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74 lines
4.6 KiB
Python
74 lines
4.6 KiB
Python
# 最终版：把那种text_block有重叠，且inline_formula位置在重叠部分的，认定整个页面都有问题，所有的inline_formula都改成no_check
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from libs.commons import fitz
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def check_inline_formula(page, inline_formula_boxes):
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"""
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:param page :fitz读取的当前页的内容
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:param inline_formula_boxes: list类型，每一个元素是一个元祖 (L, U, R, D)
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:return: inline_formula_check: list类型，每一个元素是一个类别，其顺序对应输入的inline_formula_boxes，给每个行内公式打一个标签，包括：
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- nocheck_inline_formula：这个公式框没有与任何span相交，有可能存在问题
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- wrong_text_block：这个公式框同时存在多个block里，可能页面的text block存在问题
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- false_inline_formula：只涉及一个span并且只占据这个span的小部分面积，判断可能不是公式
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- true_inline_formula：两种情况判断为公式，一是横跨多个span，二是只涉及一个span但是几乎占据了这个span大部分的面积
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"""
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# count = defaultdict(int)
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## ------------------------ Text --------------------------------------------
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blocks = page.get_text(
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"dict",
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flags=fitz.TEXTFLAGS_TEXT,
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#clip=clip,
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)["blocks"]
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# iterate over the bboxes
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inline_formula_check = []
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for result in inline_formula_boxes:
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(x1, y1, x2, y2) = (result[0], result[1], result[2], result[3])
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## 逐个block##
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in_block = 0
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for bbox in blocks:
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# image = cv2.rectangle(image, (int(bbox['bbox'][0]), int(bbox['bbox'][1])), (int(bbox['bbox'][2]), int(bbox['bbox'][3])), (0, 255, 0), 1)
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if (y1 >= bbox['bbox'][1] and y2 <= bbox['bbox'][3]) and (x1 >= bbox['bbox'][0] and x2 <= bbox['bbox'][2]): # 判定公式在哪一个block
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in_block += 1
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intersect = []
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# ## 逐个span###
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for line in bbox['lines']:
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if line['bbox'][1] <= ((y2 - y1) / 2) + y1 <= line['bbox'][3]: # 判断公式在哪一行
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for item in line['spans']:
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(t_x1, t_y1, t_x2, t_y2) = item['bbox']
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if not ((t_x1 < x1 and t_x2 < x1) or (t_x1 > x2 and t_x2 > x2) or (t_y1 < y1 and t_y2 < y1) or (t_y1 > y2 and t_y2 > y2)): # 判断是否相交
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intersect.append(item['bbox'])
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# image = cv2.rectangle(image, (int(t_x1), int(t_y1)), (int(t_x2), int(t_y2)), (0, 255, 0), 1) # 可视化涉及到的span
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# 可视化公式的分类
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if len(intersect) == 0: # 没有与任何一个span有相交，这个span或者这个inline_formula_box可能有问题
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# print(f'Wrong location, check {img_path}')
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inline_formula_check_result = "nocheck_inline_formula"
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# count['not_in_line'] += 1
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elif len(intersect) == 1:
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if abs((intersect[0][2] - intersect[0][0]) - (x2 - x1)) < (x2 - x1)*0.5: # 只涉及一个span但是几乎占据了这个span大部分的面积，判定为公式
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# image = cv2.rectangle(image, (int(x1), int(y1)), (int(x2), int(y2)), (0, 255, 0), 1)
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inline_formula_check_result = "true_inline_formula"
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# count['one_span_large'] += 1
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else: # 只涉及一个span并且只占据这个span的小部分面积，判断可能不是公式
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# image = cv2.rectangle(image, (int(x1), int(y1)), (int(x2), int(y2)), (0, 0, 255), 1)
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inline_formula_check_result = "false_inline_formula"
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# count['fail'] += 1
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else: # 横跨多个span,判定为公式
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# image = cv2.rectangle(image, (int(x1), int(y1)), (int(x2), int(y2)), (255, 0, 0), 1)
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inline_formula_check_result = "true_inline_formula"
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# count['multi_span'] += 1
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if in_block == 0: # 这个公式没有在任何的block里，这个公式可能有问题
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# image = cv2.rectangle(image, (int(x1), int(y1)), (int(x2), int(y2)), (255, 255, 0), 1)
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inline_formula_check_result = "nocheck_inline_formula"
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# count['not_in_block'] += 1
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elif in_block > 1: # 这个公式存在于多个block里，这个页面可能有问题
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inline_formula_check_result = "wrong_text_block"
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inline_formula_check.append(inline_formula_check_result)
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return inline_formula_check
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