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🚀 Built an AI-powered tool that scrapes a website and auto-generates captions for every image on it
1️⃣ What I built
A tool where you just paste a website link, and it automatically finds every image on that page and writes a caption for each one — describing what's in the picture. It also saves everything into downloadable files.
2️⃣ Why it's useful
Normally, writing descriptions for images takes a lot of time if done manually. This tool does it in seconds, for as many images as the website has.
the entire process — turning hours of manual work into a single click.
3️⃣ How it can be applied in real apps / the future
🔹 Auto-generating alt-text for website accessibility (screen readers)
🔹 Improving SEO with descriptive image tags
🔹 Speeding up product cataloging for e-commerce
🔹 Helping archives/newsrooms tag large image collections
🔹 Could evolve into a browser extension or developer API
4️⃣ Tools I used
Python, Gradio (for the interface), Hugging Face's BLIP AI model (for generating captions), BeautifulSoup (to read the website), Requests (to fetch data), Pillow (to handle images), and Pandas (to save results as a file).
5️⃣ Why I chose these tools
🔹 BLIP is a ready-made AI model, so I didn't need to train one myself
🔹 Gradio helped me build a clean interface quickly, without coding a full website
🔹 BeautifulSoup made it simple to read and collect images from any webpage
6️⃣ What I learned
🔹 Working with pretrained vision-language models in a real app
🔹 Handling real scraping issues — broken links, timeouts, corrupted files
🔹 Designing a clean, professional UI/UX for an AI tool
🔹 The gap between a proof-of-concept and a genuinely usable tool
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