Accelerate Image Annotation with SAM and Grounding DINO | Python Tutorial

Description:

In this comprehensive tutorial, discover how to speed up your image annotation process using Grounding DINO and Segment Anything Model (SAM). Learn how to convert object detection datasets into instance segmentation datasets, and see the potential of using these models to automatically annotate your datasets for real-time detectors like YOLOv8. Stay tuned for the upcoming release of a Python library that will make this process even more effortless.

Chapters:

00:00 Introduction
00:58 Python Environment Setup
04:13 Load Grounding DINO and Segment Anything Models
05:42 Single Image Mask Autoannotation
08:24 Full Dataset Mask Autoannotation
09:58 Save Labels to Pascal VOC XML
14:17 Upload Annotations to Roboflow
15:23 Review and Refine Annotations in Roboflow UI
17:11 Convert Object Detection to Instance Segmentation Dataset
22:35 Conclusions
23:28 Announcement

Resources:

🌏 Roboflow: https://roboflow.com
🌌 Roboflow Universe: https://universe.roboflow.com

📓 Automated Dataset Annotation and Evaluation with Grounding DINO and SAM notebook: https://colab.research.google.com/git...
📚 Grounding DINO blog post: https://blog.roboflow.com/grounding-d...
🎬 Detect Anything You Want with Grounding DINO | Zero-Shot Object Detection SOTA video:    • Detect Anything You Want with Groundi...  
📚 How to Use the Segment Anything Model (SAM) blog post: https://blog.roboflow.com/how-to-use-...
🎬 SAM - Segment Anything Model by Meta AI: Complete Guide | Python Setup & Applications video:    • SAM - Segment Anything Model by Meta ...  

Stay updated with the projects I'm working on at https://github.com/roboflow and https://github.com/SkalskiP! ⭐

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#MetaAI #SegmentAnythingModel #SAM #ImageSegmentation #Python #FoundationModels #ComputerVision #ZeroShot #GroundingDINO #ObjectDetection #DataLabeling