i"NdZddlZddlZd dZ d dZdZdZdZdZ d Z d Z y) zpFunctions useful for detecting graphical elements from the image to using OpenCV to reconstruct / detect tables.Nctj|}tj|tj}|st j |}tj |dtjtj||}||fS)akThresholds an image using OpenCV's adaptiveThreshold. Parameters ---------- imagename : string Path to image file. process_background : bool, optional (default: False) Whether or not to process lines that are in background. blocksize : int, optional (default: 15) Size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, and so on. For more information, refer `OpenCV's adaptiveThreshold `_. c : int, optional (default: -2) Constant subtracted from the mean or weighted mean. Normally, it is positive but may be zero or negative as well. For more information, refer `OpenCV's adaptiveThreshold `_. Returns ------- img : object numpy.ndarray representing the original image. threshold : object numpy.ndarray representing the thresholded image. ) cv2imreadcvtColorCOLOR_BGR2GRAYnpinvertadaptiveThresholdADAPTIVE_THRESH_GAUSSIAN_C THRESH_BINARY) imagenameprocess_background blocksizecimggray thresholds K/home/agent/.local/lib/python3.12/site-packages/camelot/image_processing.pyadaptive_thresholdrsn: **Y C <<S// 0D yy%% c31133D3DiQRI  >c8|dvr tdt|||\}}t||}t|||}t j |j tjtjtj\}} t||} || fS)ae Finds horizontal and vertical lines by applying morphological transformations on an image. Parameters ---------- threshold : object numpy.ndarray representing the thresholded image. regions : list, optional (default: None) List of page regions that may contain tables of the form x1,y1,x2,y2 where (x1, y1) -> left-top and (x2, y2) -> right-bottom in image coordinate space. direction : string, optional (default: 'horizontal') Specifies whether to find vertical or horizontal lines. line_scale : int, optional (default: 40) Factor by which the page dimensions will be divided to get smallest length of lines that should be detected. iterations : int, optional (default: 0) Number of times for erosion/dilation is applied. Returns ------- dmask : object numpy.ndarray representing pixels where vertical/horizontal lines lie. lines : list List of tuples representing vertical/horizontal lines with coordinates relative to a left-top origin in image coordinate space. )vertical horizontalz6Specify direction as either 'vertical' or 'horizontal') ValueErrorcreate_structuring_elementapply_region_mask process_imager findContoursastyper uint8 RETR_EXTERNALCHAIN_APPROX_SIMPLEextract_lines_from_contours) rregions direction line_scale iterationselsizeprocessed_thresholdcontours_liness r find_linesr/.s@22QRR))Y KHB!)W5I' 2zB""""288,c.?.?AXAXKHa () x1x2y1y2s rr$r$s E C%%a( 1aAEBAEB  " LL27q."rBw1nbA B , & LL"rBw1nb27q.A BC Lrc||z}tj|jtjtj tj \}}t|tjddd}g}|D]H}tj|dd}tj|\}} } } |j|| | | fJ|S)aFind table boundaries using OpenCV's findContours. Parameters ---------- vertical : object numpy.ndarray representing pixels where vertical lines lie. horizontal : object numpy.ndarray representing pixels where horizontal lines lie. Returns ------- cont : list List of tuples representing table boundaries. Each tuple is of the form (x, y, w, h) where (x, y) -> left-top, w -> width and h -> height in image coordinate space. T)keyreverseN ) rrr r r!r"r#sorted contourArea approxPolyDPrErF) rrmaskr,__contrc_polyr;r<r=r>s r find_contoursrWs$ j D## BHHs00#2I2ILHbhCOOTB3BGH D "!!!Q-%%f- 1a Q1aL!" Krctj||}i}|D]}|\}}}} |||| z|||zf} tj| j tj tj tj\} } t| dkr}g} | D]K}tj|\}}}}|d|z|zdzz|d|z|zdzz}}| j||fM| |||| z||z|f<|S)aFind joints/intersections present inside each table boundary. Parameters ---------- contours : list List of tuples representing table boundaries. Each tuple is of the form (x, y, w, h) where (x, y) -> left-top, w -> width and h -> height in image coordinate space. vertical : object numpy.ndarray representing pixels where vertical lines lie. horizontal : object numpy.ndarray representing pixels where horizontal lines lie. Returns ------- tables : dict Dict with table boundaries as keys and list of intersections in that boundary as their value. Keys are of the form (x1, y1, x2, y2) where (x1, y1) -> lb and (x2, y2) -> rt in image coordinate space. rD) r r8rrr r! RETR_CCOMPr#lenrErF)r,rrjointstablesrr;r<r=r>roijcrT joint_coordsjjxjyjwjhc1c2s r find_jointsrhs%.[[: .F F  4 1aQQYAE )*!! JJrxx #..#2I2I B r7a<   *A --a0NBB!b&2+!++Q!b&2+!1C-CB   R ) *(41q5!a%#$ 4 Mr)F)Nr(r) __doc__rnumpyr rr/rrrr$rWrhrrros@v $PPQ-&`842:D(r