readme: ---
  license: gpl-2.0
  datasets:
  - coco
  library_name: stable-baselines3
  tags:
  - seals/CartPole-v0
  - deep-reinforcement-learning
  - reinforcement-learning
  - stable-baselines3
  - object-detection
  model-index:
  - name: PPO
    results:
    - metrics:
      - type: mean_reward
        value: 500.00 +/- 0.00
        name: mean_reward
        verified: True
      task:
        type: reinforcement-learning
        name: reinforcement-learning
      dataset:
        name: seals/CartPole-v0
        type: seals/CartPole-v0
  ---
  
  
  # YOLOv5
  
  Ultralytics YOLOv5 model in Pytorch.  
  
  Proof of concept for (TypoSquatting, Niche Squatting) security flaw on Hugging Face.
  
  
  ## Model Description
  
  
  
  ## How to use
  
  ```python
  from transformers import YolosFeatureExtractor, YolosForObjectDetection
  from PIL import Image
  import requests
  
  url = 'http://images.cocodataset.org/val2017/000000039769.jpg'
  image = Image.open(requests.get(url, stream=True).raw)
  
  feature_extractor = YolosFeatureExtractor.from_pretrained('mhyatt000/yolov5')
  model = YolosForObjectDetection.from_pretrained('mhyatt000/yolov5')
  
  inputs = feature_extractor(images=image, return_tensors="pt")
  outputs = model(**inputs)
  # model predicts bounding boxes and corresponding COCO classes
  
  logits = outputs.logits
  bboxes = outputs.pred_boxes
  ```
  
  ## Training Data
  
  ### Training
  
  ## Evaluation
  
  Model was evaluated on [COCO2017](https://cocodataset.org/#home) dataset.
  
  |   Model	|	size (pixels)	|	mAPval  |   Speed   |   params  |   FLOPS   |
  |---------------|-------------------|-----------|-----------|-----------|-----------|
  | YOLOv5s6	|	    1280       	|	43.3	|	4.3 	| 	12.7	|	17.4    |
  | YOLOv5m6	|	    1280    	|	50.5	|	8.4	    | 	35.9	|	52.4    |
  | YOLOv5l6	|	    1280	    |	53.4	|	12.3	| 	77.2	|	117.7   |
  | YOLOv5x6	|	    1280	    |	54.4	|	22.4	| 	141.8	|	222.9   |
  
  ### Bibtex and citation info
  
  ```bibtex
  @software{glenn_jocher_2022_6222936,
    author       = {Glenn Jocher and
                    Ayush Chaurasia and
                    Alex Stoken and
                    Jirka Borovec and
                    NanoCode012 and
                    Yonghye Kwon and
                    TaoXie and
                    Jiacong Fang and
                    imyhxy and
                    Kalen Michael and
                    Lorna and
                    Abhiram V and
                    Diego Montes and
                    Jebastin Nadar and
                    Laughing and
                    tkianai and
                    yxNONG and
                    Piotr Skalski and
                    Zhiqiang Wang and
                    Adam Hogan and
                    Cristi Fati and
                    Lorenzo Mammana and
                    AlexWang1900 and
                    Deep Patel and
                    Ding Yiwei and
                    Felix You and
                    Jan Hajek and
                    Laurentiu Diaconu and
                    Mai Thanh Minh},
    title        = {{ultralytics/yolov5: v6.1 - TensorRT, TensorFlow 
                     Edge TPU and OpenVINO Export and Inference}},
    month        = feb,
    year         = 2022,
    publisher    = {Zenodo},
    version      = {v6.1},
    doi          = {10.5281/zenodo.6222936},
    url          = {https://doi.org/10.5281/zenodo.6222936}
  }
  ```
  