<hr />
<div class="embed-wrapper"><div class="embed-loading"><div class="loadingRow"></div><div class="loadingRow"></div></div><a class="embed-card" href="https://twitter.com/mendezluisjose/status/1691150529408151562?s=20">https://twitter.com/mendezluisjose/status/1691150529408151562?s=20</a></div>
<p> </p>
<h2 id="heading-license-plate-detection-and-text-extraction-with-yolov8-and-easyocr">License Plate Detection and Text Extraction with YoloV8 and EasyOCR</h2>
<p><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1692037755548/352b2e07-7800-46d4-ba5e-01cafea92d2b.png" alt class="image--center mx-auto" /></p>
<p>Using both the <code>COCO Model</code> to detect the vehicles and the <code>License Plate Model</code> to recognize the plate, and then with EasyOCR to extract the info from the cropped plate image.</p>
<h2 id="heading-check-it-out"><strong>Check-it out</strong></h2>
<p>Test the Model by running the <a target="_blank" href="http://app.py"><code>app.py</code></a> file, built with <code>Streamlit</code>.</p>
<p><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1692037848609/ce4cc5f7-7437-4673-83c3-6aa1a0df2af4.png" alt class="image--center mx-auto" /></p>
<h2 id="heading-run"><strong>Run</strong></h2>
<pre><code class="lang-bash">streamlit run app.py
</code></pre>
<h3 id="heading-resources"><strong>Resources:</strong></h3>
<ul>
<li><p>Licenses Plates Dataset: <a target="_blank" href="https://universe.roboflow.com/roboflow-universe-projects/license-plate-recognition-rxg4e/dataset/4">https://universe.roboflow.com/roboflow-universe-projects/license-plate-recognition-rxg4e/dataset/4</a></p>
</li>
<li><p>Code: <a target="_blank" href="https://github.com/mendez-luisjose/License-Plate-Detection-with-YoloV8-and-EasyOCR">https://github.com/mendez-luisjose/License-Plate-Detection-with-YoloV8-and-EasyOCR</a></p>
</li>
</ul>


---

%[https://twitter.com/mendezluisjose/status/1691150529408151562?s=20] 

## License Plate Detection and Text Extraction with YoloV8 and EasyOCR

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1692037755548/352b2e07-7800-46d4-ba5e-01cafea92d2b.png align="center")

Using both the `COCO Model` to detect the vehicles and the `License Plate Model` to recognize the plate, and then with EasyOCR to extract the info from the cropped plate image.

## **Check-it out**

Test the Model by running the [`app.py`](http://app.py) file, built with `Streamlit`.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1692037848609/ce4cc5f7-7437-4673-83c3-6aa1a0df2af4.png align="center")

## **Run**

```bash
streamlit run app.py
```

### **Resources:**

* Licenses Plates Dataset: [https://universe.roboflow.com/roboflow-universe-projects/license-plate-recognition-rxg4e/dataset/4](https://universe.roboflow.com/roboflow-universe-projects/license-plate-recognition-rxg4e/dataset/4)
    
* Code: [https://github.com/mendez-luisjose/License-Plate-Detection-with-YoloV8-and-EasyOCR](https://github.com/mendez-luisjose/License-Plate-Detection-with-YoloV8-and-EasyOCR)

License Plate Detection with YoloV8 and EasyOCR 🚗

License Plate Detection and Text Extraction with YoloV8 and EasyOCR

Check-it out

Resources:

Systems Engineering Student • Aragua University • Machine Learning, Deep Learning, Computer Vision


License Plate Detection with YoloV8 and EasyOCR 🚗

Table of contents

License Plate Detection and Text Extraction with YoloV8 and EasyOCR

Check-it out

Run

Resources: