40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
from functools import partial
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import cv2
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import numpy as np
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from cv_analysis.figure_detection.figures import detect_large_coherent_structures
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from cv_analysis.figure_detection.text import remove_primary_text_regions
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from cv_analysis.utils.filters import (
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is_large_enough,
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has_acceptable_format,
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is_not_too_large,
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)
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from cv_analysis.utils.postprocessing import remove_included
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from cv_analysis.utils.structures import Rectangle
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def detect_figures(image: np.array):
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max_area = image.shape[0] * image.shape[1] * 0.99
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min_area = 5000
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max_width_to_height_ratio = 6
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figure_filter = partial(is_likely_figure, min_area, max_area, max_width_to_height_ratio)
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image = remove_primary_text_regions(image)
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cnts = detect_large_coherent_structures(image)
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cnts = filter(figure_filter, cnts)
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rects = map(cv2.boundingRect, cnts)
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rects = map(Rectangle.from_xywh, rects)
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rects = remove_included(rects)
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return rects
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def is_likely_figure(min_area, max_area, max_width_to_height_ratio, cnts):
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return (
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is_not_too_large(cnts, max_area)
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and is_large_enough(cnts, min_area)
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and has_acceptable_format(cnts, max_width_to_height_ratio)
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)
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