Abstract
Abstract: In today's digital era, the influx of video content inundates online platforms daily, presenting a formidable challenge for users seeking relevant information within these extensive recordings, particularly under time constraints. The process of extracting crucial insights fromlengthy videos often proves daunting and time- consuming. Clip Outliner is an innovative project that offers a versatile solution for summarizing both textual and video content. This tool combinesthe capabilities of a text summarizer with advanced video analysis features, providing users with concise textual summaries while also offeringinsights into video content. Leveraging Python APIs for text transcription and employing natural language processing (NLP)techniques, transcripts are efficiently condensed. The user interface is meticulously crafted using Streamlit serving as the robust open-source framework in Python.
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