Annolid on Google Colab

Annolid on Google Colab#

Google Colab is often the easiest way to run GPU-heavy training or inference (especially for Detectron2 / Mask R-CNN workflows).

Open the official notebook#

  • From the Annolid GUI: File → Open in Colab

  • Or open directly:

Open In Colab

Typical workflow#

  1. On your local machine, label frames in Annolid and export a dataset (COCO or YOLO depending on the notebook/tooling you use).

  2. Upload the dataset to Google Drive (or point the notebook at a GitHub URL if the data is public).

  3. Run training/inference in Colab.

  4. Download the trained weights and use them in Annolid (e.g., “Browse Custom YOLO…” or your Detectron2 model path).

Note

For many tracking tasks you don’t need Colab: you can label one frame and track with Annolid’s built-in tracking backends, then export to CSV for analysis.

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