Summary: What You’ve Learned#

Congratulations! You’ve completed the Segmentation Guide. Let’s recap what you’ve accomplished and explore where you can go next.

Step-by-Step Recap#

Step 1: Loading Segmentation Datasets

You learned how to load segmentation datasets into FiftyOne using both built-in datasets from the zoo and custom datasets in COCO or mask folder format. You mastered the concept of dataset ingestion and how to properly configure different segmentation formats for optimal visualization and analysis.

Step 2: Adding Instance Segmentations

You explored how to add instance segmentation predictions to your datasets using both pre-trained models like SAM2 and your own models, including how to convert polygons and bounding boxes into masks. You learned the fundamentals of model integration and prediction management in FiftyOne.

Step 3: Segment Anything 2 (SAM2) in FiftyOne

You dove into the advanced image and video segmentation capabilities of SAM 2, including prompting via bounding boxes or keypoints, and automatic segmentation for visual AI workflows. You discovered how to leverage cutting-edge segmentation models for zero-shot and prompted segmentation tasks.

Suggested Exercises#

  1. Multi-Format Dataset Loading: Try loading different segmentation dataset formats (VOC, YOLO, custom) and compare how FiftyOne handles each format.

  2. Custom Model Integration: Implement your own segmentation model and integrate it with FiftyOne’s prediction pipeline.

  3. Advanced SAM2 Prompting: Experiment with different prompt types (text, keypoints, multiple bounding boxes) to see how SAM2 responds.

  4. Video Segmentation: Work with video datasets and explore SAM2’s video mask propagation capabilities.

  5. Dataset Curation: Use FiftyOne’s filtering and search capabilities to identify specific segmentation patterns or failure cases in your dataset.

Resources and Further Reading#

What to Do Next#

Now that you’ve mastered segmentation with FiftyOne, here are some suggested next steps:

  • Explore Model Evaluation - Learn how to evaluate segmentation models by comparing predictions against ground truth, and identifying failure cases in your dataset

  • Try Out FiftyOne Plugins - Extend your workflow with powerful plugins like video embeddings, active learning tools, and integrations with annotation platforms

  • Build Custom Workflows - Create domain-specific workflows for your particular segmentation use case (medical imaging, autonomous driving, retail analytics, etc.)

  • Join the Community - Connect with other FiftyOne users to share insights and learn advanced segmentation techniques

  • Apply to Real Projects - Use these skills on your production segmentation datasets to improve data quality and model performance

  • Explore Other Computer Vision Tasks - Branch out into object detection, classification, or tracking workflows using FiftyOne

We’d Love Your Feedback#

Your feedback helps us improve FiftyOne and create better learning experiences. Please let us know:

  • What aspects of this segmentation guide were most helpful?

  • What could be improved or clarified?

  • What segmentation-specific topics would you like to see covered in future guides?

  • Any issues or bugs you encountered?

You can reach us at support@voxel51.com or join our Discord community.

Thank you for completing the Segmentation Guide! We hope you’re excited to apply these segmentation skills to improve computer vision AI and research.