YOLOv5 / README.md
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---
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}
}
```