readme: ---
  license: gpl-3.0
  tags:
  - object-detection
  - computer-vision
  - yolor
  - yolov4
  datasets:
  - detection-datasets/coco
  language:
  - en
  pipeline_tag: object-detection
  library_name: yolor
  library_version: 0.0.3
  ---
  
  ### Model Description
  [YOLOR:](https://arxiv.org/abs/2105.04206)  You Only Learn One Representation: Unified Network for Multiple Tasks.
  
  [YOLOR-Pip:](https://github.com/kadirnar/yolor-pip/) Packaged version of the YOLOR repository
  
  [Paper Repo:](https://github.com/WongKinYiu/yolor/) Implementation of paper - YOLOR
  
  ### Installation
  ```
  pip install yolor
  ```
  
  ### Yolov6 Inference
  ```python
  from yolor.helpers import Yolor
  
  model = Yolor(
    cfg='yolor/cfg/yolor_w6.cfg',
    weights='kadirnar/yolor-w6',
    imgsz=640,
    device='cuda:0'
  )
  
  model.classes = None
  model.conf = 0.25
  model.iou_ = 0.45
  model.show = False
  model.save = True
  
  model.predict('yolor/data/highway.jpg')
  ```
  
  ### BibTeX Entry and Citation Info
   ```
  @article{wang2021you,
    title={You Only Learn One Representation: Unified Network for Multiple Tasks},
    author={Wang, Chien-Yao and Yeh, I-Hau and Liao, Hong-Yuan Mark},
    journal={arXiv preprint arXiv:2105.04206},
    year={2021}
  }
  ```