The idea for "Video Analysis with OpenAI" arose from the ever-growing video content on the internet. With the overwhelming amount of content, it becomes challenging for people to make sense of it all. Additionally, there are many situations in which the automatic transcript and context of the video become crucial: be it for accessibility, content summarization, searchability, or even content moderation.
As per the latest statistics, about 500 hours of video are uploaded to YouTube every minute. The demand for automated video analysis tools is at an all-time high. Content creators, educators, and businesses all have a need to analyze, understand, and extract insights from video content. Our target demographic ranges from college students, who would find it useful in academic contexts, to businesses and professionals who need it for understanding their video data.
"Video Analysis with OpenAI" revolutionizes the way we interact with videos. By utilizing advanced AI algorithms from OpenAI, our application can automatically generate accurate transcripts from videos, saving time and effort. But it doesn't stop there - our application also extracts essential insights, conducts sentiment analysis, and categorizes the content to enhance searchability.
Our journey in CalHacks AI Berkeley hackathon led us to leverage the GPT-4 model from OpenAI to analyze and interpret video content. We developed a backend using FastAPI and connected it with a frontend built using React. The backend processes the video, extracts audio, and sends it to the OpenAI model for analysis and transcription.
Our primary challenge was handling the huge video files efficiently and dealing with varying video and audio codecs. Learning how to best utilize the GPT-4 model for our specific use case was also a hurdle that we had to overcome.
We are incredibly proud of developing a fully functional application in such a short time span. The fact that our application can make video content more accessible and searchable is a significant accomplishment for us.
Throughout this hackathon, we learned a great deal about video processing, transcription, and the power of AI in data analysis. We also learned about teamwork and the importance of communication in a fast-paced, challenging environment.
In future iterations, we plan to refine our model and improve the efficiency of video processing. We also aim to incorporate additional features like real-time video analysis, multiple language support, and improved search functionality. We are excited to see the potential impact of our project on academia, businesses, and content creation.
We extend our heartfelt gratitude to CalHacks AI Berkeley hackathon, our mentors, and fellow participants who helped us shape this project. This event has truly been a platform for growth, learning, and innovation.
Built with passion and lots of coffee by Tony Astuhuaman, Zhi Zhang, Yinfeng Xu for CalHacks AI Berkeley hackathon 2023.