lucid-dl/yolo-v3

YOLOv3 (Darknet-53)

Redmon & Farhadi, 2018 — YOLOv3: An Incremental Improvement (arXiv:1804.02767)

Lucid port of darknet/yolov3.weights, converted to Lucid-native safetensors.

Available weights

Tag	mAP@0.5	Params	GFLOPs	Size	Source
COCO_2014 (default)	55.3	61.9M	—	236.57 MB	darknet

Usage

import lucid.models as models
from lucid.models.weights import YOLOV3Weights

# default tag
model = models.yolo_v3(pretrained=True)

# explicit tag (enum or string)
model = models.yolo_v3(weights=YOLOV3Weights.COCO_2014)
model = models.yolo_v3(pretrained="COCO_2014")

# preprocessing travels with the weights
weights = YOLOV3Weights.COCO_2014
preprocess = weights.transforms()
out = model(preprocess(image)[None])
# ObjectDetectionOutput: per-query/proposal class logits + boxes
logits, boxes = out.logits, out.pred_boxes

Conversion

Converted from darknet/yolov3.weights via python -m tools.convert_weights yolo_v3 --tag COCO_2014. Key mapping + numerical parity verified against the source.

License

other — inherited from the original weights.

Citation

@article{redmon2018yolov3,
  title={YOLOv3: An Incremental Improvement},
  author={Redmon, Joseph and Farhadi, Ali},
  journal={arXiv preprint arXiv:1804.02767},
  year={2018}
}