



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


A_		:  str										=  10_00



class 		_lowercase		:

   def __init__(   self      :							int				, __lowerCAmelCase      :							List[str]				, __lowerCAmelCase      :							Optional[Any]=1.2				, __lowerCAmelCase      :							Any="g"				, __lowerCAmelCase      :							int=0.5				, __lowerCAmelCase      :							Optional[Any]="-"				, __lowerCAmelCase      :							Union[str, Any]="test_out.jpg"				, __lowerCAmelCase      :							List[str]=True				, __lowerCAmelCase      :							int=False				, __lowerCAmelCase      :							Dict=None				, __lowerCAmelCase      :							Any=None				, __lowerCAmelCase      :							Union[str, Any]=0.7				, )							->					int:


    """simple docstring"""






    if isinstance(lowerCamelCase_				, torch.Tensor				):
     a							=		img.numpy().astype("np.uint8"				)
    if isinstance(lowerCamelCase_				, lowerCamelCase_				):
     a							=		img_tensorize(lowerCamelCase_				)
    assert isinstance(lowerCamelCase_				, np.ndarray				)

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

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

   def 		A				(   self      :							List[str]				, __lowerCAmelCase      :							str				, __lowerCAmelCase      :							Optional[Any]=None				)							->					Any:


    """simple docstring"""






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

   def 		A				(   self      :							Tuple				, __lowerCAmelCase      :							Dict				, __lowerCAmelCase      :							Any=None				, __lowerCAmelCase      :							Tuple=None				, __lowerCAmelCase      :							int=None				, __lowerCAmelCase      :							Optional[int]=None				)							->					Dict:


    """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(lowerCamelCase_				, torch.Tensor				):
     a							=		boxes.numpy()
    if isinstance(lowerCamelCase_				, lowerCamelCase_				):
     a							=		np.array(lowerCamelCase_				)
    assert isinstance(lowerCamelCase_				, 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(lowerCamelCase_				)				)]
    a							=		[assigned_colors[idx] for idx in sorted_idxs]
    if obj_ids is not None:
     a							=		self._create_text_labels_attr(lowerCamelCase_				, lowerCamelCase_				, lowerCamelCase_				, lowerCamelCase_				)
     for i in range(len(lowerCamelCase_				)				):
      a							=		assigned_colors[i]
      self.add_box(boxes[i]				, lowerCamelCase_				)
      self.draw_labels(labels[i]				, boxes[i]				, lowerCamelCase_				)

   def 		A				(   self      :							Union[str, Any]				, __lowerCAmelCase      :							Dict				, __lowerCAmelCase      :							Optional[int]				, __lowerCAmelCase      :							List[str]				)							->					Any:


    """simple docstring"""






    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(lowerCamelCase_				, brightness_factor=0.7				)
    a							=		np.clip((height_ratio - 0.0_2) / 0.0_8 + 1				, 1.2				, 2				)
    font_size *= 0.7_5 * self.font_size

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

   def 		A				(   self      :							str				, __lowerCAmelCase      :							Optional[int]				, __lowerCAmelCase      :							Any				, __lowerCAmelCase      :							Any="g"				, __lowerCAmelCase      :							List[str]="left"				, )							->					Tuple:


    """simple docstring"""






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

   def 		A				(   self      :							int				, __lowerCAmelCase      :							Tuple=None				)							->					Any:


    """simple docstring"""






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

   def 		A				(   self      :							str				, __lowerCAmelCase      :							Dict				, __lowerCAmelCase      :							Optional[int]				, __lowerCAmelCase      :							int				, __lowerCAmelCase      :							List[str]				)							->					str:


    """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(lowerCamelCase_				, lowerCamelCase_				, lowerCamelCase_				, lowerCamelCase_				)
    ]
    return labels

   def 		A				(   self      :							Optional[int]				, __lowerCAmelCase      :							Union[str, Any]				, __lowerCAmelCase      :							Union[str, Any]				)							->					List[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(lowerCamelCase_				, s * 100				) for li, s in zip(lowerCamelCase_				, lowerCamelCase_				)]
    return labels

   def 		A				(   self      :							List[Any]				, __lowerCAmelCase      :							Union[str, Any]=255				)							->					Dict:


    """simple docstring"""






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

   def 		A				(   self      :							Optional[Any]				)							->					Optional[Any]:


    """simple docstring"""






    if not self.pynb:
     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(lowerCamelCase_				)
     a							=		self.width, self.height
     a							=		buf.getvalue()
     a							=		self.img

    a							=		np.frombuffer(lowerCamelCase_				, dtype="uint8"				)
    a							=		buffer.reshape(lowerCamelCase_				, lowerCamelCase_				, 4				)
    a							=		np.split(lowerCamelCase_				, [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 		A				(   self      :							List[Any]				, __lowerCAmelCase      :							Optional[int]				, __lowerCAmelCase      :							int				)							->					int:


    """simple docstring"""






    assert brightness_factor >= -1.0 and brightness_factor <= 1.0
    a							=		mplc.to_rgb(lowerCamelCase_				)
    a							=		colorsys.rgb_to_hls(*mplc.to_rgb(lowerCamelCase_				)				)
    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]				, lowerCamelCase_				, polygon_color[2]				)
    return modified_color

