lucid-dl/yolo-v4

YOLOv4 (CSPDarknet-53 + SPP + PAN)

Bochkovskiy, Wang & Liao, 2020 — YOLOv4: Optimal Speed and Accuracy of Object Detection (arXiv:2004.10934)

Lucid port of darknet/yolov4.weights, converted to Lucid-native safetensors.

Available weights

Tag	mAP@0.5	Params	GFLOPs	Size	Source
COCO_2017 (default)	65.7	64.4M	—	245.85 MB	darknet

Usage

import lucid.models as models
from lucid.models.weights import YOLOV4Weights

# default tag
model = models.yolo_v4(pretrained=True)

# explicit tag (enum or string)
model = models.yolo_v4(weights=YOLOV4Weights.COCO_2017)
model = models.yolo_v4(pretrained="COCO_2017")

# preprocessing travels with the weights
weights = YOLOV4Weights.COCO_2017
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/yolov4.weights via python -m tools.convert_weights yolo_v4 --tag COCO_2017. Key mapping + numerical parity verified against the source.

License

other — inherited from the original weights.

Citation

@article{bochkovskiy2020yolov4,
  title={YOLOv4: Optimal Speed and Accuracy of Object Detection},
  author={Bochkovskiy, Alexey and Wang, Chien-Yao and Liao, Hong-Yuan Mark},
  journal={arXiv preprint arXiv:2004.10934},
  year={2020}
}