


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


UpperCamelCase			:					Union[str, Any]         =							1_000

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



											'''simple docstring'''





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

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

											__magic_name__					=      saveas
											__magic_name__					=      rgb
											__magic_name__					=      pynb
											__magic_name__					=      img
											__magic_name__					=      edgecolor
											__magic_name__					=      0.5
											__magic_name__					=      linestyle
											__magic_name__					=      int(np.sqrt(min(_lowerCAmelCase	,      _lowerCAmelCase  )  ) * scale // 3  )
											__magic_name__					=      width
											__magic_name__					=      height
											__magic_name__					=      scale
											__magic_name__					=      fig
											__magic_name__					=      ax
											__magic_name__					=      pad
											__magic_name__					=      idaobj
											__magic_name__					=      idaattr
											__magic_name__					=      FigureCanvasAgg(_lowerCAmelCase  )
					def 	a			(						self       :						str	,      _lowerCAmelCase       :						int	,      _lowerCAmelCase       :						int=None  )							->					int:



											'''simple docstring'''





											if color is None:
																	__magic_name__					=      self.edgecolor
											((__magic_name__)		,      (__magic_name__)		,      (__magic_name__)		,      (__magic_name__))					=      box
											__magic_name__					=      xa - xa
											__magic_name__					=      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       :						str	,      _lowerCAmelCase       :						str	,      _lowerCAmelCase       :						Union[str, Any]=None	,      _lowerCAmelCase       :						List[Any]=None	,      _lowerCAmelCase       :						Optional[Any]=None	,      _lowerCAmelCase       :						List[Any]=None  )							->					List[Any]:



											'''simple docstring'''





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

											__magic_name__					=      [self._random_color(maximum=1  ) for _ in range(len(_lowerCAmelCase  )  )]
											__magic_name__					=      [assigned_colors[idx] for idx in sorted_idxs]
											if obj_ids is not None:
																	__magic_name__					=      self._create_text_labels_attr(_lowerCAmelCase	,      _lowerCAmelCase	,      _lowerCAmelCase	,      _lowerCAmelCase  )
																	for i in range(len(_lowerCAmelCase  )  ):
																							__magic_name__					=      assigned_colors[i]
																							self.add_box(boxes[i]	,      _lowerCAmelCase  )
																							self.draw_labels(labels[i]	,      boxes[i]	,      _lowerCAmelCase  )
					def 	a			(						self       :						int	,      _lowerCAmelCase       :						Optional[Any]	,      _lowerCAmelCase       :						str	,      _lowerCAmelCase       :						int  )							->					Tuple:



											'''simple docstring'''





											__magic_name__		,      __magic_name__		,      __magic_name__		,      __magic_name__					=      box
											__magic_name__					=      (xa, ya)
											__magic_name__					=      (ya - ya) * (xa - xa)
											__magic_name__					=      _SMALL_OBJ * self.scale
											if instance_area < small or ya - ya < 4_0 * self.scale:
																	if ya >= self.height - 5:
																							__magic_name__					=      (xa, ya)
																	else:
																							__magic_name__					=      (xa, ya)

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

											self.draw_text(
											    text=_lowerCAmelCase	,      position=_lowerCAmelCase	,      color=_lowerCAmelCase	,      )
					def 	a			(						self       :						Optional[int]	,      _lowerCAmelCase       :						List[str]	,      _lowerCAmelCase       :						Optional[int]	,      _lowerCAmelCase       :						Optional[int]="g"	,      _lowerCAmelCase       :						List[Any]="left"	,      )							->					Optional[int]:



											'''simple docstring'''





											__magic_name__					=      0
											__magic_name__					=      self.font_size
											__magic_name__					=      np.maximum(list(mplc.to_rgb(_lowerCAmelCase  )  )	,      0.2  )
											__magic_name__					=      max(0.8	,      np.max(_lowerCAmelCase  )  )
											__magic_name__					=      {
											    'facecolor': 'black',
											    'alpha': self.alpha,
											    'pad': self.pad,
											    'edgecolor': 'none',
											}
											__magic_name__		,      __magic_name__					=      position
											self.ax.text(
											    _lowerCAmelCase	,      _lowerCAmelCase	,      _lowerCAmelCase	,      size=font_size * self.scale	,      family='sans-serif'	,      bbox=_lowerCAmelCase	,      verticalalignment='top'	,      horizontalalignment=_lowerCAmelCase	,      color=_lowerCAmelCase	,      zorder=1_0	,      rotation=_lowerCAmelCase	,      )
					def 	a			(						self       :						Union[str, Any]	,      _lowerCAmelCase       :						Tuple=None  )							->					Optional[Any]:



											'''simple docstring'''





											if saveas is None:
																	__magic_name__					=      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       :						List[str]	,      _lowerCAmelCase       :						List[Any]	,      _lowerCAmelCase       :						Optional[Any]	,      _lowerCAmelCase       :						Optional[int]	,      _lowerCAmelCase       :						Union[str, Any]  )							->					Optional[Any]:



											'''simple docstring'''





