




"""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						 =     1_0_0_0







class  _SCREAMING_SNAKE_CASE       :



 '''simple docstring'''





 def __init__(self					,     lowerCAmelCase__					,     lowerCAmelCase__=1.2					,     lowerCAmelCase__="g"					,     lowerCAmelCase__=0.5					,     lowerCAmelCase__="-"					,     lowerCAmelCase__="test_out.jpg"					,     lowerCAmelCase__=True					,     lowerCAmelCase__=False					,     lowerCAmelCase__=None					,     lowerCAmelCase__=None					,     lowerCAmelCase__=0.7					,     ):

  '''simple docstring'''







  if isinstance(lowerCAmelCase__					,     torch.Tensor   ):
   _UpperCamelCase      :	int					      =  img.numpy().astype("np.uint8"   )
  if isinstance(lowerCAmelCase__					,     lowerCAmelCase__   ):
   _UpperCamelCase      :	Tuple					      =  img_tensorize(lowerCAmelCase__   )
  assert isinstance(lowerCAmelCase__					,     np.ndarray   )

  _UpperCamelCase      ,	_UpperCamelCase      :	Optional[Any]					      =  img.shape[1], img.shape[0]
  _UpperCamelCase      :	List[str]					      =  mplfigure.Figure(frameon=lowerCAmelCase__   )
  _UpperCamelCase      :	List[str]					      =  fig.get_dpi()
  _UpperCamelCase      :	Tuple					      =  (width * scale + 1E-2) / dpi
  _UpperCamelCase      :	Union[str, Any]					      =  (height * scale + 1E-2) / dpi
  fig.set_size_inches(lowerCAmelCase__					,     lowerCAmelCase__   )
  _UpperCamelCase      :	Optional[int]					      =  fig.add_axes([0.0, 0.0, 1.0, 1.0]   )
  ax.axis("off"   )
  ax.set_xlim(0.0					,     lowerCAmelCase__   )
  ax.set_ylim(lowerCAmelCase__   )

  _UpperCamelCase      :	Optional[Any]					      =  saveas
  _UpperCamelCase      :	Optional[int]					      =  rgb
  _UpperCamelCase      :	Any					      =  pynb
  _UpperCamelCase      :	Any					      =  img
  _UpperCamelCase      :	Optional[int]					      =  edgecolor
  _UpperCamelCase      :	Dict					      =  0.5
  _UpperCamelCase      :	Any					      =  linestyle
  _UpperCamelCase      :	Optional[Any]					      =  int(np.sqrt(min(lowerCAmelCase__					,     lowerCAmelCase__   )   ) * scale // 3   )
  _UpperCamelCase      :	Any					      =  width
  _UpperCamelCase      :	Optional[Any]					      =  height
  _UpperCamelCase      :	List[str]					      =  scale
  _UpperCamelCase      :	Tuple					      =  fig
  _UpperCamelCase      :	Dict					      =  ax
  _UpperCamelCase      :	Tuple					      =  pad
  _UpperCamelCase      :	Optional[int]					      =  idaobj
  _UpperCamelCase      :	Dict					      =  idaattr
  _UpperCamelCase      :	Any					      =  FigureCanvasAgg(lowerCAmelCase__   )






 def lowercase_      (self					,     lowerCAmelCase__					,     lowerCAmelCase__=None   ):

  '''simple docstring'''







  if color is None:
   _UpperCamelCase      :	Union[str, Any]					      =  self.edgecolor
  ((_UpperCamelCase)      ,	(_UpperCamelCase)      ,	(_UpperCamelCase)      ,	(_UpperCamelCase))      :	int					      =  box
  _UpperCamelCase      :	List[Any]					      =  xa - xa
  _UpperCamelCase      :	List[Any]					      =  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 lowercase_      (self					,     lowerCAmelCase__					,     lowerCAmelCase__=None					,     lowerCAmelCase__=None					,     lowerCAmelCase__=None					,     lowerCAmelCase__=None   ):

  '''simple docstring'''







