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camelotで点線を実線として処理する(ハフ変換)

Last updated at Posted at 2020-11-03

はじめに

camelotは点線が苦手でよく失敗するので調べてみると以下の参考の記事が見つかりました

camelotはopencvで抽出しているので点線を書き換えればいいみたいなのでハフ変換で点線を抽出し実線で上書きしてみたらうまくいきました

参考

Pythonを使えばテキストを含むPDFの解析は簡単だ・・・そんなふうに考えていた時期が俺にもありました

camelotで点線を実線として処理する

こちらの記事の横の点線のPDFを使わせていただきます

ハフ変換

OpenCVのハフ変換による直線検出

data1.png

ハフ変換で直線抽出

houghline.png

千葉のGo To Eatの加盟店一覧のPDF

data1(1).png

ハフ変換で水平の直線のみ抽出

houghline(1).png

プログラム

import cv2
import numpy as np

import camelot

# パッチ作成

def my_threshold(imagename, process_background=False, blocksize=15, c=-2):

    img = cv2.imread(imagename)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    edges = cv2.Canny(gray, 50, 150, apertureSize=3)

    lines = cv2.HoughLinesP(
        edges, rho=1, theta=np.pi / 180, threshold=80, minLineLength=3000, maxLineGap=50
    )

    for line in lines:
        x1, y1, x2, y2 = line[0]
        # 水平の場合はy1 == y2、垂直の場合はx1 == x2のifでフィルタする
        cv2.line(img, (x1, y1), (x2, y2), (0, 0, 0), 1) 

    if process_background:
        threshold = cv2.adaptiveThreshold(
            gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, blocksize, c
        )
    else:
        threshold = cv2.adaptiveThreshold(
            np.invert(gray),
            255,
            cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
            cv2.THRESH_BINARY,
            blocksize,
            c,
        )
    return img, threshold

camelot.parsers.lattice.adaptive_threshold = my_threshold

tables = camelot.read_pdf("data.pdf", pages="all")

tables[0].df

パッチ摘要前

点線部分が反応しないため縦に結合してしまっている
Screenshot_2020-11-04 Google Colaboratory(1).png

パッチ摘要後

Screenshot_2020-11-04 Google Colaboratory.png

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