





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_     =1_000




class 				_a		:






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




										'''simple docstring'''



										if isinstance(lowerCAmelCase__,				torch.Tensor							):
																_UpperCamelCase    :      Any						     =					img.numpy().astype('''np.uint8'''							)
										if isinstance(lowerCAmelCase__,				lowerCAmelCase__							):
																_UpperCamelCase    :      List[str]						     =					img_tensorize(lowerCAmelCase__							)
										assert isinstance(lowerCAmelCase__,				np.ndarray							)

										_UpperCamelCase    :      Optional[int]						     =					img.shape[1], img.shape[0]
										_UpperCamelCase    :      Optional[int]						     =					mplfigure.Figure(frameon=lowerCAmelCase__							)
										_UpperCamelCase    :      Union[str, Any]						     =					fig.get_dpi()
										_UpperCamelCase    :      Any						     =					(width * scale + 1e-2) / dpi
										_UpperCamelCase    :      List[str]						     =					(height * scale + 1e-2) / dpi
										fig.set_size_inches(lowerCAmelCase__,				lowerCAmelCase__							)
										_UpperCamelCase    :      Any						     =					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    :      int						     =					saveas
										_UpperCamelCase    :      Dict						     =					rgb
										_UpperCamelCase    :      str						     =					pynb
										_UpperCamelCase    :      Optional[int]						     =					img
										_UpperCamelCase    :      Any						     =					edgecolor
										_UpperCamelCase    :      str						     =					0.5
										_UpperCamelCase    :      List[str]						     =					linestyle
										_UpperCamelCase    :      Union[str, Any]						     =					int(np.sqrt(min(lowerCAmelCase__,				lowerCAmelCase__							)							) * scale // 3							)
										_UpperCamelCase    :      Optional[Any]						     =					width
										_UpperCamelCase    :      Dict						     =					height
										_UpperCamelCase    :      Dict						     =					scale
										_UpperCamelCase    :      Union[str, Any]						     =					fig
										_UpperCamelCase    :      str						     =					ax
										_UpperCamelCase    :      List[str]						     =					pad
										_UpperCamelCase    :      Tuple						     =					idaobj
										_UpperCamelCase    :      Optional[int]						     =					idaattr
										_UpperCamelCase    :      int						     =					FigureCanvasAgg(lowerCAmelCase__							)






				def        snake_case			(				self	:					List[Any],				lowerCAmelCase__	:					Optional[Any],				lowerCAmelCase__	:					Union[str, Any]=None							)			->   List[str]:




										'''simple docstring'''



										if color is None:
																_UpperCamelCase    :      str						     =					self.edgecolor
										(_UpperCamelCase)    :      Optional[Any]						     =					box
										_UpperCamelCase    :      Union[str, Any]						     =					xa - xa
										_UpperCamelCase    :      int						     =					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        snake_case			(				self	:					Optional[int],				lowerCAmelCase__	:					Tuple,				lowerCAmelCase__	:					Optional[Any]=None,				lowerCAmelCase__	:					str=None,				lowerCAmelCase__	:					Tuple=None,				lowerCAmelCase__	:					str=None							)			->   Dict:




										'''simple docstring'''



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

										_UpperCamelCase    :      List[Any]						     =					[self._random_color(maximum=1							) for _ in range(len(lowerCAmelCase__							)							)]
										_UpperCamelCase    :      Tuple						     =					[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    :      List[Any]						     =					assigned_colors[i]
																						self.add_box(boxes[i],				lowerCAmelCase__							)
																						self.draw_labels(labels[i],				boxes[i],				lowerCAmelCase__							)






				def        snake_case			(				self	:					Dict,				lowerCAmelCase__	:					List[str],				lowerCAmelCase__	:					int,				lowerCAmelCase__	:					str							)			->   str:




										'''simple docstring'''



										_UpperCamelCase    :      Dict						     =					box
										_UpperCamelCase    :      List[str]						     =					(xa, ya)
										_UpperCamelCase    :      List[str]						     =					(ya - ya) * (xa - xa)
										_UpperCamelCase    :      int						     =					_SMALL_OBJ * self.scale
										if instance_area < small or ya - ya < 4_0 * self.scale:
																if ya >= self.height - 5:
																						_UpperCamelCase    :      Union[str, Any]						     =					(xa, ya)
																else:
																						_UpperCamelCase    :      int						     =					(xa, ya)

