import cv2 import matplotlib.pyplot as plt import matplotlib.patches as patches from .handlers import PDFHandler from .utils import validate_input, remove_extra def plot_geometry(filepath, pages='1', mesh=False, geometry_type=None, **kwargs): """Plot geometry found on pdf page based on type specified, useful for debugging and playing with different parameters to get the best output. Note: kwargs annotated with ^ can only be used with mesh=False and kwargs annotated with * can only be used with mesh=True. Parameters ---------- filepath : str Path to pdf file. pages : str Comma-separated page numbers to parse. Example: 1,3,4 or 1,4-end mesh : bool (default: False) Whether or not to use Lattice method of parsing. Stream is used by default. geometry_type : str, optional (default: None) * 'text' : Plot text objects found on page. (Useful to get \ table_area and columns coordinates) * 'table' : Plot parsed table. * 'contour'* : Plot detected rectangles. * 'joint'* : Plot detected line intersections. * 'line'* : Plot detected lines. table_area : list, optional (default: None) List of table areas to process as strings of the form x1,y1,x2,y2 where (x1, y1) -> left-top and (x2, y2) -> right-bottom in pdf coordinate space. columns^ : list, optional (default: None) List of column x-coordinates as strings where the coordinates are comma-separated. split_text : bool, optional (default: False) Whether or not to split a text line if it spans across multiple cells. flag_size : bool, optional (default: False) Whether or not to highlight a substring using if its size is different from rest of the string. (Useful for super and subscripts.) row_close_tol^ : int, optional (default: 2) Rows will be formed by combining text vertically within this tolerance. col_close_tol^ : int, optional (default: 0) Columns will be formed by combining text horizontally within this tolerance. process_background* : bool, optional (default: False) Whether or not to process lines that are in background. line_size_scaling* : int, optional (default: 15) Factor by which the page dimensions will be divided to get smallest length of lines that should be detected. The larger this value, smaller the detected lines. Making it too large will lead to text being detected as lines. copy_text* : list, optional (default: None) {'h', 'v'} Select one or more strings from above and pass them as a list to specify the direction in which text should be copied over when a cell spans multiple rows or columns. shift_text* : list, optional (default: ['l', 't']) {'l', 'r', 't', 'b'} Select one or more strings from above and pass them as a list to specify where the text in a spanning cell should flow. line_close_tol* : int, optional (default: 2) Tolerance parameter used to merge vertical and horizontal detected lines which lie close to each other. joint_close_tol* : int, optional (default: 2) Tolerance parameter used to decide whether the detected lines and points lie close to each other. threshold_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 `_. threshold_constant* : 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 `_. iterations* : int, optional (default: 0) Number of times for erosion/dilation is applied. For more information, refer `OpenCV's dilate `_. margins : tuple PDFMiner margins. (char_margin, line_margin, word_margin) For more information, refer `PDFMiner docs `_. """ validate_input(kwargs, mesh=mesh, geometry_type=geometry_type) p = PDFHandler(filepath, pages) kwargs = remove_extra(kwargs, mesh=mesh) debug = True if geometry_type is not None else False kwargs.update({'debug': debug}) __, geometry = p.parse(mesh=mesh, **kwargs) if geometry_type == 'text': for text in geometry.text: fig = plt.figure() ax = fig.add_subplot(111, aspect='equal') xs, ys = [], [] for t in text: xs.extend([t[0], t[1]]) ys.extend([t[2], t[3]]) ax.add_patch( patches.Rectangle( (t[0], t[1]), t[2] - t[0], t[3] - t[1] ) ) ax.set_xlim(min(xs) - 10, max(xs) + 10) ax.set_ylim(min(ys) - 10, max(ys) + 10) plt.show() elif geometry_type == 'table': for tables in geometry.tables: for table in tables: for row in table.cells: for cell in row: if cell.left: plt.plot([cell.lb[0], cell.lt[0]], [cell.lb[1], cell.lt[1]]) if cell.right: plt.plot([cell.rb[0], cell.rt[0]], [cell.rb[1], cell.rt[1]]) if cell.top: plt.plot([cell.lt[0], cell.rt[0]], [cell.lt[1], cell.rt[1]]) if cell.bottom: plt.plot([cell.lb[0], cell.rb[0]], [cell.lb[1], cell.rb[1]]) plt.show() elif geometry_type == 'contour': for img, table_bbox in geometry.images: for t in table_bbox.keys(): cv2.rectangle(img, (t[0], t[1]), (t[2], t[3]), (255, 0, 0), 3) plt.imshow(img) plt.show() elif geometry_type == 'joint': for img, table_bbox in geometry.images: x_coord = [] y_coord = [] for k in table_bbox.keys(): for coord in table_bbox[k]: x_coord.append(coord[0]) y_coord.append(coord[1]) max_x, max_y = max(x_coord), max(y_coord) plt.plot(x_coord, y_coord, 'ro') plt.axis([0, max_x + 100, max_y + 100, 0]) plt.imshow(img) plt.show() elif geometry_type == 'line': for v_s, h_s in geometry.segments: for v in v_s: plt.plot([v[0], v[2]], [v[1], v[3]]) for h in h_s: plt.plot([h[0], h[2]], [h[1], h[3]]) plt.show()