| name | roboflow-data-management |
| description | Use when uploading images, labeling, organizing datasets, creating Roboflow projects (detection/segmentation/keypoint/classification), tags, splits, versions, or RoboQL search. |
For agents — source-of-truth: This skill is authored in roboflow/computer-vision-skills and shipped with the Roboflow plugin. If your client has loaded the plugin (you'll see roboflow:<name> skills in your available skills list), use those local skills — they're read fresh from disk every session. The same content served as MCP resources at roboflow://skills/<name>/... is a fallback for clients without the plugin and may lag this repo. Don't call ReadMcpResourceTool for roboflow://skills/... URIs when a local roboflow:<name> skill is available.
Data Management on Roboflow
Project Types
| Type | Annotation Format | Use Case |
|---|
| Object Detection | Bounding box (polygon/mask auto-converted) | Locate objects with boxes |
| Instance Segmentation | Polygon, Mask | Pixel-level per-object boundaries |
| Semantic Segmentation | Polygon, Mask | Pixel-level class regions |
| Keypoint Detection | Keypoints (skeleton) | Pose/skeleton estimation |
| Single-Label Classification | Image-level label (no drawn annotations) | One class per image |
| Multi-Label Classification | Image-level labels | Multiple classes per image |
Project type is set at creation and cannot be changed later.
Uploading Data
Methods
| Method | Best For | Formats |
|---|
| Web UI drag-and-drop | < 1,000 images | JPG, PNG, WEBP, AVIF, BMP, MOV, MP4, PDF + 40+ annotation formats |
CLI (roboflow import) | > 1,000 images (images only) | Same image formats, no video |
| Cloud storage bucket mirror | Extensive or continuously-growing data already in S3 / GCS | See roboflow://skills/cloud-storage/SKILL |
| Dataset Upload Workflow Block | Collecting from production Workflows | Programmatic |
| Universe fork | Starting from a public dataset | Any Universe dataset |
Limits: Max 20 MB per image, max 16,400 x 10,900 px. Duplicate images are skipped automatically.
Video Upload
Videos are split into frames at a configurable rate (1 frame/60s to 60 fps). Supported formats depend on browser (MP4 H.264 most compatible).
CLI Upload
pip install roboflow
roboflow import -w <workspace> -p <project-id> /path/to/dataset
Tags
Tags are free-form labels on images for organization and filtering.
| Action | How |
|---|
| Add during upload | Tag selector in upload dialog or via API |
| Add to existing images | Select images -> "Images Selected" -> "Apply tags" |
| Rename/delete in bulk | Project Settings -> Tags -> "Modify Tags" |
| Filter by tag | Search with tag:<name> or use Assign page filter |
| Use in versions | "Filter by Tag" preprocessing step (require/exclude/allow) |
Dataset Search (RoboQL)
Search images via the Images page search bar. Combine filters with boolean logic.
Filters
| Filter | Example | Description |
|---|
| (free text) | person on sidewalk | Semantic search (CLIP-based) |
like-image:<ID> | like-image:abc123 | Find visually similar images |
filename: | filename:*factory* | Filename match (* for partial) |
tag: | tag:factory | Filter by tag |
split: | split:train | Filter by split |
job: | job:<JOB_ID> | Filter by annotation job |
class: | class:helmet | Has annotation with class |
metadata: | metadata:key=value | Filter by user metadata |
project: | project:my-project | Filter by project (workspace search) |
sort: | sort:updated | Sort results |
min-width: / max-width: | min-width:1000 | Image dimension filters |
min-height: / max-height: | max-height:800 | Image dimension filters |
min-annotations: / max-annotations: | max-annotations:1 | Annotation count filters |
Boolean Logic
AND, OR, NOT, parentheses: class:helmet AND NOT (tag:v1 OR tag:v2)- Inverted filter with
-: -class:vest
- Comparison operators on numeric filters:
>, <, >=, <=, = (e.g., class:helmet>=3)
Splits (Train / Valid / Test)
Images are assigned to train, valid, or test splits. Splits are rebalanced during version generation (Step 2 in version creation). Augmentations only apply to train split.
Dataset Versions
A version is a frozen snapshot of the dataset at a point in time. Changes to the project after version creation do not affect existing versions.