										_UpperCamelCase    :      int						     =					(ya - ya) / np.sqrt(self.height * self.width							)
										_UpperCamelCase    :      Dict						     =					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        snake_case			(				self	:					str,				lowerCAmelCase__	:					List[str],				lowerCAmelCase__	:					Optional[int],				lowerCAmelCase__	:					List[Any]="g",				lowerCAmelCase__	:					Union[str, Any]="left",				)			->   Optional[int]:




										'''simple docstring'''



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




										'''simple docstring'''



										if saveas is None:
																_UpperCamelCase    :      Tuple						     =					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        snake_case			(				self	:					Optional[int],				lowerCAmelCase__	:					int,				lowerCAmelCase__	:					List[str],				lowerCAmelCase__	:					Tuple,				lowerCAmelCase__	:					Optional[Any]							)			->   List[Any]:




										'''simple docstring'''



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






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




										'''simple docstring'''



										_UpperCamelCase    :      Tuple						     =					[self.idaobj[i] for i in classes]
										if scores is not None:
																if labels is None:
																						_UpperCamelCase    :      Optional[Any]						     =					['''{:.0f}%'''.format(s * 1_0_0							) for s in scores]
																else:
																						_UpperCamelCase    :      Tuple						     =					['''{} {:.0f}%'''.format(lowerCAmelCase__,				s * 1_0_0							) for li, s in zip(lowerCAmelCase__,				lowerCAmelCase__							)]
										return labels






				def        snake_case			(				self	:					Tuple,				lowerCAmelCase__	:					Dict=2_5_5							)			->   Dict:




										'''simple docstring'''



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






				def        snake_case			(				self	:					str							)			->   List[str]:




										'''simple docstring'''



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

										_UpperCamelCase    :      int						     =					np.frombuffer(lowerCAmelCase__,				dtype='''uint8'''							)
										_UpperCamelCase    :      List[str]						     =					buffer.reshape(lowerCAmelCase__,				lowerCAmelCase__,				4							)
										_UpperCamelCase    :      Tuple						     =					np.split(lowerCAmelCase__,				[3],				axis=2							)

										try:
																import numexpr as ne  # fuse them with numexpr

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

										return visualized_image.astype('''uint8'''							)






				def        snake_case			(				self	:					List[Any],				lowerCAmelCase__	:					Optional[Any],				lowerCAmelCase__	:					List[str]							)			->   Dict:




										'''simple docstring'''



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










"""simple docstring"""




UpperCamelCase_     =1_000





def  a_       (							_lowercase     ):
						return x * x





def  a_       (							_lowercase ,		_lowercase ,		_lowercase ,		_lowercase = 4     ):
						assert callable(
						    _lowercase     ), F"""the function(object) passed should be callable your input : {function}"""
						assert isinstance(_lowercase ,		(float, int)     ), F"""a should be float or integer your input : {a}"""
						assert isinstance(function(_lowercase     ) ,		(float, int)     ), (
						    "the function should return integer or float return type of your function, "
						    F"""{type(_lowercase     )}"""
						)
						assert isinstance(_lowercase ,		(float, int)     ), F"""b should be float or integer your input : {b}"""
						assert (
						    isinstance(_lowercase ,		_lowercase     ) and precision > 0
						), F"""precision should be positive integer your input : {precision}"""

						# just applying the formula of simpson for approximate integration written in
						# mentioned article in first comment of this file and above this function

						_UpperCamelCase    :      str						     =					(b - a) / N_STEPS
						_UpperCamelCase    :      Dict						     =					function(_lowercase     ) + function(_lowercase     )

						for i in range(1 ,		_lowercase     ):
												_UpperCamelCase    :      List[Any]						     =					a + h * i
												result += function(_lowercase     ) * (4 if i % 2 else 2)

						result *= h / 3
						return round(_lowercase ,		_lowercase     )


if __name__ == "__main__":
						import doctest

						doctest.testmod()