A_		:  Optional[Any]										=  (
    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 __future__ import annotations

from abc import abstractmethod
from collections.abc import Iterable
from typing import Generic, Protocol, TypeVar


class 	a__						(    lowerCAmelCase_     ):

       @abstractmethod
       def __lt__( self   :  T   ,				lowerCamelCase_   :  T     ):
            pass

       @abstractmethod
       def __gt__( self   :  T   ,				lowerCamelCase_   :  T     ):
            pass

       @abstractmethod
       def __eq__( self   :  T   ,				lowerCamelCase_   :  object     ):
            pass

__lowerCamelCase   	=  TypeVar('''T''', bound=Comparable)


class 	a__						(    Generic[T]     ):

       def __init__( self   :  Tuple     ):
            a_     :  list[T]				      =     []
            a_     :  int				      =     0

       def __repr__( self   :  Optional[Any]     ):
            return str(self.h     )

       def     UpperCAmelCase( self   :  Dict   ,				lowerCamelCase_   :  int     ):
            if child_idx > 0:
                 return (child_idx - 1) // 2
            return None

       def     UpperCAmelCase( self   :  Any   ,				lowerCamelCase_   :  int     ):
            a_     :  Tuple				      =     2 * parent_idx + 1
            if left_child_index < self.heap_size:
                 return left_child_index
            return None

       def     UpperCAmelCase( self   :  List[Any]   ,				lowerCamelCase_   :  int     ):
            a_     :  List[Any]				      =     2 * parent_idx + 2
            if right_child_index < self.heap_size:
                 return right_child_index
            return None

       def     UpperCAmelCase( self   :  Optional[int]   ,				lowerCamelCase_   :  int     ):
            if index < self.heap_size:
                 a_     :  int				      =     index
                 a_     :  Union[str, Any]				      =     self.left_child_idx(lowerCamelCase_     )
                 a_     :  Optional[int]				      =     self.right_child_idx(lowerCamelCase_     )
                 # check which child is larger than its parent
                 if left_child is not None and self.h[left_child] > self.h[violation]:
                      a_     :  str				      =     left_child
                 if right_child is not None and self.h[right_child] > self.h[violation]:
                      a_     :  List[Any]				      =     right_child
                 # if violation indeed exists
                 if violation != index:
                      # swap to fix the violation
                      a_      ,      a_     :  int				      =     self.h[index], self.h[violation]
                      # fix the subsequent violation recursively if any
                      self.max_heapify(lowerCamelCase_     )

       def     UpperCAmelCase( self   :  List[str]   ,				lowerCamelCase_   :  Iterable[T]     ):
            a_     :  Dict				      =     list(lowerCamelCase_     )
            a_     :  int				      =     len(self.h     )
            if self.heap_size > 1:
                 # max_heapify from right to left but exclude leaves (last level)
                 for i in range(self.heap_size // 2 - 1   ,				-1   ,				-1     ):
                      self.max_heapify(lowerCamelCase_     )

       def     UpperCAmelCase( self   :  Tuple     ):
            if self.heap_size >= 2:
                 a_     :  int				      =     self.h[0]
                 a_     :  Dict				      =     self.h.pop(-1     )
                 self.heap_size -= 1
                 self.max_heapify(0     )
                 return me
            elif self.heap_size == 1:
                 self.heap_size -= 1
                 return self.h.pop(-1     )
            else:
                 raise Exception("""Empty heap"""     )

       def     UpperCAmelCase( self   :  List[str]   ,				lowerCamelCase_   :  T     ):
            self.h.append(lowerCamelCase_     )
            a_     :  Optional[int]				      =     (self.heap_size - 1) // 2
            self.heap_size += 1
            while idx >= 0:
                 self.max_heapify(lowerCamelCase_     )
                 a_     :  Union[str, Any]				      =     (idx - 1) // 2

       def     UpperCAmelCase( self   :  int     ):
            a_     :  Union[str, Any]				      =     self.heap_size
            for j in range(size - 1   ,				0   ,				-1     ):
                 a_      ,      a_     :  str				      =     self.h[j], self.h[0]
                 self.heap_size -= 1
                 self.max_heapify(0     )
            a_     :  Union[str, Any]				      =     size


if __name__ == "__main__":
       import doctest

       # run doc test
       doctest.testmod()

       # demo
       for unsorted in [
           [0],
           [2],
           [3, 5],
           [5, 3],
           [5, 5],
           [0, 0, 0, 0],
           [1, 1, 1, 1],
           [2, 2, 3, 5],
           [0, 2, 2, 3, 5],
           [2, 5, 3, 0, 2, 3, 0, 3],
           [6, 1, 2, 7, 9, 3, 4, 5, 10, 8],
           [103, 9, 1, 7, 11, 15, 25, 201, 209, 107, 5],
           [-45, -2, -5],
       ]:
              print(f'''unsorted array: {unsorted}''')

              __lowerCamelCase   	=  Heap()
              heap.build_max_heap(unsorted)
              print(f'''after build heap: {heap}''')

              print(f'''max value: {heap.extract_max()}''')
              print(f'''after max value removed: {heap}''')

              heap.insert(100)
              print(f'''after new value 100 inserted: {heap}''')

              heap.heap_sort()
              print(f'''heap-sorted array: {heap}\n''')



