

"""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


_a					 =				10_00




class    _lowerCAmelCase    :







 """simple docstring"""







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

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

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


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

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


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

    __lowercase								=		(ya - ya) / np.sqrt(self.height * self.width      )
    __lowercase								=		self._change_color_brightness(UpperCAmelCase__,   brightness_factor=0.7      )
    __lowercase								=		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    _lowercase					(     self				:     List[Any],   UpperCAmelCase__				:     Any,   UpperCAmelCase__				:     Tuple,   UpperCAmelCase__				:     Optional[int]="g",   UpperCAmelCase__				:     str="left",   ):
    __lowercase								=		0
    __lowercase								=		self.font_size
    __lowercase								=		np.maximum(list(mplc.to_rgb(UpperCAmelCase__      )      ),   0.2      )
    __lowercase								=		max(0.8,   np.max(UpperCAmelCase__      )      )
    __lowercase								=		{
        "facecolor": "black",
        "alpha": self.alpha,
        "pad": self.pad,
        "edgecolor": "none",
    }
    __lowercase						,__lowercase								=		position
    self.ax.text(
        UpperCAmelCase__,   UpperCAmelCase__,   UpperCAmelCase__,   size=font_size * self.scale,   family="sans-serif",   bbox=UpperCAmelCase__,   verticalalignment="top",   horizontalalignment=UpperCAmelCase__,   color=UpperCAmelCase__,   zorder=1_0,   rotation=UpperCAmelCase__,   )


 def    _lowercase					(     self				:     List[Any],   UpperCAmelCase__				:     List[str]=None      ):
    if saveas is None:
       __lowercase								=		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    _lowercase					(     self				:     Union[str, Any],   UpperCAmelCase__				:     Optional[int],   UpperCAmelCase__				:     Union[str, Any],   UpperCAmelCase__				:     Tuple,   UpperCAmelCase__				:     Any      ):
    __lowercase								=		[self.idaobj[i] for i in classes]
    __lowercase								=		[self.idaattr[i] for i in attr_classes]
    __lowercase								=		[
        F"""{label} {score:.2f} {attr} {attr_score:.2f}"""
        for label, score, attr, attr_score in zip(UpperCAmelCase__,   UpperCAmelCase__,   UpperCAmelCase__,   UpperCAmelCase__      )
    ]
    return labels


 def    _lowercase					(     self				:     List[Any],   UpperCAmelCase__				:     Union[str, Any],   UpperCAmelCase__				:     Dict      ):
    __lowercase								=		[self.idaobj[i] for i in classes]
    if scores is not None:
       if labels is None:
          __lowercase								=		["{:.0f}%".format(s * 1_0_0      ) for s in scores]
       else:
          __lowercase								=		["{} {:.0f}%".format(UpperCAmelCase__,   s * 1_0_0      ) for li, s in zip(UpperCAmelCase__,   UpperCAmelCase__      )]
    return labels


 def    _lowercase					(     self				:     Optional[Any],   UpperCAmelCase__				:     Dict=2_5_5      ):
    __lowercase								=		np.random.randint(0,   len(_COLORS      )      )
    __lowercase								=		_COLORS[idx] * maximum
    if not self.rgb:
       __lowercase								=		ret[::-1]
    return ret


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

    __lowercase								=		np.frombuffer(UpperCAmelCase__,   dtype="uint8"      )
    __lowercase								=		buffer.reshape(UpperCAmelCase__,   UpperCAmelCase__,   4      )
    __lowercase						,__lowercase								=		np.split(UpperCAmelCase__,   [3],   axis=2      )

    try:
       import numexpr as ne  # fuse them with numexpr

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

    return visualized_image.astype("uint8"      )



 def    _lowercase					(     self				:     str,   UpperCAmelCase__				:     Tuple,   UpperCAmelCase__				:     List[Any]      ):
    assert brightness_factor >= -1.0 and brightness_factor <= 1.0
    __lowercase								=		mplc.to_rgb(UpperCAmelCase__      )
    __lowercase								=		colorsys.rgb_to_hls(*mplc.to_rgb(UpperCAmelCase__      )      )
    __lowercase								=		polygon_color[1] + (brightness_factor * polygon_color[1])
    __lowercase								=		0.0 if modified_lightness < 0.0 else modified_lightness
    __lowercase								=		1.0 if modified_lightness > 1.0 else modified_lightness
    __lowercase								=		colorsys.hls_to_rgb(polygon_color[0],   UpperCAmelCase__,   polygon_color[2]      )
    return modified_color







_a					 =				(
    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 cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey

from digital_image_processing.filters.convolve import img_convolve




def     _A    (    UpperCamelCase_	:			int)      ->		str:
   '''simple docstring'''


   __lowercase								=		np.array([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]])
   __lowercase								=		np.array([[1, 2, 1], [0, 0, 0], [-1, -2, -1]])

   __lowercase								=		np.abs(img_convolve(UpperCamelCase_,     UpperCamelCase_))
   __lowercase								=		np.abs(img_convolve(UpperCamelCase_,     UpperCamelCase_))
   # modify the pix within [0, 255]
   __lowercase								=		dst_x * 255 / np.max(UpperCamelCase_)
   __lowercase								=		dst_y * 255 / np.max(UpperCamelCase_)

   __lowercase								=		np.sqrt((np.square(UpperCamelCase_)) + (np.square(UpperCamelCase_)))
   __lowercase								=		dst_xy * 255 / np.max(UpperCamelCase_)
   __lowercase								=		dst_xy.astype(np.uinta)

   __lowercase								=		np.arctana(UpperCamelCase_,     UpperCamelCase_)
   return dst, theta


if __name__ == "__main__":
   # read original image
   _a					 =				imread('../image_data/lena.jpg')
   # turn image in gray scale value
   _a					 =				cvtColor(img, COLOR_BGR2GRAY)

   _a ,		_a					 =				sobel_filter(gray)

   # show result images
   imshow('sobel filter', sobel_grad)
   imshow('sobel theta', sobel_theta)
   waitKey(0)




