---
pipeline_tag: object-detection
tags:
- ultralytics
- yolo
- yolov8
- tracking
- image-classification
- obb
- object-detection
language:
- hy
datasets:
- armvectores/handwritten_text_detection
---
# YOLOv8 Handwritten Text Detection
## Model Description
YOLOv8 is the eighth version of the You Only Look Once (YOLO) object detection algorithm. It excels in speed and accuracy, making it an ideal choice for real-time applications. The YOLOv8 model provided here has been fine-tuned on a diverse dataset of handwritten texts to improve its specificity in detecting handwritten content as opposed to typed or printed materials.
## How to use
```
pip install ultralytics
```
```
from ultralytics import YOLO
from huggingface_hub import hf_hub_download
from matplotlib import pyplot as plt
# Load the weights from our repository
model_path = hf_hub_download(local_dir=".",
repo_id="armvectores/yolov8n_handwritten_text_detection",
filename="best.pt")
model = YOLO(model_path)
# Load test blank
test_blank_path = hf_hub_download(local_dir=".",
repo_id="armvectores/yolov8n_handwritten_text_detection",
filename="test_blank.png")
# Do the predictions
res = model.predict(source=test_blank_path, project='.',name='detected', exist_ok=True, save=True, show=False, show_labels=False, show_conf=False, conf=0.5, )
plt.figure(figsize=(15,10))
plt.imshow(plt.imread('detected/test_blank.png'))
plt.show()
```
## Tests
## Metrics
The final IoU=0.98
The IoU during training
