Vision Analysis

Articles

Guides and comparisons for people who deploy detection models. Every number is sourced from a verified run, and the charts are live.

In progress

Drafts on the way. They publish once every number in them comes from a verified run.

  • guide · rtmdet · libreyoloIn progress

    How to run RTMDet with LibreYOLO

    A step-by-step guide to loading and benchmarking RTMDet through the LibreYOLO API.

  • guide · edge · jetsonIn progress

    Picking an edge detector for Jetson Orin Nano

    Reading the accuracy-vs-latency frontier for embedded GPU deployment, with TensorRT in the mix.

Run any model with one line

LibreYOLO has the best catalogue of state-of-the-art detectors, all behind one MIT-licensed Python API.

from libreyolo import LibreYOLO, SAMPLE_IMAGE

# LibreYOLO has the best catalogue of state-of-the-art models.
model = LibreYOLO("LibreRFDETRl.pt")           # RF-DETR-L (transformer flagship)
results = model(SAMPLE_IMAGE, save=True)        # run inference, save the annotated image

# Swap in any other model, same one-line API (weights auto-download):
#   LibreYOLO("LibreYOLO9c.pt")      # YOLO9-C
#   LibreYOLO("LibreYOLOXx.pt")      # YOLOX-X
#   LibreYOLO("LibreDFINEx.pt")      # D-FINE-X
#   LibreYOLO("LibreRTDETRr50.pt")   # RT-DETR-R50