a d/@sddlmZmZmZmZddlZddlmZddlmZm Z eje e ejddddZ ejejejejejdd d Z dejejeejee ejd d d Zee e eeefdddZeeedddZeeeeefeedddZdS))ListOptionalTupleUnionN)Tensor) KORNIA_CHECKKORNIA_CHECK_SHAPE)imagexycolorreturncCs||dd||f<dS)alDraws a pixel into an image. Args: image: the input image to where to draw the lines with shape :math`(C,H,W)`. x: the x coordinate of the pixel. y: the y coordinate of the pixel. color: the color of the pixel with :math`(C)` where :math`C` is the number of channels of the image. Return: Nothing is returned. N)r r r r rrZ/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/kornia/utils/draw.py _draw_pixel s r)r p1p2r r c srt|dkst|dkr tdt|dkr8td|d|dkrTtd|d|dks|d|dks|ddks|ddkrtd|d|dks|d|dks|ddks|ddkrtd ||jtj}||jtj}||}|\}}|\}}||||||||dkrZ   dkrn }t||t ||}}t||t ||}}fd d } dkr||d d ||d|f<ndkr ||d d |||df<ndd|kr"dkrnnnHt ||dD]4} t || ||| | d|d dkr4|d7}q4n|dkrt ||dD]4} t ||| || |d | ddkr|d7}qn|dkrt ||dD]4} t ||| || |d | ddkr|d8}qn`d|kr&dkrnnnDt ||dD]4} t || ||| | d|d dkr8|d8}q8|S)a[Draw a single line into an image. Args: image: the input image to where to draw the lines with shape :math`(C,H,W)`. p1: the start point [x y] of the line with shape (2). p2: the end point [x y] of the line with shape (2). color: the color of the line with shape :math`(C)` where :math`C` is the number of channels of the image. Return: the image with containing the line. Examples: >>> image = torch.zeros(1, 8, 8) >>> draw_line(image, torch.tensor([6, 4]), torch.tensor([1, 4]), torch.tensor([255])) tensor([[[ 0., 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0., 0.], [ 0., 255., 255., 255., 255., 255., 255., 0.], [ 0., 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0., 0.]]]) zp1 and p2 must have length 2.z%image must have 3 dimensions (C,H,W).rz9color must have the same number of channels as the image.zp1 is out of bounds.zp2 is out of bounds.cs||S)Nr)r r ABCrr line_equationbsz draw_line..line_equationNg?) len ValueErrorsizetodevicetorchint64minlongmaxranger) r rrr x1y1Zx2y2mrijrrr draw_linesh<<         r-)r rectangler fillr c Cs,|j\}}}}|j\}} } ||kr*td| dkr:td|}t|dddddddfd|d|dddddddf<t|dddddddfd|d|dddddddf<|durtdg||| |}|durd }t|jdkr||| |}|j\} } } | dkrD|d krD||| |}t |D]} t | D]} |r|| | ddddf|| ddt || | dft || | d fdt || | dft || | dfdf<qZ|| | dddf|| ddt || | dft || | d fd|| | dff<|| | dddf|| ddt || | dft || | d fd|| | dff<|| | dddf|| dd|| | dft || | dft || | dfdf<|| | dddf|| dd|| | d ft || | dft || | dfdf<qZqL|S) aGDraw N rectangles on a batch of image tensors. Args: image: is tensor of BxCxHxW. rectangle: represents number of rectangles to draw in BxNx4 N is the number of boxes to draw per batch index[x1, y1, x2, y2] 4 is in (top_left.x, top_left.y, bot_right.x, bot_right.y). color: a size 1, size 3, BxNx1, or BxNx3 tensor. If C is 3, and color is 1 channel it will be broadcasted. fill: is a flag used to fill the boxes with color if True. Returns: This operation modifies image inplace but also returns the drawn tensor for convenience with same shape the of the input BxCxHxW. Example: >>> img = torch.rand(2, 3, 10, 12) >>> rect = torch.tensor([[[0, 0, 4, 4]], [[4, 4, 10, 10]]]) >>> out = draw_rectangle(img, rect) z-Image batch and rectangle batch must be equalz'Number of points in rectangle must be 4NrrrgFr) shapeAssertionErrorr$cloner!clampZtensorexpandrr&int)r r.r r/batchchwZ batch_rectZ num_rectangleZ num_pointsbnZcolor_channelsrrrdraw_rectanglesT  BB &&BBBJr=)polygonr9r:r c Cs|j}t|ddddf|ddddfsRtj||dddddffdd}|ddddf|ddddf}}|ddddf|ddddf}}tj||j|d}||||d | |} |ddddf|ddddf| ddddf|ddddf} |ddddf|ddddfk|ddddf|ddddfk} | |ddddf|ddddfk|ddddf|ddddfkO} | } || | <| } d| | <| j ddj }| j ddj }||fS) aGets the left and right edges of a polygon for each y-coordinate y \in [0, h) Args: polygons: represents polygons to draw in BxNx2 N is the number of points 2 is (x, y). h: bottom most coordinate (top coordinate is assumed to be 0) w: right most coordinate (left coordinate is assumed to be 0) Returns: The left and right edges of the polygon of shape (B,B). .rNrr)Zdimr dtypeg-q=) rAr!Zallclosecataranger r4 logical_andr3r#valuesr%)r>r9r:rAZx_startZy_startZx_endZy_endZysZdxxsZ valid_edgesZ x_left_edgesZ x_right_edgesx_leftx_rightrrr_get_convex_edgess" ($&&HJN  rI)polygonsr c Cst|tt|td}}tj||d|dj|djd}t|D]B\}}t||kr|t||dd|t|dfn|||<qB|S)aConverts a List of variable length polygons into a fixed size tensor. Works by repeating the last element in the tensor. Args: polygon: List of variable length polygons of shape [N_1 x 2, N_2 x 2, ..., N_B x 2]. B is the batch size, N_i is the number of points, 2 is (x, y). Returns: A fixed size tensor of shape (B, N, 2) where N = max_i(N_i) )keyrr)rAr rN) rr%r!zerosrAr enumeraterBr5)rJrNZbatched_polygonsr;prrr_batch_polygonss  <rP)imagesrJcolorsr cCsft|gdg|j|jR\}}}}}t|tr>> img = torch.rand(1, 3, 12, 16) >>> poly = torch.tensor([[[4, 4], [12, 4], [12, 8], [4, 8]]]) >>> color = torch.tensor([[0.5, 0.5, 0.5]]) >>> out = draw_convex_polygon(img, poly, color) )rrHWrrz/Polygon vertices must be xy, i.e. 2-dimensionalz8Image, polygon, and color must have same batch dimensionz/Image, polygon, and color must have same devicer@N.).NN) rr1r isinstancerrPrArr5rrIr!rC)rQrJrRZb_iZc_iZh_iZw_ir Zb_p_ZxyZdevice_pZdtype_pZb_cZdevice_crGrHwsZ fill_regionrrrdraw_convex_polygons  " ,.rX)NN)typingrrrrr!rZkornia.testingrrr6rr-boolr=rIrPrXrrrrs  n M)