import numpy as np import cv2 class Element: def __init__(self, id, corner, category, text_content=None): self.id = id self.category = category self.col_min, self.row_min, self.col_max, self.row_max = corner self.width = self.col_max - self.col_min self.height = self.row_max - self.row_min self.area = self.width * self.height self.text_content = text_content self.parent_id = None self.children = [] # list of elements def init_bound(self): self.width = self.col_max - self.col_min self.height = self.row_max - self.row_min self.area = self.width * self.height def put_bbox(self): return self.col_min, self.row_min, self.col_max, self.row_max def wrap_info(self): info = {'id':self.id, 'class': self.category, 'height': self.height, 'width': self.width, 'position': {'column_min': self.col_min, 'row_min': self.row_min, 'column_max': self.col_max, 'row_max': self.row_max}} if self.text_content is not None: info['text_content'] = self.text_content if len(self.children) > 0: info['children'] = [] for child in self.children: info['children'].append(child.id) if self.parent_id is not None: info['parent'] = self.parent_id return info def resize(self, resize_ratio): self.col_min = int(self.col_min * resize_ratio) self.row_min = int(self.row_min * resize_ratio) self.col_max = int(self.col_max * resize_ratio) self.row_max = int(self.row_max * resize_ratio) self.init_bound() def element_merge(self, element_b, new_element=False, new_category=None, new_id=None): col_min_a, row_min_a, col_max_a, row_max_a = self.put_bbox() col_min_b, row_min_b, col_max_b, row_max_b = element_b.put_bbox() new_corner = (min(col_min_a, col_min_b), min(row_min_a, row_min_b), max(col_max_a, col_max_b), max(row_max_a, row_max_b)) if element_b.text_content is not None: self.text_content = element_b.text_content if self.text_content is None else self.text_content + '\n' + element_b.text_content if new_element: return Element(new_id, new_corner, new_category) else: self.col_min, self.row_min, self.col_max, self.row_max = new_corner self.init_bound() def calc_intersection_area(self, element_b, bias=(0, 0)): a = self.put_bbox() b = element_b.put_bbox() col_min_s = max(a[0], b[0]) - bias[0] row_min_s = max(a[1], b[1]) - bias[1] col_max_s = min(a[2], b[2]) row_max_s = min(a[3], b[3]) w = np.maximum(0, col_max_s - col_min_s) h = np.maximum(0, row_max_s - row_min_s) inter = w * h iou = inter / (self.area + element_b.area - inter) ioa = inter / self.area iob = inter / element_b.area return inter, iou, ioa, iob def element_relation(self, element_b, bias=(0, 0)): """ @bias: (horizontal bias, vertical bias) :return: -1 : a in b 0 : a, b are not intersected 1 : b in a 2 : a, b are identical or intersected """ inter, iou, ioa, iob = self.calc_intersection_area(element_b, bias) # area of intersection is 0 if ioa == 0: return 0 # a in b if ioa >= 1: return -1 # b in a if iob >= 1: return 1 return 2 def visualize_element(self, img, color=(0, 255, 0), line=1, show=False): loc = self.put_bbox() cv2.rectangle(img, loc[:2], loc[2:], color, line) # for child in self.children: # child.visualize_element(img, color=(255, 0, 255), line=line) if show: cv2.imshow('element', img) cv2.waitKey(0) cv2.destroyWindow('element')