From the source
Enabling smarter sampling and lower-latency video analytics June 26th, 2026 Client-Side Video Decoding Enabling smarter sampling and lower-latency video analytics June 26th, 2026 Client-Side Video Decoding Enabling smarter sampling and lower-latency video analytics Today we're adding a new way to send video to Perceptron Mk1: frame-by-frame video, decoded on the client.
We support this via the video_frames content part in our API.
If you've already sampled frames client-side, you can now pass them directly, instead of encoding them into a clip.
Each frame carries its own timestamp, and the model sees precisely the frames you send.
Why it matters for existing vision pipelines The default way to send video to Mk1 is via a single video_url , which our platform decodes and samples at a dynamic frame rate of up to 2 FPS.
That's the right behavior when you have a file and want the model to figure out what to look at.
But it assumes an encoded video is the starting point.
Often it isn't.
This assumption breaks when: Your frames already exist.
Dataloaders, frame extractors, and camera pipelines emit decoded frames, not containers.
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