Instructions to use WARAJA/Tzefa-Line-Segmentation-YOLO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use WARAJA/Tzefa-Line-Segmentation-YOLO with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("WARAJA/Tzefa-Line-Segmentation-YOLO") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Tzefa Line Segmentation Model (YOLO11x-OBB)
Custom-trained oriented bounding box (OBB) model for detecting text lines in handwritten code images.
Architecture
- Model: YOLO11x-OBB (Ultralytics)
- Task: Oriented Bounding Box detection
- Classes: 1 (text_line)
- Input: RGB image (letterboxed to 640x640 internally)
- Output: OBB coordinates per text line, sorted top-to-bottom
Usage
from huggingface_hub import hf_hub_download
from ultralytics import YOLO
weights = hf_hub_download("WARAJA/Tzefa-Line-Segmentation-YOLO", "best.pt")
model = YOLO(weights)
results = model.predict("your_image.png", imgsz=640, conf=0.2, iou=0.2)
Training
- See
training_artifacts/for training curves, confusion matrices, and configuration.
Related
- Downloads last month
- 16