metadata
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
# 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
model.predict(source=test_blank, save=True, show=True, show_labels=False, show_conf=False, conf=0.3)
Tests
Metrics
The final IoU=0.98
The IoU during training