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#!/usr/bin/env python3
"""
Bubble Processing Module
========================
Processes detected text bubbles to prepare them for text replacement.
This module handles the cleaning and preparation of speech bubble regions
by removing existing text and creating a clean background.
Author: MangaTranslator Team
License: MIT
"""
import cv2
import numpy as np
def process_bubble(image):
"""
Process a speech bubble by removing existing text and creating a clean background
This function analyzes the bubble region, detects the bubble boundary,
and fills the interior with white color to prepare for new text insertion.
Args:
image (numpy.ndarray): Input image containing the speech bubble (BGR format)
Returns:
tuple: A tuple containing:
- image (numpy.ndarray): Processed image with white bubble interior
- largest_contour (numpy.ndarray): Contour of the detected bubble boundary
"""
# Convert to grayscale for processing
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Apply threshold to separate bubble from background
# Threshold value 240 works well for typical manga bubbles
_, thresh = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY)
# Find contours in the thresholded image
contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# Get the largest contour (assumed to be the speech bubble)
largest_contour = max(contours, key=cv2.contourArea)
# Create a mask for the bubble area
mask = np.zeros_like(gray)
cv2.drawContours(mask, [largest_contour], -1, 255, cv2.FILLED)
# Fill the bubble area with white color
image[mask == 255] = (255, 255, 255)
return image, largest_contour
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