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

  _UpperCamelCase      :	int					      =  [self._random_color(maximum=1   ) for _ in range(len(lowerCAmelCase__   )   )]
  _UpperCamelCase      :	Optional[Any]					      =  [assigned_colors[idx] for idx in sorted_idxs]
  if obj_ids is not None:
   _UpperCamelCase      :	Tuple					      =  self._create_text_labels_attr(lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__   )
   for i in range(len(lowerCAmelCase__   )   ):
    _UpperCamelCase      :	Dict					      =  assigned_colors[i]
    self.add_box(boxes[i]					,     lowerCAmelCase__   )
    self.draw_labels(labels[i]					,     boxes[i]					,     lowerCAmelCase__   )






 def lowercase_      (self					,     lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__   ):

  '''simple docstring'''







  _UpperCamelCase      ,	_UpperCamelCase      ,	_UpperCamelCase      ,	_UpperCamelCase      :	str					      =  box
  _UpperCamelCase      :	List[str]					      =  (xa, ya)
  _UpperCamelCase      :	int					      =  (ya - ya) * (xa - xa)
  _UpperCamelCase      :	str					      =  _SMALL_OBJ * self.scale
  if instance_area < small or ya - ya < 40 * self.scale:
   if ya >= self.height - 5:
    _UpperCamelCase      :	Dict					      =  (xa, ya)
   else:
    _UpperCamelCase      :	List[Any]					      =  (xa, ya)

  _UpperCamelCase      :	Union[str, Any]					      =  (ya - ya) / np.sqrt(self.height * self.width   )
  _UpperCamelCase      :	Optional[int]					      =  self._change_color_brightness(lowerCAmelCase__					,     brightness_factor=0.7   )
  _UpperCamelCase      :	int					      =  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 lowercase_      (self					,     lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__="g"					,     lowerCAmelCase__="left"					,     ):

  '''simple docstring'''







  _UpperCamelCase      :	Any					      =  0
  _UpperCamelCase      :	Optional[Any]					      =  self.font_size
  _UpperCamelCase      :	Optional[Any]					      =  np.maximum(list(mplc.to_rgb(lowerCAmelCase__   )   )					,     0.2   )
  _UpperCamelCase      :	Union[str, Any]					      =  max(0.8					,     np.max(lowerCAmelCase__   )   )
  _UpperCamelCase      :	List[Any]					      =  {
      "facecolor": "black",
      "alpha": self.alpha,
      "pad": self.pad,
      "edgecolor": "none",
  }
  _UpperCamelCase      ,	_UpperCamelCase      :	str					      =  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 lowercase_      (self					,     lowerCAmelCase__=None   ):

  '''simple docstring'''







  if saveas is None:
   _UpperCamelCase      :	int					      =  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 lowercase_      (self					,     lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__   ):

  '''simple docstring'''







  _UpperCamelCase      :	Union[str, Any]					      =  [self.idaobj[i] for i in classes]
  _UpperCamelCase      :	List[str]					      =  [self.idaattr[i] for i in attr_classes]
  _UpperCamelCase      :	Any					      =  [
      F"{label} {score:.2f} {attr} {attr_score:.2f}"
      for label, score, attr, attr_score in zip(lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__   )
  ]
  return labels






 def lowercase_      (self					,     lowerCAmelCase__					,     lowerCAmelCase__   ):

  '''simple docstring'''







  _UpperCamelCase      :	str					      =  [self.idaobj[i] for i in classes]
  if scores is not None:
   if labels is None:
    _UpperCamelCase      :	str					      =  ["{:.0f}%".format(s * 1_00   ) for s in scores]
   else:
    _UpperCamelCase      :	Union[str, Any]					      =  ["{} {:.0f}%".format(lowerCAmelCase__					,     s * 1_00   ) for li, s in zip(lowerCAmelCase__					,     lowerCAmelCase__   )]
  return labels






 def lowercase_      (self					,     lowerCAmelCase__=2_55   ):

  '''simple docstring'''







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






 def lowercase_      (self   ):

  '''simple docstring'''







  if not self.pynb:
   _UpperCamelCase      ,	_UpperCamelCase      :	int					      =  self.canvas.print_to_buffer()
   if (width, height) != (self.width, self.height):
    _UpperCamelCase      :	List[str]					      =  cva.resize(self.img					,     (width, height)   )
   else:
    _UpperCamelCase      :	Any					      =  self.img
  else:
   _UpperCamelCase      :	str					      =  io.BytesIO()  # works for cairo backend
   self.canvas.print_rgba(lowerCAmelCase__   )
   _UpperCamelCase      ,	_UpperCamelCase      :	str					      =  self.width, self.height
   _UpperCamelCase      :	List[Any]					      =  buf.getvalue()
   _UpperCamelCase      :	str					      =  self.img

