SSD

Install

SSD needs no optional extra. Everything it imports is in the base install.

pip install libreyolo

Predict

Weights download from Hugging Face on first use and are cached locally.

from libreyolo import LibreYOLO, SAMPLE_IMAGE model = LibreYOLO("LibreSSD300.pt")result = model(SAMPLE_IMAGE, save=True) for box in result.boxes:    print(box.cls, box.conf, box.xyxy)

libreyolo predict model=LibreSSD300.pt source=https://raw.githubusercontent.com/LibreYOLO/libreyolo/release/libreyolo/assets/parkour.jpg save=True

The returned Results object is the one every family returns, so swapping in a different detector is a one line change. SSD decodes its default-box grid with per-class scores and then runs non-maximum suppression, so conf, iou and max_det all have a real effect here, unlike the query-based detectors in this library. See prediction for sources, streaming and result handling.

Variants

SSD ships one checkpoint: the VGG16-backed SSD300 network at its fixed native canvas. There is no size or scale choice in this family; predict, validate and export all use that one graph.

Validate

val() returns a dictionary of metrics/ keys covering precision, recall, mAP 50 and mAP 50-95, measured against any dataset in the format you trained on.

from libreyolo import LibreYOLO model = LibreYOLO("LibreSSD300.pt")metrics = model.val(data="my-dataset.yaml") print(metrics["metrics/mAP50-95"])print(metrics["metrics/mAP50"])

libreyolo val model=LibreSSD300.pt data=my-dataset.yaml

Export

SSD exports to ONNX only; every other format is currently blocked for this family. Export always uses the checkpoint's native canvas, and the graph exposes SSD's raw packed head rather than a fused non-maximum-suppression output, so nms=True is not accepted at export time. LibreYOLO's own backends run the decode and suppression step after loading the graph back.

from libreyolo import LibreYOLO model = LibreYOLO("LibreSSD300.pt") # imgsz is left out here on purpose: SSD300 traces at its checkpoint's# native canvas, and any other value raises before export starts.model.export(format="onnx")

libreyolo export model=LibreSSD300.pt format=onnx

from libreyolo import LibreYOLO # The factory routes on the file suffix, so an exported artifact loads# like any checkpoint and returns the same Results object.model = LibreYOLO("LibreSSD300.onnx")result = model(SAMPLE_IMAGE) print(result.boxes.xyxy)

Checkpoints

Every published weight file for this family.

Licensing

Citation

@inproceedings{liu2016ssd,
  title = {{SSD}: Single Shot MultiBox Detector},
  author = {Liu, Wei and Anguelov, Dragomir and Erhan, Dumitru and Szegedy, Christian and Reed, Scott and Fu, Cheng-Yang and Berg, Alexander C.},
  booktitle = {ECCV},
  year = {2016}
}