   alpha=self.alpha,   linestyle=self.linestyle,   )	)



   def 			_UpperCAmelCase			(    self,   lowercase_,   lowercase_=None,   lowercase_=None,   lowercase_=None,   lowercase_=None	)							->   Union[str, Any]:






     """simple docstring"""






     if len(boxes.shape	) > 2:
       a__  =boxes[0]
     if len(obj_ids.shape	) > 1:
       a__  =obj_ids[0]
     if len(obj_scores.shape	) > 1:
       a__  =obj_scores[0]
     if len(attr_ids.shape	) > 1:
       a__  =attr_ids[0]
     if len(attr_scores.shape	) > 1:
       a__  =attr_scores[0]
     if isinstance(lowercase_,   torch.Tensor	):
       a__  =boxes.numpy()
     if isinstance(lowercase_,   lowercase_	):
       a__  =np.array(lowercase_	)
     assert isinstance(lowercase_,   np.ndarray	)
     a__  =np.prod(boxes[:, 2:] - boxes[:, :2],   axis=1	)
     a__  =np.argsort(-areas	).tolist()
     a__  =boxes[sorted_idxs] if boxes is not None else None
     a__  =obj_ids[sorted_idxs] if obj_ids is not None else None
     a__  =obj_scores[sorted_idxs] if obj_scores is not None else None
     a__  =attr_ids[sorted_idxs] if attr_ids is not None else None
     a__  =attr_scores[sorted_idxs] if attr_scores is not None else None

     a__  =[self._random_color(maximum=1	) for _ in range(len(lowercase_	)	)]
     a__  =[assigned_colors[idx] for idx in sorted_idxs]
     if obj_ids is not None:
       a__  =self._create_text_labels_attr(lowercase_,   lowercase_,   lowercase_,   lowercase_	)
       for i in range(len(lowercase_	)	):
         a__  =assigned_colors[i]
         self.add_box(boxes[i],   lowercase_	)
         self.draw_labels(labels[i],   boxes[i],   lowercase_	)



   def 			_UpperCAmelCase			(    self,   lowercase_,   lowercase_,   lowercase_	)							->   Any:






     """simple docstring"""






     a__,				a__,				a__,				a__  =box
     a__  =(xa, ya)
     a__  =(ya - ya) * (xa - xa)
     a__  =_SMALL_OBJ * self.scale
     if instance_area < small or ya - ya < 40 * self.scale:
       if ya >= self.height - 5:
         a__  =(xa, ya)
       else:
         a__  =(xa, ya)

     a__  =(ya - ya) / np.sqrt(self.height * self.width	)
     a__  =self._change_color_brightness(lowercase_,   brightness_factor=0.7	)
     a__  =np.clip((height_ratio - 0.02) / 0.08 + 1,   1.2,   2	)
     font_size *= 0.75 * self.font_size

     self.draw_text(
         text=lowercase_,   position=lowercase_,   color=lowercase_,   )



   def 			_UpperCAmelCase			(    self,   lowercase_,   lowercase_,   lowercase_="g",   lowercase_="left",   )							->   Optional[Any]:






     """simple docstring"""






     a__  =0
     a__  =self.font_size
     a__  =np.maximum(list(mplc.to_rgb(lowercase_	)	),   0.2	)
     a__  =max(0.8,   np.max(lowercase_	)	)
     a__  ={
         '''facecolor''': '''black''',
         '''alpha''': self.alpha,
         '''pad''': self.pad,
         '''edgecolor''': '''none''',
     }
     a__,				a__  =position
     self.ax.text(
         lowercase_,   lowercase_,   lowercase_,   size=font_size * self.scale,   family='''sans-serif''',   bbox=lowercase_,   verticalalignment='''top''',   horizontalalignment=lowercase_,   color=lowercase_,   zorder=10,   rotation=lowercase_,   )



   def 			_UpperCAmelCase			(    self,   lowercase_=None	)							->   List[Any]:






     """simple docstring"""






     if saveas is None:
       a__  =self.saveas
     if saveas.lower().endswith('''.jpg'''	) or saveas.lower().endswith('''.png'''	):
       cva.imwrite(
           lowercase_,   self._get_buffer()[:, :, ::-1],   )
     else:
       self.fig.savefig(lowercase_	)



   def 			_UpperCAmelCase			(    self,   lowercase_,   lowercase_,   lowercase_,   lowercase_	)							->   Tuple:






     """simple docstring"""






     a__  =[self.idaobj[i] for i in classes]
     a__  =[self.idaattr[i] for i in attr_classes]
     a__  =[
         F"""{label} {score:.2f} {attr} {attr_score:.2f}"""
         for label, score, attr, attr_score in zip(lowercase_,   lowercase_,   lowercase_,   lowercase_	)
     ]
     return labels



   def 			_UpperCAmelCase			(    self,   lowercase_,   lowercase_	)							->   Union[str, Any]:






