cv-analysis-service/vidocp/utils/text.py

import cv2


def remove_primary_text_regions(image):
    """Removes regions of primary text, meaning no figure descriptions for example, but main text body paragraphs.

    Args:
        image: Image to remove primary text from.

    Returns:
        Image with primary text removed.
    """

    image = image.copy()

    cnts = find_primary_text_regions(image)

    for cnt in cnts:
        x, y, w, h = cv2.boundingRect(cnt)
        cv2.rectangle(image, (x, y), (x + w, y + h), (255, 255, 255), -1)

    return image


def find_primary_text_regions(image):
    """Finds regions of primary text, meaning no figure descriptions for example, but main text body paragraphs.

    Args:
        image: Image to remove primary text from.

    Returns:
        Image with primary text removed.

    References:
        https://stackoverflow.com/questions/58349726/opencv-how-to-remove-text-from-background
    """

    def is_likely_primary_text_segments(cnt):
        return 800 < cv2.contourArea(cnt) < 15000

    image = image.copy()

    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

    thresh = cv2.threshold(gray, 253, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

    close_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (20, 3))
    close = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, close_kernel, iterations=1)

    dilate_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 3))
    dilate = cv2.dilate(close, dilate_kernel, iterations=1)

    cnts, _ = cv2.findContours(dilate, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

    cnts = filter(is_likely_primary_text_segments, cnts)

    return cnts