






"""simple docstring"""





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


_SCREAMING_SNAKE_CASE :    Optional[Any]    =						1000






class 					a						:






    def __init__(	self					:							Any	,						__SCREAMING_SNAKE_CASE					:							int	,						__SCREAMING_SNAKE_CASE					:							List[Any]=1.2	,						__SCREAMING_SNAKE_CASE					:							List[Any]="g"	,						__SCREAMING_SNAKE_CASE					:							Optional[int]=0.5	,						__SCREAMING_SNAKE_CASE					:							int="-"	,						__SCREAMING_SNAKE_CASE					:							Any="test_out.jpg"	,						__SCREAMING_SNAKE_CASE					:							Any=True	,						__SCREAMING_SNAKE_CASE					:							str=False	,						__SCREAMING_SNAKE_CASE					:							List[str]=None	,						__SCREAMING_SNAKE_CASE					:							List[str]=None	,						__SCREAMING_SNAKE_CASE					:							str=0.7	,						)					->		Optional[Any]:
      if isinstance(UpperCamelCase__	,						torch.Tensor ):
        lowerCamelCase_   					=						img.numpy().astype('np.uint8' )
      if isinstance(UpperCamelCase__	,						UpperCamelCase__ ):
        lowerCamelCase_   					=						img_tensorize(UpperCamelCase__ )
      assert isinstance(UpperCamelCase__	,						np.ndarray )

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

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






    def        UpperCamelCase	(	self					:							str	,						__SCREAMING_SNAKE_CASE					:							Optional[int]	,						__SCREAMING_SNAKE_CASE					:							List[Any]=None )					->		Dict:
      if color is None:
        lowerCamelCase_   					=						self.edgecolor
      (lowerCamelCase_)   					=						box
      lowerCamelCase_   					=						xa - xa
      lowerCamelCase_   					=						ya - ya
      self.ax.add_patch(
          mpl.patches.Rectangle(
              (xa, ya)	,						UpperCamelCase__	,						UpperCamelCase__	,						fill=UpperCamelCase__	,						edgecolor=UpperCamelCase__	,						linewidth=self.font_size // 3	,						alpha=self.alpha	,						linestyle=self.linestyle	,						) )






    def        UpperCamelCase	(	self					:							List[str]	,						__SCREAMING_SNAKE_CASE					:							Optional[int]	,						__SCREAMING_SNAKE_CASE					:							Tuple=None	,						__SCREAMING_SNAKE_CASE					:							Optional[Any]=None	,						__SCREAMING_SNAKE_CASE					:							int=None	,						__SCREAMING_SNAKE_CASE					:							Union[str, Any]=None )					->		str:
      if len(boxes.shape ) > 2:
        lowerCamelCase_   					=						boxes[0]
      if len(obj_ids.shape ) > 1:
        lowerCamelCase_   					=						obj_ids[0]
      if len(obj_scores.shape ) > 1:
        lowerCamelCase_   					=						obj_scores[0]
      if len(attr_ids.shape ) > 1:
        lowerCamelCase_   					=						attr_ids[0]
      if len(attr_scores.shape ) > 1:
        lowerCamelCase_   					=						attr_scores[0]
      if isinstance(UpperCamelCase__	,						torch.Tensor ):
        lowerCamelCase_   					=						boxes.numpy()
      if isinstance(UpperCamelCase__	,						UpperCamelCase__ ):
        lowerCamelCase_   					=						np.array(UpperCamelCase__ )
      assert isinstance(UpperCamelCase__	,						np.ndarray )
      lowerCamelCase_   					=						np.prod(boxes[:, 2:] - boxes[:, :2]	,						axis=1 )
      lowerCamelCase_   					=						np.argsort(-areas ).tolist()
      lowerCamelCase_   					=						boxes[sorted_idxs] if boxes is not None else None
      lowerCamelCase_   					=						obj_ids[sorted_idxs] if obj_ids is not None else None
      lowerCamelCase_   					=						obj_scores[sorted_idxs] if obj_scores is not None else None
      lowerCamelCase_   					=						attr_ids[sorted_idxs] if attr_ids is not None else None
      lowerCamelCase_   					=						attr_scores[sorted_idxs] if attr_scores is not None else None

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






    def        UpperCamelCase	(	self					:							Union[str, Any]	,						__SCREAMING_SNAKE_CASE					:							Tuple	,						__SCREAMING_SNAKE_CASE					:							Union[str, Any]	,						__SCREAMING_SNAKE_CASE					:							Dict )					->		Any:
      lowerCamelCase_   					=						box
      lowerCamelCase_   					=						(xa, ya)
      lowerCamelCase_   					=						(ya - ya) * (xa - xa)
      lowerCamelCase_   					=						_SMALL_OBJ * self.scale
      if instance_area < small or ya - ya < 40 * self.scale:
        if ya >= self.height - 5:
          lowerCamelCase_   					=						(xa, ya)
        else:
          lowerCamelCase_   					=						(xa, ya)