     """simple docstring"""






     a__  =[self.idaobj[i] for i in classes]
     if scores is not None:
       if labels is None:
         a__  =['''{:.0f}%'''.format(s * 100	) for s in scores]
       else:
         a__  =['''{} {:.0f}%'''.format(lowercase_,   s * 100	) for li, s in zip(lowercase_,   lowercase_	)]
     return labels



   def 			_UpperCAmelCase			(    self,   lowercase_=255	)							->   Optional[int]:






     """simple docstring"""






     a__  =np.random.randint(0,   len(_COLORS	)	)
     a__  =_COLORS[idx] * maximum
     if not self.rgb:
       a__  =ret[::-1]
     return ret



   def 			_UpperCAmelCase			(    self	)							->   int:






     """simple docstring"""






     if not self.pynb:
       a__,				a__  =self.canvas.print_to_buffer()
       if (width, height) != (self.width, self.height):
         a__  =cva.resize(self.img,   (width, height)	)
       else:
         a__  =self.img
     else:
       a__  =io.BytesIO()  # works for cairo backend
       self.canvas.print_rgba(lowercase_	)
       a__,				a__  =self.width, self.height
       a__  =buf.getvalue()
       a__  =self.img

     a__  =np.frombuffer(lowercase_,   dtype='''uint8'''	)
     a__  =buffer.reshape(lowercase_,   lowercase_,   4	)
     a__,				a__  =np.split(lowercase_,   [3],   axis=2	)

     try:
       import numexpr as ne  # fuse them with numexpr

       a__  =ne.evaluate('''img * (1 - alpha / 255.0) + rgb * (alpha / 255.0)'''	)
     except ImportError:
       a__  =alpha.astype('''float32'''	) / 255.0
       a__  =img * (1 - alpha) + rgb * alpha

     return visualized_image.astype('''uint8'''	)



   def 			_UpperCAmelCase			(    self,   lowercase_,   lowercase_	)							->   List[str]:






     """simple docstring"""






     assert brightness_factor >= -1.0 and brightness_factor <= 1.0
     a__  =mplc.to_rgb(lowercase_	)
     a__  =colorsys.rgb_to_hls(*mplc.to_rgb(lowercase_	)	)
     a__  =polygon_color[1] + (brightness_factor * polygon_color[1])
     a__  =0.0 if modified_lightness < 0.0 else modified_lightness
     a__  =1.0 if modified_lightness > 1.0 else modified_lightness
     a__  =colorsys.hls_to_rgb(polygon_color[0],   lowercase_,   polygon_color[2]	)
     return modified_color





lowerCamelCase									= (
    np.array(
        [
            0.000,
            0.447,
            0.741,
            0.850,
            0.325,
            0.098,
            0.929,
            0.694,
            0.125,
            0.494,
            0.184,
            0.556,
            0.466,
            0.674,
            0.188,
            0.301,
            0.745,
            0.933,
            0.635,
            0.078,
            0.184,
            0.300,
            0.300,
            0.300,
            0.600,
            0.600,
            0.600,
            1.000,
            0.000,
            0.000,
            1.000,
            0.500,
            0.000,
            0.749,
            0.749,
            0.000,
            0.000,
            1.000,
            0.000,
            0.000,
            0.000,
            1.000,
            0.667,
            0.000,
            1.000,
            0.333,
            0.333,
            0.000,
            0.333,
            0.667,
            0.000,
            0.333,
            1.000,
            0.000,
            0.667,
            0.333,
            0.000,
            0.667,
            0.667,
            0.000,
            0.667,
            1.000,
            0.000,
            1.000,
            0.333,
            0.000,
            1.000,
            0.667,
            0.000,
            1.000,
            1.000,
            0.000,
            0.000,
            0.333,
            0.500,
            0.000,
            0.667,
            0.500,
            0.000,
            1.000,
            0.500,
            0.333,
            0.000,
            0.500,
            0.333,
            0.333,
            0.500,
            0.333,
            0.667,
            0.500,
            0.333,
            1.000,
            0.500,
            0.667,
            0.000,
            0.500,
            0.667,
            0.333,
            0.500,
            0.667,
            0.667,
            0.500,
            0.667,
            1.000,
            0.500,
            1.000,
            0.000,
            0.500,
            1.000,
            0.333,
            0.500,
            1.000,
            0.667,
            0.500,
            1.000,
            1.000,
            0.500,
            0.000,
            0.333,
            1.000,
            0.000,
            0.667,
            1.000,
            0.000,
            1.000,
            1.000,
            0.333,
            0.000,
            1.000,
            0.333,
            0.333,
            1.000,
            0.333,
            0.667,
            1.000,
            0.333,
            1.000,
            1.000,
            0.667,
            0.000,
            1.000,
            0.667,
            0.333,
            1.000,
            0.667,
            0.667,
            1.000,
            0.667,
            1.000,
            1.000,
            1.000,
            0.000,
            1.000,
            1.000,
            0.333,
            1.000,
            1.000,
            0.667,
            1.000,
            0.333,
            0.000,
            0.000,
            0.500,
            0.000,
            0.000,
            0.667,
            0.000,
            0.000,
            0.833,
            0.000,
            0.000,
            1.000,
            0.000,
            0.000,
            0.000,
            0.167,
            0.000,
            0.000,
            0.333,
            0.000,
            0.000,
            0.500,
            0.000,
            0.000,
            0.667,
            0.000,
            0.000,
            0.833,
            0.000,
            0.000,
            1.000,
            0.000,
            0.000,
            0.000,
            0.167,
            0.000,
            0.000,
            0.333,
            0.000,
            0.000,
            0.500,
            0.000,
            0.000,
            0.667,
            0.000,
            0.000,
            0.833,
            0.000,
            0.000,
            1.000,
            0.000,
            0.000,
            0.000,
            0.143,
            0.143,
            0.143,
            0.857,
            0.857,
            0.857,
            1.000,
            1.000,
            1.000,
        ]
    )
    .astype(np.floataa)
    .reshape(-1, 3)
)



