Built by Metorial, the integration platform for agentic AI.
List all annotation jobs for a project. Returns each job's status, image counts, and progress towards completion. Optionally retrieve detailed information for a specific job by providing a jobId.
Upload an annotation file for a specific image in a project. Supports various annotation formats including YOLO/Darknet, Pascal VOC XML, COCO JSON, and more. The annotation text should match the expected format for the project type.
Run predictions on an image using a trained model deployed on the Roboflow hosted inference API. Provide a publicly accessible image URL or base64-encoded image data. Returns detected objects with bounding boxes, confidence scores, and class labels.
Create a new annotation job for a project. An annotation job assigns images from a batch to a labeler for annotation and a reviewer for quality control. Both must be members of the workspace.
Get detailed information about a specific Roboflow project, including its dataset versions, annotation classes, image splits, and training status. Use the project URL slug as the projectId.
Start training a model on a specific dataset version using Roboflow Train. Training runs asynchronously and typically completes within 24 hours. Once done, the model is automatically deployed to a hosted inference API. Use **Get Version** to monitor training progress and results, and **Stop Training** to end it early.
List all projects in a Roboflow workspace. Returns project metadata including name, type, image counts, annotation classes, and version counts. Useful for discovering available projects and their current state.
Export a dataset version as a downloadable ZIP in a specified annotation format. Supported formats include YOLOv5, COCO JSON, Pascal VOC, TFRecord, and many more.
Get detailed information about a specific image in a project, including its annotations, labels, tags, split assignment, and URLs for the original and thumbnail versions.
Delete one or more images from a Roboflow project. This permanently removes the images and their annotations from the project.
Create a new computer vision project in the workspace. Supports object detection, classification (single and multi-label), instance segmentation, and semantic segmentation project types.
Generate a new versioned snapshot of a project's dataset with optional preprocessing and augmentation settings. The version is generated asynchronously. Use **Get Version** to check generation progress. Preprocessing options include auto-orient, resize, grayscale, static crop, and tile. Augmentation options include flip, rotate, crop, brightness, blur, noise, cutout, mosaic, and more.
Search for images within a project using text prompts, visual similarity to an existing image, or by filtering on tags, classes, and batch assignments. Supports pagination for browsing large datasets.
Upload an image to a Roboflow project. Provide either a publicly accessible image URL or base64-encoded image data. Optionally assign the image to a batch, add tags, or specify the dataset split.
Get detailed information about a specific dataset version, including preprocessing and augmentation settings, training results (mAP, precision, recall), and model endpoint details. Use this to check training progress or model performance.
Add, remove, or set tags on a specific image in a project. Tags are used for organizing and filtering images. Use "add" to append tags, "remove" to delete specific tags, or "set" to replace all existing tags.
List uploaded image batches for a project, including IDs and names to use with create_annotation_job. Call list_projects to discover projects.
Verify the connected credential and return the workspace it belongs to.
Move a project to Trash, hiding it from the workspace and cancelling its in-flight training jobs. Roboflow retains it for 30 days and allows restoration from Trash during that period. Call list_projects to discover projects.
End a model training job on a dataset version before it finishes. Use **stop** to finish early and keep the current model weights, or **cancel** to discard the weights (credits may be refunded if canceled early). Use **Get Version** to confirm the resulting training status.
List trained models in a project, including models trained on dataset versions and standalone models such as Neural Architecture Search children. Returns each model's ID, architecture, training status, source version, and evaluation metrics. Call list_projects to discover projects.