Yeah to speed up media I/O. The thing is that you're feeding Yolo frame per frame. That's not ideal because you have to reimplement streaming and batching into Yolo. Here's an example of what you can do: https://docs.ultralytics.com/modes/predict/#__tabbed_2_13
That's giving more control to Yolo as to when it pulls frames and how it processes them. In the Colab example you can't do this.
I get this error: "No server set for the cv2 frontend. Set VF_IGNI_ENDPOINT and VF_IGNI_API_KEY environment variables or use cv2.set_server() before use."
I tried to use set_server but I'm not sure what argument it needs.
That's giving more control to Yolo as to when it pulls frames and how it processes them. In the Colab example you can't do this.
I get this error: "No server set for the cv2 frontend. Set VF_IGNI_ENDPOINT and VF_IGNI_API_KEY environment variables or use cv2.set_server() before use."
I tried to use set_server but I'm not sure what argument it needs.