58 lines
1.8 KiB
Python
58 lines
1.8 KiB
Python
import cv2
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import numpy as np
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from pdf2image import pdf2image
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from cv_analysis.utils.detection import detect_large_coherent_structures
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from cv_analysis.utils.display import show_mpl
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from cv_analysis.utils.draw import draw_rectangles
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from cv_analysis.utils.post_processing import remove_included
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from cv_analysis.utils.filters import is_large_enough, has_acceptable_format
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from cv_analysis.utils.text import remove_primary_text_regions
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from cv_analysis.utils.visual_logging import vizlogger
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#from PIL import Image
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def is_likely_figure(cont, min_area=5000, max_width_to_hight_ratio=6):
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return is_large_enough(cont, min_area) and has_acceptable_format(cont, max_width_to_hight_ratio)
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def detect_figures(image: np.array):
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image = image.copy()
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vizlogger.debug(image, "figures01_start.png")
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image = remove_primary_text_regions(image)
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vizlogger.debug(image, "figures02_remove_text.png")
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cnts = detect_large_coherent_structures(image)
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cnts = filter(is_likely_figure, cnts)
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rects = map(cv2.boundingRect, cnts)
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rects = remove_included(rects)
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return list(rects)
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def detect_figures_in_pdf(pdf_path, page_index=1, show=False):
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page = pdf2image.convert_from_path(pdf_path, first_page=page_index + 1, last_page=page_index + 1)[0]
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page = np.array(page)
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redaction_contours = detect_figures(page)
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page = draw_rectangles(page, redaction_contours)
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vizlogger.debug(page, "figures03_final.png")
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if show:
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show_mpl(page)
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return page
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# pages = []
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# for i in range(0,16):
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# pdf_path = "/home/lillian/ocr_docs/Report on spectra.pdf"
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# page_index = i
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# page = detect_figures_in_pdf(pdf_path,page_index)
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# pages.append(Image.fromarray(page))
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# p1, p = pages[0], pages[1:]
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#
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# out_pdf_path = "/home/lillian/ocr_docs/out.pdf"
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#
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# p1.save(
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# out_pdf_path, "PDF", resolution=150.0, save_all=True, append_images=p
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# ) |