Version Creation Pipeline
- Source selection — images from the dataset split
- Train/Test split — rebalance percentages
- Preprocessing — applied to all splits (train + valid + test)
- Augmentation — applied only to train split
- Generate — creates immutable version
Preprocessing Options
| Step | Effect |
|---|
| Auto-Orient | Strips EXIF, normalizes orientation |
| Resize | Stretch to / Fit within / Fit (black edges) / Fit (white edges) |
| Grayscale | Convert RGB to single channel |
| Auto-Adjust Contrast | Contrast Stretching / Histogram Equalization / Adaptive (CLAHE) |
| Isolate Objects | Crop each bbox into separate image (converts OD to classification) |
| Static Crop | Crop all images to fixed region |
| Tile | Split images into NxN grid (default 2x2, helps small object detection) |
| Dynamic Crop | Crop images around a specific class |
| Modify Classes | Remap/omit classes for this version only |
| Filter Null | Control percentage of unannotated images |
| Filter by Tag | Require / Exclude / Allow images by tag |
| Random Sample | Sample a percentage of images per split |
Augmentation Options
Applied to train images only. Configurable max version size (e.g., 3x = source + 2 augmented copies).
| Augmentation | Image Level | BBox Level | Tier |
|---|
| Flip | yes | yes | Basic |
| 90 deg Rotate | yes | yes | Basic |
| Crop | yes | yes | Basic |
| Rotation | yes | yes | Basic |
| Shear | yes | yes | Basic |
| Grayscale | yes | no | Basic |
| Hue | yes | no | Basic |
| Saturation | yes | no | Basic |
| Brightness | yes | yes | Basic |
| Exposure | yes | yes | Basic |
| Blur | yes | yes | Basic |
| Noise | yes | yes | Basic |
| Camera Gain | yes | yes | Basic |
| Motion Blur | yes | yes | Basic |
| Cutout | yes | no | Enhanced (paid) |
| Mosaic | yes | no | Enhanced (paid) |
Dataset Analytics
Available at project sidebar -> "Analytics". Shows:
- Image count, annotation count, avg image size, median aspect ratio
- Missing and null annotation counts
- Class distribution across train/valid/test
- Image dimension insights (size + aspect ratio distribution)
- Annotation heatmap (click-drag to filter images by region)
- Object count histogram (click bars to see matching images)
Classes
Managed at Project Settings -> Classes.
| Action | Description |
|---|
| Rename | Type new name in Override column |
| Merge | Override multiple classes to same name |
| Delete | Check Delete checkbox |
| Lock | "Lock Annotation Classes" prevents new class creation |
Warning: Class changes at project level affect all images (irreversible). Use version-level "Modify Classes" preprocessing for non-destructive changes.
Annotation Groups
Annotation group = the category encompassing all classes in a project. Projects sharing the same annotation group share their class list and annotations.
- Enable during project creation: "Share image annotations with other projects"
- Shared annotations: editing in one project affects all linked projects
- Look for chain-link icon to identify shared images/projects
- Images shared across projects count only once toward usage
Project Folders
Folders group projects for organization. SSO workspaces can restrict folder access to specific team members.
| Action | How |
|---|
| Create | "+ New Folder" from workspace view |
| Move project | Project menu -> "Move Project" |
| Delete folder | Folder menu -> "Delete" (projects move to workspace root, not deleted) |
Export Formats
Versions can be exported as .zip download or curl command. 40+ formats supported including COCO, YOLO, Pascal VOC, TFRecord, and more. Full list at roboflow.com/formats.
Export via Python SDK:
project.version(1).download("yolov8")
MCP apps vs plain tools
Prefab MCP apps (create_project_app) exist when parameters are unclear, you need real UX, or a human must confirm after seeing form fields — plain chat/MCP calls should not guess project type and license alone.
MCP Tools Available
| Tool | Purpose |
|---|
projects_create | Create a new project (specify type, annotation group) |
projects_list / projects_get | List or get project details |
images_search | Search images using RoboQL filters |
image_upload / image_upload_status | Prepare zip image upload and poll status |
versions_generate | Generate a dataset version with preprocessing/augmentation |
versions_get | Inspect a version |
versions_export | Export a version in a given format |
Related Pages
roboflow://skills/data-management/labeling — annotation tools, AI labeling, Label Assist, Smart Polygon, Auto Label, annotation jobsroboflow://skills/cloud-storage/SKILL — mirror an S3/GCS bucket into the workspace (credentials, datasources, glob rules, scheduled sync)