											__magic_name__					=      [self.idaobj[i] for i in classes]
											__magic_name__					=      [self.idaattr[i] for i in attr_classes]
											__magic_name__					=      [
											    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       :						List[str]	,      _lowerCAmelCase       :						Union[str, Any]	,      _lowerCAmelCase       :						Any  )							->					Tuple:



											'''simple docstring'''





											__magic_name__					=      [self.idaobj[i] for i in classes]
											if scores is not None:
																	if labels is None:
																							__magic_name__					=      ['{:.0f}%'.format(s * 1_0_0  ) for s in scores]
																	else:
																							__magic_name__					=      ['{} {:.0f}%'.format(_lowerCAmelCase	,      s * 1_0_0  ) for li, s in zip(_lowerCAmelCase	,      _lowerCAmelCase  )]
											return labels
					def 	a			(						self       :						Union[str, Any]	,      _lowerCAmelCase       :						Optional[Any]=2_5_5  )							->					List[str]:



											'''simple docstring'''





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



											'''simple docstring'''





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

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

											try:
																	import numexpr as ne  # fuse them with numexpr

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

											return visualized_image.astype('uint8'  )







					def 	a			(						self       :						Optional[Any]	,      _lowerCAmelCase       :						Union[str, Any]	,      _lowerCAmelCase       :						Dict  )							->					Union[str, Any]:



											'''simple docstring'''





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







UpperCamelCase			:					List[str]         =							(
    np.array(
        [
            0.0_0_0,
            0.4_4_7,
            0.7_4_1,
            0.8_5_0,
            0.3_2_5,
            0.0_9_8,
            0.9_2_9,
            0.6_9_4,
            0.1_2_5,
            0.4_9_4,
            0.1_8_4,
            0.5_5_6,
            0.4_6_6,
            0.6_7_4,
            0.1_8_8,
            0.3_0_1,
            0.7_4_5,
            0.9_3_3,
            0.6_3_5,
            0.0_7_8,
            0.1_8_4,
            0.3_0_0,
            0.3_0_0,
            0.3_0_0,
            0.6_0_0,
            0.6_0_0,
            0.6_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.5_0_0,
            0.0_0_0,
            0.7_4_9,
            0.7_4_9,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.6_6_7,
            0.0_0_0,
            1.0_0_0,
            0.3_3_3,
            0.3_3_3,
            0.0_0_0,
            0.3_3_3,
            0.6_6_7,
            0.0_0_0,
            0.3_3_3,
            1.0_0_0,
            0.0_0_0,
            0.6_6_7,
            0.3_3_3,
            0.0_0_0,
            0.6_6_7,
            0.6_6_7,
            0.0_0_0,
            0.6_6_7,
            1.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.3_3_3,
            0.0_0_0,
            1.0_0_0,
            0.6_6_7,
            0.0_0_0,
            1.0_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.3_3_3,
            0.5_0_0,
            0.0_0_0,
            0.6_6_7,
            0.5_0_0,
            0.0_0_0,
            1.0_0_0,
            0.5_0_0,
            0.3_3_3,
            0.0_0_0,
            0.5_0_0,
            0.3_3_3,
            0.3_3_3,
            0.5_0_0,
            0.3_3_3,
            0.6_6_7,
            0.5_0_0,
            0.3_3_3,
            1.0_0_0,
            0.5_0_0,
            0.6_6_7,
            0.0_0_0,
            0.5_0_0,
            0.6_6_7,
            0.3_3_3,
            0.5_0_0,
            0.6_6_7,
            0.6_6_7,
            0.5_0_0,
            0.6_6_7,
            1.0_0_0,
            0.5_0_0,
            1.0_0_0,
            0.0_0_0,
            0.5_0_0,
            1.0_0_0,
            0.3_3_3,
            0.5_0_0,
            1.0_0_0,
            0.6_6_7,
            0.5_0_0,
            1.0_0_0,
            1.0_0_0,
            0.5_0_0,
            0.0_0_0,
            0.3_3_3,
            1.0_0_0,
            0.0_0_0,
            0.6_6_7,
            1.0_0_0,
            0.0_0_0,
            1.0_0_0,
            1.0_0_0,
            0.3_3_3,
            0.0_0_0,
            1.0_0_0,
            0.3_3_3,
            0.3_3_3,
            1.0_0_0,
            0.3_3_3,
            0.6_6_7,
            1.0_0_0,
            0.3_3_3,
            1.0_0_0,
            1.0_0_0,
            0.6_6_7,
            0.0_0_0,
            1.0_0_0,
            0.6_6_7,
            0.3_3_3,
            1.0_0_0,
            0.6_6_7,
            0.6_6_7,
            1.0_0_0,
            0.6_6_7,
            1.0_0_0,
            1.0_0_0,
            1.0_0_0,
            0.0_0_0,
            1.0_0_0,
            1.0_0_0,
            0.3_3_3,
            1.0_0_0,
            1.0_0_0,
            0.6_6_7,
            1.0_0_0,
            0.3_3_3,
            0.0_0_0,
            0.0_0_0,
            0.5_0_0,
            0.0_0_0,
            0.0_0_0,
            0.6_6_7,
            0.0_0_0,
            0.0_0_0,
            0.8_3_3,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.1_6_7,
            0.0_0_0,
            0.0_0_0,
            0.3_3_3,
            0.0_0_0,
            0.0_0_0,
            0.5_0_0,
            0.0_0_0,
            0.0_0_0,
            0.6_6_7,
            0.0_0_0,
            0.0_0_0,
            0.8_3_3,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.1_6_7,
            0.0_0_0,
            0.0_0_0,
            0.3_3_3,
            0.0_0_0,
            0.0_0_0,
            0.5_0_0,
            0.0_0_0,
            0.0_0_0,
            0.6_6_7,
            0.0_0_0,
            0.0_0_0,
            0.8_3_3,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.1_4_3,
            0.1_4_3,
            0.1_4_3,
            0.8_5_7,
            0.8_5_7,
            0.8_5_7,
            1.0_0_0,
            1.0_0_0,
            1.0_0_0,
        ]
    )
    .astype(np.floataa)
    .reshape(-1, 3)
)





