




'''simple docstring'''


class     SCREAMING_SNAKE_CASE						:






      def __init__(   self      :     str					):


           '''simple docstring'''

           a_    :       Optional[int]    	=     []
           a_    :       Any    	=     0
           a_    :       Any    	=     0






      def __str__(   self      :     Union[str, Any]					):


           '''simple docstring'''

           a_    :       str    	=     """<""" + str(self.entries					)[1:-1] + """>"""
           return printed






      def        lowercase_	(   self      :     List[str]	,	lowercase__      :     List[Any]					):


           '''simple docstring'''

           self.entries.append(lowercase__					)
           a_    :       List[str]    	=     self.length + 1






      def        lowercase_	(   self      :     List[str]					):


           '''simple docstring'''

           a_    :       Union[str, Any]    	=     self.length - 1
           a_    :       Optional[int]    	=     self.entries[self.front]
           # self.front-=1
           # self.entries = self.entries[self.front:]
           a_    :       str    	=     self.entries[1:]
           return dequeued






      def        lowercase_	(   self      :     int	,	lowercase__      :     Tuple					):


           '''simple docstring'''

           for _ in range(lowercase__					):
                self.put(self.get()					)






      def        lowercase_	(   self      :     Optional[Any]					):


           '''simple docstring'''

           return self.entries[0]






      def        lowercase_	(   self      :     Tuple					):


           '''simple docstring'''

           return self.length






'''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


lowerCAmelCase_			:     Tuple							    =     1000







class     SCREAMING_SNAKE_CASE						:






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


           '''simple docstring'''

           if isinstance(lowercase__	,	torch.Tensor					):
                a_    :       Union[str, Any]    	=     img.numpy().astype("""np.uint8"""					)
           if isinstance(lowercase__	,	lowercase__					):
                a_    :       List[Any]    	=     img_tensorize(lowercase__					)
           assert isinstance(lowercase__	,	np.ndarray					)

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

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






      def        lowercase_	(   self      :     Optional[Any]	,	lowercase__      :     Optional[Any]	,	lowercase__      :     str=None					):


           '''simple docstring'''

           if color is None:
                a_    :       int    	=     self.edgecolor
           ((a_)	,    (a_)	,    (a_)	,    (a_))    :       Union[str, Any]    	=     box
           a_    :       Union[str, Any]    	=     xa - xa
           a_    :       List[Any]    	=     ya - ya
           self.ax.add_patch(
               mpl.patches.Rectangle(
                   (xa, ya)	,	lowercase__	,	lowercase__	,	fill=lowercase__	,	edgecolor=lowercase__	,	linewidth=self.font_size // 3	,	alpha=self.alpha	,	linestyle=self.linestyle	,	)					)






      def        lowercase_	(   self      :     int	,	lowercase__      :     List[Any]	,	lowercase__      :     List[str]=None	,	lowercase__      :     Optional[Any]=None	,	lowercase__      :     List[Any]=None	,	lowercase__      :     Union[str, Any]=None					):


           '''simple docstring'''

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

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






      def        lowercase_	(   self      :     Optional[Any]	,	lowercase__      :     Any	,	lowercase__      :     Optional[Any]	,	lowercase__      :     Optional[Any]					):


           '''simple docstring'''

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

           a_    :       List[Any]    	=     (ya - ya) / np.sqrt(self.height * self.width					)
           a_    :       Optional[int]    	=     self._change_color_brightness(lowercase__	,	brightness_factor=0.7					)
           a_    :       List[str]    	=     np.clip((height_ratio - 0.02) / 0.08 + 1	,	1.2	,	2					)
           font_size *= 0.75 * self.font_size

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






      def        lowercase_	(   self      :     Any	,	lowercase__      :     Optional[int]	,	lowercase__      :     Tuple	,	lowercase__      :     str="g"	,	lowercase__      :     Optional[Any]="left"	,	):


           '''simple docstring'''

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






      def        lowercase_	(   self      :     List[Any]	,	lowercase__      :     Optional[Any]=None					):


           '''simple docstring'''

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






      def        lowercase_	(   self      :     List[Any]	,	lowercase__      :     int	,	lowercase__      :     Tuple	,	lowercase__      :     Optional[int]	,	lowercase__      :     Tuple					):


           '''simple docstring'''

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






      def        lowercase_	(   self      :     str	,	lowercase__      :     Optional[Any]	,	lowercase__      :     Optional[Any]					):


           '''simple docstring'''

           a_    :       Optional[int]    	=     [self.idaobj[i] for i in classes]
           if scores is not None:
                if labels is None:
                     a_    :       int    	=     ["""{:.0f}%""".format(s * 100					) for s in scores]
                else:
                     a_    :       Optional[int]    	=     ["""{} {:.0f}%""".format(lowercase__	,	s * 100					) for li, s in zip(lowercase__	,	lowercase__					)]
           return labels






      def        lowercase_	(   self      :     Dict	,	lowercase__      :     Union[str, Any]=255					):


           '''simple docstring'''

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






      def        lowercase_	(   self      :     Optional[Any]					):


           '''simple docstring'''

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

           a_    :       Optional[Any]    	=     np.frombuffer(lowercase__	,	dtype="""uint8"""					)
           a_    :       Union[str, Any]    	=     buffer.reshape(lowercase__	,	lowercase__	,	4					)
           a_	,    a_    :       Optional[Any]    	=     np.split(lowercase__	,	[3]	,	axis=2					)

           try:
                import numexpr as ne  # fuse them with numexpr

                a_    :       Dict    	=     ne.evaluate("""img * (1 - alpha / 255.0) + rgb * (alpha / 255.0)"""					)
           except ImportError:
                a_    :       List[Any]    	=     alpha.astype("""float32"""					) / 255.0
                a_    :       Optional[int]    	=     img * (1 - alpha) + rgb * alpha

           return visualized_image.astype("""uint8"""					)






      def        lowercase_	(   self      :     Optional[Any]	,	lowercase__      :     Union[str, Any]	,	lowercase__      :     Any					):


           '''simple docstring'''

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

lowerCAmelCase_			:     List[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)
)
