| name | quickstart |
| description | Guided quickstart for FiftyOne - choose between user workflows (import, inference, visualization) or developer workflows (plugin development) |
FiftyOne Quickstart
Welcome to FiftyOne! This quickstart will guide you through your first workflow.
Prerequisites Check
First, let me verify your setup by listing available datasets:
Use the list_datasets MCP tool to check the connection.
If this fails, run:
pip install fiftyone-mcp-server
Then check /fiftyone:help for environment configuration.
Choose Your Path
Option 1: User Quickstart
Build and explore a computer vision dataset.
Step 1: Load a Dataset
You can either:
-
Use the quickstart dataset (built-in):
Load the FiftyOne quickstart dataset
-
Import your own dataset:
Use /fiftyone:fiftyone-dataset-import to import my dataset from /path/to/data
-
Import from Hugging Face Hub:
Use /fiftyone:fiftyone-dataset-import to import the dataset from huggingface.co/datasets/username/dataset-name
Step 2: Run Model Inference
Apply a model to your dataset:
Use /fiftyone:fiftyone-dataset-inference to run object detection on my dataset
This will run a Zoo model (like YOLO or Faster R-CNN) and add predictions to your samples.
Step 3: Explore in the App
Launch the FiftyOne App to visualize your data and predictions:
Launch the FiftyOne App with my dataset
From here you can:
- Browse samples and labels
- Filter by predictions or ground truth
- Identify model errors
Next Steps
Once you're comfortable, try:
/fiftyone:fiftyone-find-duplicates - Clean your dataset/fiftyone:fiftyone-model-evaluation - Evaluate prediction quality/fiftyone:fiftyone-embeddings-visualization - Explore data distribution/fiftyone:fiftyone-create-notebook - Generate a full ML pipeline notebook
Option 2: Developer Quickstart
Create a custom FiftyOne plugin.
Step 1: Start Plugin Development
Use /fiftyone:fiftyone-develop-plugin to create a new plugin
The skill will guide you through:
- Defining your plugin's purpose
- Choosing between operators (actions) or panels (UI)
- Generating the plugin structure
- Installing and testing locally
Step 2: Follow the Guided Workflow
The develop-plugin skill provides comprehensive guidance on:
- Plugin directory structure
- Python operator patterns
- JavaScript/React panels
- Hybrid plugins with Python backend + JS frontend
- Testing and debugging
Next Steps
For code contributions:
Need Help?
