georgescutelnicu
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7050235
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Parent(s):
1b78324
Upload 2 files
Browse files- add_text.py +65 -0
- translator.py +41 -0
add_text.py
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from PIL import Image, ImageDraw, ImageFont
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import numpy as np
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import textwrap
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import cv2
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def add_text(image, text, font_path, bubble_contour):
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"""
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Add text inside a speech bubble contour.
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Args:
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image (numpy.ndarray): Processed bubble image (cv2 format - BGR).
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text (str): Text to be placed inside the speech bubble.
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font_path (str): Font path.
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bubble_contour (numpy.ndarray): Contour of the detected speech bubble.
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Returns:
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numpy.ndarray: Image with text placed inside the speech bubble.
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"""
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pil_image = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
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draw = ImageDraw.Draw(pil_image)
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x, y, w, h = cv2.boundingRect(bubble_contour)
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line_height = 16
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font_size = 14
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wrapping_ratio = 0.075
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wrapped_text = textwrap.fill(text, width=int(w * wrapping_ratio),
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break_long_words=True)
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font = ImageFont.truetype(font_path, size=font_size)
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lines = wrapped_text.split('\n')
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total_text_height = (len(lines)) * line_height
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while total_text_height > h:
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line_height -= 2
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font_size -= 2
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wrapping_ratio += 0.025
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wrapped_text = textwrap.fill(text, width=int(w * wrapping_ratio),
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break_long_words=True)
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font = ImageFont.truetype(font_path, size=font_size)
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lines = wrapped_text.split('\n')
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total_text_height = (len(lines)) * line_height
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# Vertical centering
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text_y = y + (h - total_text_height) // 2
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for line in lines:
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text_length = draw.textlength(line, font=font)
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# Horizontal centering
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text_x = x + (w - text_length) // 2
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draw.text((text_x, text_y), line, font=font, fill=(0, 0, 0))
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text_y += line_height
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image[:, :, :] = cv2.cvtColor(np.array(pil_image), cv2.COLOR_RGB2BGR)
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return image
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translator.py
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from deep_translator import GoogleTranslator
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from transformers import pipeline
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class MangaTranslator:
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def __init__(self):
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self.target = "en"
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self.source = "ja"
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def translate(self, text, method="google"):
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"""
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Translates the given text to the target language using the specified method.
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Args:
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text (str): The text to be translated.
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method (str):'google' for Google Translator,
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'hf' for Helsinki-NLP's opus-mt-ja-en model (HF pipeline)
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Returns:
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str: The translated text.
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"""
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if method == "hf":
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return self._translate_with_hf(self._preprocess_text(text))
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elif method == "google":
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return self._translate_with_google(self._preprocess_text(text))
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else:
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raise ValueError("Invalid translation method.")
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def _translate_with_google(self, text):
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translator = GoogleTranslator(source=self.source, target=self.target)
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translated_text = translator.translate(text)
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return translated_text if translated_text != None else text
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def _translate_with_hf(self, text):
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pipe = pipeline("translation", model=f"Helsinki-NLP/opus-mt-ja-en")
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translated_text = pipe(text)[0]["translation_text"]
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return translated_text if translated_text != None else text
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def _preprocess_text(self, text):
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preprocessed_text = text.replace(".", ".")
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return preprocessed_text
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