An advanced platform designed to streamline metadata generation for stock media, including images, vectors, video. Metadata Stock Generator combines user-provided information with algorithmically generated data to produce rich, descriptive metadata for each stock item. Leveraging web scraping, the platform gathers metadata from similar stock items across various sites. It uses techniques to analyze colors, shapes, and patterns, while large language models (LLMs) generate contextually accurate metadata, transforming and filtering it as needed. The result s an optimized metadata output in multiple formats, enhancing the discoverability and relevance of stock content.
Challenge
The key challenge was to integrate user-provided metadata with data derived from item analysis and algorithmically generated metadata, producing consistent and accurate descriptors across diverse media types. The platform needed to adapt metadata to suit different formats while ensuring relevance, specificity, and uniqueness. Additionally, seamless web scraping and processing were required to collect similar metadata and refine it through natural language processing.
Solution
Metadata Stock Generator was built with a Python-based backend, incorporating NLTK and OpenAI's API for natural language processing (NLP). Utilizing Python graphic libraries alongside Azure Computer Vision, the platform analyzes graphical assets for colors, shapes, and patterns, while Google Functions manage serverless operations for streamlined processing. By blending user-provided data with algorithmically generated content, the platform creates metadata optimized for relevance and presentation, stored in flexible formats suitable for immediate use.
Components
Backend: Developed with Python for robust data processing and graphic analysis, ensuring metadata generation is scalable and secure.
Scraping and Analysis: Utilizes Azure Computer Vision and Python graphic libraries for detailed analysis of visual elements and web scraping techniques to gather metadata similar to specified stock items.
Metadata Generation: Powered by OpenAI's LLMs and standalone Python NLP capabilities to produce, transform, and filter metadata, aligning it with content and context requirements.
Technologies
Python, OpenAI, Natural Language Processing (NLP), python-nltk, python-pandas, Azure Computer Vision, Google Functions.
Clients
Self-Hosted project
