image crawler and search app

In today’s digital age, image retrieval has become an essential tool across domains—whether it’s for education, design, presentations, research, or content creation. While many popular search engines offer robust image search functionalities, building a lightweight, customizable, and fast image search engine as a standalone application offers immense educational and technical value. This project is a Flask-based Image Search Web App that allows users to input a keyword and receive a visual grid of relevant images scraped dynamically from the web using a custom-built crawler. The project is designed to be responsive, visually appealing, and lightweight, while still incorporating useful features like light/dark mode, and potential for interactive navigation . Designed and implemented in a tight timeframe during a hackathon (by a solo developer ), this application focuses on demonstrating rapid full-stack development, real-time data handling, and user-centric UI/UX. This Flask-based image search app demonstrates how a developer can combine multiple disciplines—web scraping, server-side logic, and front-end design—into a fully working, interactive tool within a short timeframe. Despite being built solo in under an hour, it showcases a solid grasp of full-stack principles, creative problem-solving, and efficient UI/UX design. In a hackathon setting, such a project is highly valuable for: Demonstrating technical depth and versatility. Delivering a useful, working prototype. Leaving room for scalability and polish. While additional features like swipe gestures and modal previews were initially planned but caused conflicts, their attempted integration reflects thoughtful design ambitions. Overall, the project provides a functional base with potential for real-world usage or future academic/portfolio work.