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Model Description

YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported.

YOLOXDetect-Pip: This repo is a packaged version of the YOLOX for easy installation and use.

[Paper Repo]: Implementation of paper - YOLOX

Installation

pip install yoloxdetect

Yolox Inference

from yoloxdetect import YoloxDetector
from yolox.data.datasets import COCO_CLASSES
model = YoloxDetector(
    model_path = "kadirnar/yolox_m-v0.1.1",
    config_path = "configs.yolox_m",
    device = "cuda:0",
    hf_model=True
)
model.classes = COCO_CLASSES
model.conf = 0.25
model.iou = 0.45
model.show = False
model.save = True
pred = model.predict(image='data/images', img_size=640)

BibTeX Entry and Citation Info

@article{yolox2021,
 title={YOLOX: Exceeding YOLO Series in 2021},
 author={Ge, Zheng and Liu, Songtao and Wang, Feng and Li, Zeming and Sun, Jian},
 journal={arXiv preprint arXiv:2107.08430},
 year={2021}
}
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Dataset used to train kadirnar/yolox_m-v0.1.1

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