---
tags:
- yolov5
- yolo
- vision
- object-detection
- pytorch
license: mit
base_model:
- Ultralytics/YOLOv5
---

# Model Card for BillboardAdvertDetectionYOLOV5
<img src="img/image_collage.png" />


Computer vision object detection model to detect billboard advertising.

This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).

## Model Details

### Model Description

As the adoption of augmented reality (AR) headsets proliferates, the ways in which consumers will experience content will change considerably, which means a radical shift away from the current state of billboard advertising.

This is to show how to create a computer vision model for applications such as ad-blocking in everyday life.

- **Developed by:** Lewis James 
- **Model type:** Computer Vision
- **Transfer learning from model YOLOv5:** [Hugging Face](https://huggingface.co/Ultralytics/YOLOv5)

### Model Sources

- **Repository:** [GitHub](https://github.com/lewisExternal/BillboardAdvertDetection)
- **Blog:** [Medium](https://medium.com/@ljamesdatascience/billboard-advert-detection-using-transfer-learning-with-yolo-9405d6aeb943)

### Results 
| Class | Images | Instances | P     | R     | mAP50 |
| :---: | :----: | :-------: | :---: | :---: | :---: |
| all   |   71   | 99        | 0.805 | 0.828 | 0.818 | 


## Model Card Contact

Connect with me via [LinkedIn](https://www.linkedin.com/in/lewisjames1/)