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from PIL import Image, ImageDraw, ImageFont | |
import cv2 | |
import os | |
import textwrap | |
import nltk | |
nltk.download('punkt', quiet=True) | |
nltk.download('averaged_perceptron_tagger', quiet=True) | |
from nltk.tokenize import word_tokenize | |
from nltk import pos_tag | |
def read_image_width_height(image_path): | |
image = Image.open(image_path) | |
width, height = image.size | |
return width, height | |
def display_images_and_text(source_image_path, generated_image, generated_paragraph, outfile_name): | |
source_image = Image.open(source_image_path) | |
# Create a new image that can fit the images and the text | |
width = source_image.width + generated_image.width | |
height = max(source_image.height, generated_image.height) | |
new_image = Image.new("RGB", (width, height + 150), "white") | |
# Paste the source image and the generated image onto the new image | |
new_image.paste(source_image, (0, 0)) | |
new_image.paste(generated_image, (source_image.width, 0)) | |
# Write the generated paragraph onto the new image | |
draw = ImageDraw.Draw(new_image) | |
# font_size = 12 | |
# font = ImageFont.load_default().font_variant(size=font_size) | |
font_path = os.path.join(cv2.__path__[0],'qt','fonts','DejaVuSans.ttf') | |
font = ImageFont.truetype(font_path, size=14) | |
# Wrap the text for better display | |
wrapped_text = textwrap.wrap(generated_paragraph, width=170) | |
# Draw each line of wrapped text | |
line_spacing = 18 | |
y_offset = 0 | |
for line in wrapped_text: | |
draw.text((0, height + y_offset), line, font=font, fill="black") | |
y_offset += line_spacing | |
# Show the final image | |
# new_image.show() | |
new_image.save(outfile_name) | |
return 1 | |
def extract_nouns_nltk(paragraph): | |
words = word_tokenize(paragraph) | |
pos_tags = pos_tag(words) | |
nouns = [word for word, tag in pos_tags if tag in ('NN', 'NNS', 'NNP', 'NNPS')] | |
return nouns | |