  _UpperCamelCase      :	int					      =  np.frombuffer(lowerCAmelCase__					,     dtype="uint8"   )
  _UpperCamelCase      :	Any					      =  buffer.reshape(lowerCAmelCase__					,     lowerCAmelCase__					,     4   )
  _UpperCamelCase      ,	_UpperCamelCase      :	Optional[Any]					      =  np.split(lowerCAmelCase__					,     [3]					,     axis=2   )

  try:
   import numexpr as ne  # fuse them with numexpr

   _UpperCamelCase      :	Union[str, Any]					      =  ne.evaluate("img * (1 - alpha / 255.0) + rgb * (alpha / 255.0)"   )
  except ImportError:
   _UpperCamelCase      :	Union[str, Any]					      =  alpha.astype("float32"   ) / 255.0
   _UpperCamelCase      :	List[str]					      =  img * (1 - alpha) + rgb * alpha

  return visualized_image.astype("uint8"   )






 def lowercase_      (self					,     lowerCAmelCase__					,     lowerCAmelCase__   ):

  '''simple docstring'''







  assert brightness_factor >= -1.0 and brightness_factor <= 1.0
  _UpperCamelCase      :	Tuple					      =  mplc.to_rgb(lowerCAmelCase__   )
  _UpperCamelCase      :	Union[str, Any]					      =  colorsys.rgb_to_hls(*mplc.to_rgb(lowerCAmelCase__   )   )
  _UpperCamelCase      :	Optional[int]					      =  polygon_color[1] + (brightness_factor * polygon_color[1])
  _UpperCamelCase      :	int					      =  0.0 if modified_lightness < 0.0 else modified_lightness
  _UpperCamelCase      :	Union[str, Any]					      =  1.0 if modified_lightness > 1.0 else modified_lightness
  _UpperCamelCase      :	Union[str, Any]					      =  colorsys.hls_to_rgb(polygon_color[0]					,     lowerCAmelCase__					,     polygon_color[2]   )
  return modified_color

_SCREAMING_SNAKE_CASE						 =     (
    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
from numpy import floataa
from numpy.typing import NDArray






def 				__lowerCAmelCase					(					__lowerCAmelCase			:		NDArray[floataa]  ,	__lowerCAmelCase			:		NDArray[floataa]						)    ->       NDArray[floataa]:
 _UpperCamelCase      ,	_UpperCamelCase      :	Optional[Any]					      =  np.shape(__lowerCAmelCase						)

 _UpperCamelCase      :	NDArray[floataa]					      =  np.zeros((rows, 1)  ,	dtype=__lowerCAmelCase						)
 for row in reversed(range(__lowerCAmelCase						)						):
  _UpperCamelCase      :	List[str]					      =  0
  for col in range(row + 1  ,	__lowerCAmelCase						):
   total += coefficients[row, col] * x[col]

  _UpperCamelCase      :	Dict					      =  (vector[row] - total) / coefficients[row, row]

 return x






def 				__lowerCAmelCase					(					__lowerCAmelCase			:		NDArray[floataa]  ,	__lowerCAmelCase			:		NDArray[floataa]						)    ->       NDArray[floataa]:
 _UpperCamelCase      ,	_UpperCamelCase      :	Optional[Any]					      =  np.shape(__lowerCAmelCase						)
 if rows != columns:
  return np.array(()  ,	dtype=__lowerCAmelCase						)

 # augmented matrix
 _UpperCamelCase      :	NDArray[floataa]					      =  np.concatenate((coefficients, vector)  ,	axis=1						)
 _UpperCamelCase      :	List[str]					      =  augmented_mat.astype("float64"						)

 # scale the matrix leaving it triangular
 for row in range(rows - 1						):
  _UpperCamelCase      :	Optional[Any]					      =  augmented_mat[row, row]
  for col in range(row + 1  ,	__lowerCAmelCase						):
   _UpperCamelCase      :	Union[str, Any]					      =  augmented_mat[col, row] / pivot
   augmented_mat[col, :] -= factor * augmented_mat[row, :]

 _UpperCamelCase      :	Any					      =  retroactive_resolution(
     augmented_mat[:, 0:columns]  ,	augmented_mat[:, columns : columns + 1]						)

 return x


if __name__ == "__main__":
    import doctest

    doctest.testmod()