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

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






    def        UpperCamelCase	(	self					:							Optional[int]	,						__SCREAMING_SNAKE_CASE					:							Union[str, Any]	,						__SCREAMING_SNAKE_CASE					:							List[Any]	,						__SCREAMING_SNAKE_CASE					:							Dict="g"	,						__SCREAMING_SNAKE_CASE					:							Optional[Any]="left"	,						)					->		Optional[Any]:
      lowerCamelCase_   					=						0
      lowerCamelCase_   					=						self.font_size
      lowerCamelCase_   					=						np.maximum(list(mplc.to_rgb(UpperCamelCase__ ) )	,						0.2 )
      lowerCamelCase_   					=						max(0.8	,						np.max(UpperCamelCase__ ) )
      lowerCamelCase_   					=						{
          "facecolor": "black",
          "alpha": self.alpha,
          "pad": self.pad,
          "edgecolor": "none",
      }
      lowerCamelCase_   					=						position
      self.ax.text(
          UpperCamelCase__	,						UpperCamelCase__	,						UpperCamelCase__	,						size=font_size * self.scale	,						family='sans-serif'	,						bbox=UpperCamelCase__	,						verticalalignment='top'	,						horizontalalignment=UpperCamelCase__	,						color=UpperCamelCase__	,						zorder=10	,						rotation=UpperCamelCase__	,						)






    def        UpperCamelCase	(	self					:							Optional[int]	,						__SCREAMING_SNAKE_CASE					:							List[str]=None )					->		Tuple:
      if saveas is None:
        lowerCamelCase_   					=						self.saveas
      if saveas.lower().endswith('.jpg' ) or saveas.lower().endswith('.png' ):
        cva.imwrite(
            UpperCamelCase__	,						self._get_buffer()[:, :, ::-1]	,						)
      else:
        self.fig.savefig(UpperCamelCase__ )






    def        UpperCamelCase	(	self					:							Tuple	,						__SCREAMING_SNAKE_CASE					:							Optional[Any]	,						__SCREAMING_SNAKE_CASE					:							List[str]	,						__SCREAMING_SNAKE_CASE					:							Optional[int]	,						__SCREAMING_SNAKE_CASE					:							Dict )					->		List[str]:
      lowerCamelCase_   					=						[self.idaobj[i] for i in classes]
      lowerCamelCase_   					=						[self.idaattr[i] for i in attr_classes]
      lowerCamelCase_   					=						[
          F'''{label} {score:.2f} {attr} {attr_score:.2f}'''
          for label, score, attr, attr_score in zip(UpperCamelCase__	,						UpperCamelCase__	,						UpperCamelCase__	,						UpperCamelCase__ )
      ]
      return labels






    def        UpperCamelCase	(	self					:							Optional[Any]	,						__SCREAMING_SNAKE_CASE					:							str	,						__SCREAMING_SNAKE_CASE					:							int )					->		Dict:
      lowerCamelCase_   					=						[self.idaobj[i] for i in classes]
      if scores is not None:
        if labels is None:
          lowerCamelCase_   					=						["{:.0f}%".format(s * 100 ) for s in scores]
        else:
          lowerCamelCase_   					=						["{} {:.0f}%".format(UpperCamelCase__	,						s * 100 ) for li, s in zip(UpperCamelCase__	,						UpperCamelCase__ )]
      return labels






    def        UpperCamelCase	(	self					:							Dict	,						__SCREAMING_SNAKE_CASE					:							List[str]=255 )					->		Optional[int]:
      lowerCamelCase_   					=						np.random.randint(0	,						len(_COLORS ) )
      lowerCamelCase_   					=						_COLORS[idx] * maximum
      if not self.rgb:
        lowerCamelCase_   					=						ret[::-1]
      return ret






    def        UpperCamelCase	(	self					:							List[Any] )					->		Optional[Any]:
      if not self.pynb:
        lowerCamelCase_   					=						self.canvas.print_to_buffer()
        if (width, height) != (self.width, self.height):
          lowerCamelCase_   					=						cva.resize(self.img	,						(width, height) )
        else:
          lowerCamelCase_   					=						self.img
      else:
        lowerCamelCase_   					=						io.BytesIO()  # works for cairo backend
        self.canvas.print_rgba(UpperCamelCase__ )
        lowerCamelCase_   					=						self.width, self.height
        lowerCamelCase_   					=						buf.getvalue()
        lowerCamelCase_   					=						self.img

