The video provides a detailed tutorial on using the new Sora 2 API for video generation, covering basic video creation, image-to-video animation, advanced prompting with the Pro model, remixing videos, and multi-shot sequencing—all demonstrated through practical Python code examples. It emphasizes building automated video pipelines, handling challenges like moderation filters and processing delays, and encourages experimentation with the API via the GitHub repository.
The video provides a comprehensive tutorial on how to use the new Sora 2 API for video generation, demonstrating practical steps and prompting techniques to create videos with just a few lines of Python code. Starting from the GitHub repository, the presenter walks through basic video generation, image-to-video conversion, using the pro model, enhanced AI prompting, remixing videos, and multi-shot sequencing. The tutorial emphasizes not just following the API documentation but understanding how to build pipelines to automate video creation effectively.
The initial demonstration shows how to generate a simple video by importing OpenAI’s library, setting the API key, and calling the video creation function with parameters like prompt, model, duration, and video size. The presenter explains how to check the status of video generation, retrieve a list of videos, and download completed videos to an output folder. This process is illustrated with an example of creating a studio setup video, highlighting the time it takes for rendering and how to monitor progress using a polling loop.
Next, the video explores using an image reference to animate a static image, which requires the reference image to match the video resolution exactly. The presenter generates an image using OpenAI’s image API, resizes it with a helper function, and then uses it as a reference to create an animated video. Challenges with moderation filters are discussed, especially when using images containing people, which often trigger restrictions. Despite these limitations, the presenter successfully animates a studio setup image, demonstrating the API’s capabilities.
The tutorial then delves into advanced prompting techniques with the Sora Pro model and a custom “director” class that generates detailed prompts to maintain a consistent visual style, such as Pixar-like animations. Although the pro model currently has some issues with videos getting stuck in the processing state, the presenter shows how to use the director to create rich, descriptive prompts that guide the video generation process. This approach helps automate narrative creation and ensures stylistic coherence across videos.
Finally, the video covers remixing existing videos by referencing previously generated content and applying new prompts to alter elements like color or scene. The presenter demonstrates creating a three-shot sequence to maintain character consistency and build a narrative, though noting that character consistency is not perfect yet. To complete the workflow, a Python script using FFmpeg is shown to stitch multiple video shots into a seamless final video. The video concludes by encouraging viewers to experiment with the Sora 2 API using the provided GitHub repository and invites feedback and questions to improve understanding of this emerging technology.