Roboflow + LabelMe
Upload LabelMe JSON files with your images to Roboflow to train detection and segmentation models on your polygons and boxes.
How to connect LabelMe to Roboflow
4 stepsSave your annotations in LabelMe
Label each image and save. LabelMe writes a JSON file with the same name as the image.
Create a Roboflow project
Choose instance segmentation if you drew polygons, or object detection if you drew rectangles.
Upload the folder
Drag the folder with your images and LabelMe JSON files onto the upload page.
Generate a version and train
Generate a dataset version with preprocessing and augmentation, then train a model such as RF-DETR.
What teams build with LabelMe
Train a segmentation model on LabelMe polygons
Upload polygon labels and train an instance segmentation model without converting them to COCO yourself.
Convert LabelMe JSON to COCO or YOLO
Export the same dataset from Roboflow in the format another training pipeline expects.
Questions
No. Roboflow reads LabelMe JSON as it is, and can export the dataset as COCO JSON afterwards.
Pick instance segmentation for polygon labels and object detection for rectangles.
Yes. Roboflow Annotate supports boxes and polygons and adds Label Assist for model-assisted labeling.
Why are companies choosing Roboflow?
The end-to-end platform for vision AI: create datasets, train models and deploy to production.
Flexible deployment modes
Move from a scalable cloud API to edge hardware like NVIDIA Jetson without managing complex dependencies.
Integrated workflow builder
Combine multiple AI models, custom business logic and third-party integrations into one production-ready pipeline in a low-code editor.
Model monitoring and alerts
Dashboards track confidence, inference time and request volume for your deployed models, and email alerts tell your team when confidence suddenly drops.
