| | from PIL import Image, ImageDraw, ImageFont |
| | import numpy as np |
| | import textwrap |
| | import cv2 |
| |
|
| |
|
| | def add_text(image, text, font_path, bubble_contour): |
| | """ |
| | Add text inside a speech bubble contour. |
| | |
| | Args: |
| | image (numpy.ndarray): Processed bubble image (cv2 format - BGR). |
| | text (str): Text to be placed inside the speech bubble. |
| | font_path (str): Font path. |
| | bubble_contour (numpy.ndarray): Contour of the detected speech bubble. |
| | |
| | Returns: |
| | numpy.ndarray: Image with text placed inside the speech bubble. |
| | """ |
| | pil_image = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)) |
| | draw = ImageDraw.Draw(pil_image) |
| |
|
| | x, y, w, h = cv2.boundingRect(bubble_contour) |
| |
|
| | line_height = 16 |
| | font_size = 14 |
| | wrapping_ratio = 0.075 |
| |
|
| | wrapped_text = textwrap.fill(text, width=int(w * wrapping_ratio), |
| | break_long_words=True) |
| | |
| | font = ImageFont.truetype(font_path, size=font_size) |
| |
|
| | lines = wrapped_text.split('\n') |
| | total_text_height = (len(lines)) * line_height |
| |
|
| | while total_text_height > h: |
| | line_height -= 2 |
| | font_size -= 2 |
| | wrapping_ratio += 0.025 |
| |
|
| | wrapped_text = textwrap.fill(text, width=int(w * wrapping_ratio), |
| | break_long_words=True) |
| | |
| | font = ImageFont.truetype(font_path, size=font_size) |
| |
|
| | lines = wrapped_text.split('\n') |
| | total_text_height = (len(lines)) * line_height |
| |
|
| | |
| | text_y = y + (h - total_text_height) // 2 |
| |
|
| | for line in lines: |
| | text_length = draw.textlength(line, font=font) |
| |
|
| | |
| | text_x = x + (w - text_length) // 2 |
| |
|
| | draw.text((text_x, text_y), line, font=font, fill=(0, 0, 0)) |
| |
|
| | text_y += line_height |
| |
|
| | image[:, :, :] = cv2.cvtColor(np.array(pil_image), cv2.COLOR_RGB2BGR) |
| |
|
| | return image |
| |
|