






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__            =	1000






class 	lowercase_      :






      '''simple docstring'''




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




       """simple docstring"""


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

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

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







      def    __lowerCAmelCase      (   self   :		str				,      __UpperCAmelCase   :		str				,      __UpperCAmelCase   :		Any=None						)					->int:




       """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)				,      __UpperCAmelCase				,      __UpperCAmelCase				,      fill=__UpperCAmelCase				,      edgecolor=__UpperCAmelCase				,      linewidth=self.font_size // 3				,      alpha=self.alpha				,      linestyle=self.linestyle				,      )						)







      def    __lowerCAmelCase      (   self   :		List[Any]				,      __UpperCAmelCase   :		int				,      __UpperCAmelCase   :		str=None				,      __UpperCAmelCase   :		Tuple=None				,      __UpperCAmelCase   :		Tuple=None				,      __UpperCAmelCase   :		Optional[Any]=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(__UpperCAmelCase				,      torch.Tensor						):
        a							=   boxes.numpy()
       if isinstance(__UpperCAmelCase				,      __UpperCAmelCase						):
        a							=   np.array(__UpperCAmelCase						)
       assert isinstance(__UpperCAmelCase				,      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(__UpperCAmelCase						)						)]
       a							=   [assigned_colors[idx] for idx in sorted_idxs]
       if obj_ids is not None:
        a							=   self._create_text_labels_attr(__UpperCAmelCase				,      __UpperCAmelCase				,      __UpperCAmelCase				,      __UpperCAmelCase						)
        for i in range(len(__UpperCAmelCase						)						):
         a							=   assigned_colors[i]
         self.add_box(boxes[i]				,      __UpperCAmelCase						)
         self.draw_labels(labels[i]				,      boxes[i]				,      __UpperCAmelCase						)







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




       """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(__UpperCAmelCase				,      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=__UpperCAmelCase				,      position=__UpperCAmelCase				,      color=__UpperCAmelCase				,      )







      def    __lowerCAmelCase      (   self   :		Any				,      __UpperCAmelCase   :		Optional[Any]				,      __UpperCAmelCase   :		Dict				,      __UpperCAmelCase   :		str="g"				,      __UpperCAmelCase   :		List[Any]="left"				,      )					->str:




       """simple docstring"""


       a							=   0
       a							=   self.font_size
       a							=   np.maximum(list(mplc.to_rgb(__UpperCAmelCase						)						)				,      0.2						)
       a							=   max(0.8				,      np.max(__UpperCAmelCase						)						)
       a							=   {
           '''facecolor''': '''black''',
           '''alpha''': self.alpha,
           '''pad''': self.pad,
           '''edgecolor''': '''none''',
       }
       a						,  a							=   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    __lowerCAmelCase      (   self   :		Any				,      __UpperCAmelCase   :		Tuple=None						)					->Tuple:




       """simple docstring"""


       if saveas is None:
        a							=   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    __lowerCAmelCase      (   self   :		Dict				,      __UpperCAmelCase   :		Optional[Any]				,      __UpperCAmelCase   :		List[Any]				,      __UpperCAmelCase   :		int				,      __UpperCAmelCase   :		Any						)					->Optional[int]:




       """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(__UpperCAmelCase				,      __UpperCAmelCase				,      __UpperCAmelCase				,      __UpperCAmelCase						)
       ]
       return labels







      def    __lowerCAmelCase      (   self   :		Union[str, Any]				,      __UpperCAmelCase   :		List[Any]				,      __UpperCAmelCase   :		Tuple						)					->Dict:




       """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(__UpperCAmelCase				,      s * 100						) for li, s in zip(__UpperCAmelCase				,      __UpperCAmelCase						)]
       return labels







      def    __lowerCAmelCase      (   self   :		List[Any]				,      __UpperCAmelCase   :		List[Any]=255						)					->Tuple:




       """simple docstring"""


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







      def    __lowerCAmelCase      (   self   :		List[str]						)					->Union[str, Any]:




       """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(__UpperCAmelCase						)
        a						,  a							=   self.width, self.height
        a							=   buf.getvalue()
        a							=   self.img

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




       """simple docstring"""


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

UpperCAmelCase__            =	namedtuple("from_to", "from_ to")

UpperCAmelCase__            =	{
    "atm": from_to(1, 1),
    "pascal": from_to(0.000_0098, 101325),
    "bar": from_to(0.98_6923, 1.0_1325),
    "kilopascal": from_to(0.0098_6923, 101.325),
    "megapascal": from_to(9.8_6923, 0.10_1325),
    "psi": from_to(0.06_8046, 14.6959),
    "inHg": from_to(0.033_4211, 29.9213),
    "torr": from_to(0.0013_1579, 760),
}
def 		_a					(   a				:float			,							a				:str			,							a				:str				)							->    float:
 if from_type not in PRESSURE_CONVERSION:
  raise ValueError(
      F"""Invalid 'from_type' value: {from_type!r}  Supported values are:\n"""
      + ''', '''.join(a				)				)
 if to_type not in PRESSURE_CONVERSION:
  raise ValueError(
      F"""Invalid 'to_type' value: {to_type!r}.  Supported values are:\n"""
      + ''', '''.join(a				)				)
 return (
     value * PRESSURE_CONVERSION[from_type].from_ * PRESSURE_CONVERSION[to_type].to
 )


if __name__ == "__main__":
     import doctest

     doctest.testmod()


