Roboflow + Supervisely
Export a Supervisely project and upload it to Roboflow to train, compare and deploy models on the same labels.
How to connect Supervisely to Roboflow
4 stepsExport the project from Supervisely
Open the project's three-dot menu, choose Download, then Export in Supervisely Format. Supervisely builds the archive and gives you a download link on the Tasks page.
Create a Roboflow project
Choose object detection for rectangles or instance segmentation for polygons.
Upload the archive
Drag the downloaded archive or its extracted folder 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 Supervisely
Convert Supervisely labels to YOLO
Upload Supervisely JSON and export the dataset in a YOLO format for training elsewhere.
Train and deploy outside Supervisely
Bring the labels into Roboflow and deploy the trained model on the Hosted API or your own hardware.
Questions
Supervisely Format keeps everything Supervisely supports and Roboflow reads it directly. COCO and Pascal VOC exports also work.
Roboflow's Supervisely support is for image annotations. Export video as frames or label it in Roboflow.
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.
