RectLabel
An offline image annotation tool for object detection and segmentation.
To download RectLabel apps.
Post the problem to our Github issues.
Have questions? Send an email to support@rectlabel.com.
How to Train a YOLO26 Classification Model with Custom Data
We will show you how to train a YOLO26 classification model with your images and annotations and export to a Core ML model which can be used for auto labeling on RectLabel.
We recommend working through this blog post side-by-side with the YOLO26 Object Classification Colab notebook.
Install YOLO26.
pip install -q ultralytics
Download training images and annotations. You can use these or replace them with your own data.
wget -q https://huggingface.co/datasets/rectlabel/datasets/resolve/main/converse_vans_classification.zip
unzip -q converse_vans_classification.zip
Fine-tune YOLO26 on custom dataset.
yolo classify train data=converse_vans_classification model=yolo26n-cls.pt epochs=100
Move the best model to the current folder and export to a Core ML model.
mv runs/classify/train/weights/best.pt .
yolo export model=best.pt format=coreml
Now you can auto label using the Core ML model on RectLabel.