from dataclasses import dataclass

lowerCamelCase									= '''0.1'''
lowerCamelCase									= '''Lucia Harcekova'''







@dataclass
class 						__magic_name__      :

   '''simple docstring'''




   lowerCamelCase__			:     int
   lowerCamelCase__			:     int
   lowerCamelCase__			:     str



   def __repr__(    self	)							->   str:






     """simple docstring"""






     return F"""({self.offset}, {self.length}, {self.indicator})"""







class 						__magic_name__      :

   '''simple docstring'''




   def __init__(    self,   lowercase_ = 13,   lowercase_ = 6	)							->   None:






     """simple docstring"""






     a__  =window_size
     a__  =lookahead_buffer_size
     a__  =self.window_size - self.lookahead_buffer_size



   def 			_UpperCAmelCase			(    self,   lowercase_	)							->   list[Token]:






     """simple docstring"""






     a__  =[]
     a__  =''''''

     # while there are still characters in text to compress
     while text:
       # find the next encoding phrase
       # - triplet with offset, length, indicator (the next encoding character)
       a__  =self._find_encoding_token(lowercase_,   lowercase_	)

       # update the search buffer:
       # - add new characters from text into it
       # - check if size exceed the max search buffer size, if so, drop the
       #   oldest elements
       search_buffer += text[: token.length + 1]
       if len(lowercase_	) > self.search_buffer_size:
         a__  =search_buffer[-self.search_buffer_size :]

       # update the text
       a__  =text[token.length + 1 :]

       # append the token to output
       output.append(lowercase_	)

     return output



   def 			_UpperCAmelCase			(    self,   lowercase_	)							->   str:






     """simple docstring"""






     a__  =''''''

     for token in tokens:
       for _ in range(token.length	):
         output += output[-token.offset]
       output += token.indicator

     return output



   def 			_UpperCAmelCase			(    self,   lowercase_,   lowercase_	)							->   Token:






     """simple docstring"""






     if not text:
       raise ValueError('''We need some text to work with.'''	)

     # Initialise result parameters to default values
     a__,				a__  =0, 0

     if not search_buffer:
       return Token(lowercase_,   lowercase_,   text[length]	)

     for i, character in enumerate(lowercase_	):
       a__  =len(lowercase_	) - i
       if character == text[0]:
         a__  =self._match_length_from_index(lowercase_,   lowercase_,   0,   lowercase_	)
         # if the found length is bigger than the current or if it's equal,
         # which means it's offset is smaller: update offset and length
         if found_length >= length:
           a__,				a__  =found_offset, found_length

     return Token(lowercase_,   lowercase_,   text[length]	)



   def 			_UpperCAmelCase			(    self,   lowercase_,   lowercase_,   lowercase_,   lowercase_	)							->   int:






     """simple docstring"""






     if not text or text[text_index] != window[window_index]:
       return 0
     return 1 + self._match_length_from_index(
         lowercase_,   window + text[text_index],   text_index + 1,   window_index + 1	)


if __name__ == "__main__":
       from doctest import testmod

       testmod()
       # Initialize compressor class
       lowerCamelCase									= LZaaCompressor(window_size=13, lookahead_buffer_size=6)

       # Example
       lowerCamelCase									= '''cabracadabrarrarrad'''
       lowerCamelCase									= lzaa_compressor.compress(TEXT)
       print(lzaa_compressor.compress('''ababcbababaa'''))
       lowerCamelCase									= lzaa_compressor.decompress(compressed_text)
       assert decompressed_text == TEXT, "The LZ77 algorithm returned the invalid result."