from collections import OrderedDict
from dataclasses import fields
from typing import Any, Tuple

import numpy as np

from .import_utils import is_torch_available
def 				UpperCamelCase_	(					__snake_case      :    Dict  )->   str:




						'''simple docstring'''
						if is_torch_available():
												import torch

												if isinstance(__snake_case						,      torch.Tensor  ):
																		return True

						return isinstance(__snake_case						,      np.ndarray  )




class      __snake_case				(   _UpperCAmelCase):
					def 	a			(						self       :						Optional[Any]  )							->					Optional[Any]:



											'''simple docstring'''





											__magic_name__					=      fields(self  )

											# Safety and consistency checks
											if not len(_lowerCAmelCase  ):
																	raise ValueError(F'''{self.__class__.__name__} has no fields.'''  )

											__magic_name__					=      getattr(self	,      class_fields[0].name  )
											__magic_name__					=      all(getattr(self	,      field.name  ) is None for field in class_fields[1:]  )

											if other_fields_are_none and isinstance(_lowerCAmelCase	,      _lowerCAmelCase  ):
																	for key, value in first_field.items():
																							__magic_name__					=      value
											else:
																	for field in class_fields:
																							__magic_name__					=      getattr(self	,      field.name  )
																							if v is not None:
																													__magic_name__					=      v
					def __delitem__(						self       :						Dict	,      *_lowerCAmelCase       :						List[str]	,      **_lowerCAmelCase       :						List[str]  )							->					List[str]:



											'''simple docstring'''





											raise Exception(F'''You cannot use ``__delitem__`` on a {self.__class__.__name__} instance.'''  )
					def 	a			(						self       :						Optional[int]	,      *_lowerCAmelCase       :						Optional[Any]	,      **_lowerCAmelCase       :						Optional[Any]  )							->					str:



											'''simple docstring'''





											raise Exception(F'''You cannot use ``setdefault`` on a {self.__class__.__name__} instance.'''  )
					def 	a			(						self       :						Union[str, Any]	,      *_lowerCAmelCase       :						List[str]	,      **_lowerCAmelCase       :						Any  )							->					str:



											'''simple docstring'''





											raise Exception(F'''You cannot use ``pop`` on a {self.__class__.__name__} instance.'''  )
					def 	a			(						self       :						Any	,      *_lowerCAmelCase       :						str	,      **_lowerCAmelCase       :						Optional[int]  )							->					List[Any]:



											'''simple docstring'''





											raise Exception(F'''You cannot use ``update`` on a {self.__class__.__name__} instance.'''  )
					def __getitem__(						self       :						Optional[Any]	,      _lowerCAmelCase       :						Any  )							->					Tuple:



											'''simple docstring'''





											if isinstance(_lowerCAmelCase	,      _lowerCAmelCase  ):
																	__magic_name__					=      dict(self.items()  )
																	return inner_dict[k]
											else:
																	return self.to_tuple()[k]
					def __setattr__(						self       :						str	,      _lowerCAmelCase       :						Optional[Any]	,      _lowerCAmelCase       :						Optional[int]  )							->					int:



											'''simple docstring'''





											if name in self.keys() and value is not None:
																	# Don't call self.__setitem__ to avoid recursion errors
																	super().__setitem__(_lowerCAmelCase	,      _lowerCAmelCase  )
											super().__setattr__(_lowerCAmelCase	,      _lowerCAmelCase  )
					def __setitem__(						self       :						Optional[Any]	,      _lowerCAmelCase       :						Optional[Any]	,      _lowerCAmelCase       :						List[str]  )							->					Optional[int]:



											'''simple docstring'''





											super().__setitem__(_lowerCAmelCase	,      _lowerCAmelCase  )
											# Don't call self.__setattr__ to avoid recursion errors
											super().__setattr__(_lowerCAmelCase	,      _lowerCAmelCase  )







					def 	a			(						self       :						str  )							->					Tuple[Any]:



											'''simple docstring'''





											return tuple(self[k] for k in self.keys()  )