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

      try:
        import numexpr as ne  # fuse them with numexpr

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

      return visualized_image.astype('uint8' )






    def        UpperCamelCase	(	self					:							Tuple	,						__SCREAMING_SNAKE_CASE					:							List[Any]	,						__SCREAMING_SNAKE_CASE					:							Dict )					->		Optional[int]:
      assert brightness_factor >= -1.0 and brightness_factor <= 1.0
      lowerCamelCase_   					=						mplc.to_rgb(UpperCamelCase__ )
      lowerCamelCase_   					=						colorsys.rgb_to_hls(*mplc.to_rgb(UpperCamelCase__ ) )
      lowerCamelCase_   					=						polygon_color[1] + (brightness_factor * polygon_color[1])
      lowerCamelCase_   					=						0.0 if modified_lightness < 0.0 else modified_lightness
      lowerCamelCase_   					=						1.0 if modified_lightness > 1.0 else modified_lightness
      lowerCamelCase_   					=						colorsys.hls_to_rgb(polygon_color[0]	,						UpperCamelCase__	,						polygon_color[2] )
      return modified_color
_SCREAMING_SNAKE_CASE :    List[str]    =						(
    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)
)












"""simple docstring"""





import numpy as np







def 					lowerCamelCase__	(							_lowerCamelCase	:		Dict		,    _lowerCamelCase	:		Any		,    _lowerCamelCase	:		Tuple			)				->    str:
  lowerCamelCase_   					=						n_draws * class_counts / class_counts.sum()
  # floored means we don't overshoot n_samples, but probably undershoot
  lowerCamelCase_   					=						np.floor(_lowerCamelCase			)
  # we add samples according to how much "left over" probability
  # they had, until we arrive at n_samples
  lowerCamelCase_   					=						int(n_draws - floored.sum()			)
  if need_to_add > 0:
    lowerCamelCase_   					=						continuous - floored
    lowerCamelCase_   					=						np.sort(np.unique(_lowerCamelCase			)			)[::-1]
    # add according to remainder, but break ties
    # randomly to avoid biases
    for value in values:
      ((lowerCamelCase_)					,     )   					=						np.where(remainder == value			)
      # if we need_to_add less than what's in inds
      # we draw randomly from them.
      # if we need to add more, we add them all and
      # go to the next value
      lowerCamelCase_   					=						min(len(_lowerCamelCase			)		,    _lowerCamelCase			)
      lowerCamelCase_   					=						rng.choice(_lowerCamelCase		,    size=_lowerCamelCase		,    replace=_lowerCamelCase			)
      floored[inds] += 1
      need_to_add -= add_now
      if need_to_add == 0:
        break
  return floored.astype(np.intaa			)







def 					lowerCamelCase__	(							_lowerCamelCase	:		Any		,    _lowerCamelCase	:		int		,    _lowerCamelCase	:		Optional[Any]		,    _lowerCamelCase	:		List[str]		,    _lowerCamelCase	:		Optional[int]=10			)				->    Any:
  lowerCamelCase_					,     lowerCamelCase_   					=						np.unique(_lowerCamelCase		,    return_inverse=_lowerCamelCase			)
  lowerCamelCase_   					=						classes.shape[0]
  lowerCamelCase_   					=						np.bincount(_lowerCamelCase			)
  if np.min(_lowerCamelCase			) < 2:
    raise ValueError('Minimum class count error'			)
  if n_train < n_classes:
    raise ValueError(
        'The train_size = %d should be greater or ' 'equal to the number of classes = %d' % (n_train, n_classes)			)
  if n_test < n_classes:
    raise ValueError(
        'The test_size = %d should be greater or ' 'equal to the number of classes = %d' % (n_test, n_classes)			)
  lowerCamelCase_   					=						np.split(np.argsort(_lowerCamelCase		,    kind='mergesort'			)		,    np.cumsum(_lowerCamelCase			)[:-1]			)
  for _ in range(_lowerCamelCase			):
    lowerCamelCase_   					=						approximate_mode(_lowerCamelCase		,    _lowerCamelCase		,    _lowerCamelCase			)
    lowerCamelCase_   					=						class_counts - n_i
    lowerCamelCase_   					=						approximate_mode(_lowerCamelCase		,    _lowerCamelCase		,    _lowerCamelCase			)

    lowerCamelCase_   					=						[]
    lowerCamelCase_   					=						[]

    for i in range(_lowerCamelCase			):
      lowerCamelCase_   					=						rng.permutation(class_counts[i]			)
      lowerCamelCase_   					=						class_indices[i].take(_lowerCamelCase		,    mode='clip'			)
      train.extend(perm_indices_class_i[: n_i[i]]			)
      test.extend(perm_indices_class_i[n_i[i] : n_i[i] + t_i[i]]			)
    lowerCamelCase_   					=						rng.permutation(_lowerCamelCase			)
    lowerCamelCase_   					=						rng.permutation(_lowerCamelCase			)

    yield train, test




