import os import re import base64 import cv2 import numpy as np import shutil from bs4 import BeautifulSoup def extract_base64_image(html_file): """Extracts base64-encoded image data from an HTML file.""" with open(html_file, "r", encoding="utf-8") as f: soup = BeautifulSoup(f, "html.parser") img_tag = soup.find("img") if img_tag and 'src' in img_tag.attrs: match = re.search(r'data:image/png;base64,(.+)', img_tag['src']) if match: return match.group(1) return None def categorize_image(image_data): """Categorizes the image as 'grey', 'no image', or 'content'.""" if not image_data: return "no_image" img_array = np.frombuffer(base64.b64decode(image_data), dtype=np.uint8) img = cv2.imdecode(img_array, cv2.IMREAD_GRAYSCALE) if img is None: return "no_image" mean_value = cv2.mean(img)[0] # Average pixel brightness std_dev = np.std(img) # Standard deviation of pixel values if mean_value > 200 and std_dev < 10: return "grey" return "content" def process_html_files(input_folder, output_html="gallery.html"): """Processes all HTML files, categorizes them, and generates a gallery.""" categories = {"no_image": [], "grey": [], "content": []} for file in os.listdir(input_folder): if file.endswith(".html") and not file.startswith('report'): file_path = os.path.join(input_folder, file) image_data = extract_base64_image(file_path) category = categorize_image(image_data) categories[category].append((file, image_data)) with open(output_html, "w", encoding="utf-8") as f: f.write(""" Image Gallery

Image Gallery

""") for category, files in categories.items(): f.write(f"

{category.replace('_', ' ').title()}

") f.write("

") for file_name, img_data in files: if img_data: f.write(f"

") else: f.write(f"

[No Image]

") f.write("

") f.write("") print(f"Gallery created at {output_html}") if __name__ == "__main__": input_folder = "./output" # Change to your directory process_html_files(input_folder, "output/gallery.html")