testing SAM3 for computer vision tracking and segmentation pretty insane model, very quick and accurate, uses natural language prompts to identify objects

Open vocabulary text prompting with SAM 3 in images and videos opens up tons of use cases! Here are some examples of the types of prompts you can use! 🧵

SAM 3D is helping advance the future of rehabilitation. See how researchers at Carnegie Mellon University are using SAM 3D to capture and analyze human movement in clinical settings, opening the doors to personalized, data-driven insights in the recovery process. 🔗 Learn more about SAM

MedSAM3: Segment Anything with Medical Concepts A new framework for text-promptable medical segmentation (PCS). It adapts SAM3 with medical concepts for diverse modalities (X-ray, MRI, CT, video), outperforming existing models & simplifying anatomical targeting.

Encouraging to see medical applications of SAM 3 in just 1 week. We didn't prioritize medical use cases, so works like the MedSAM series that add real clinical data and knowledge are especially valuable. Medicine & science uses for SAM remain some of the most rewarding to see 🩺

why you should open-source your scientific work, it always goes like this ⬇️

SAM 3 is not a referring expression segmentation model - this is by design. SAM 3 solves Promptable Concept Segmentation (PCS): segmenting objects using simple noun phrases (general categories + basic attributes) and optional exemplars. It's also a robust, composable primitive

A call to all the hackers out there, if you make the WebCodecs API work on Node.js before the end of the year, you can win 💵 $10k 💵! Video editing on the web has so much potential with AI and Edge Compute, we finally have the API with WebCodecs, now we need it on the server!

🏀 Object Tracking Made Easy with SAM 3! With just a simple text prompt like “player”, you can now segment and track objects throughout an entire video using SAM 3. Easily customize object names, isolate specific players, or remove unwanted objects. GitHub:

🚀 Why SAM‑3 Is a Game‑Changer in Computer Vision Everyone’s talking about Meta’s Segment Anything Model (SAM) - but few realize how different SAM‑1, SAM‑2, and SAM‑3 truly are. ✨ SAM‑1: The breakthrough - point at anything in an image and instantly cut it out. 🎥 SAM‑2: Took

🚀 Why SAM‑3 Is a Game‑Changer in Computer Vision Everyone’s talking about Meta’s Segment Anything Model (SAM) - but few realize how different SAM‑1, SAM‑2, and SAM‑3 truly are. ✨ SAM‑1: The breakthrough - point at anything in an image and instantly cut it out. 🎥 SAM‑2: Took

🚨 SAM 3D is now live on fal! 🎯 Reconstruct full 3D shape geometry, texture, and layout from a single image 🎨 Convert objects in images into 3D models with pose ✨ Excels in real-world scenarios with occlusion and clutter ⚡ Fast 3D generation with superior results

The new SAM3 model from Meta is blowing my mind Shown here: detecting putting greens, pools, and cars in Scottsdale from simple text prompts via Mapbox imagery R, Shiny, mapgl for the UI; Python backend via Qiusheng Wu's segment-geospatial package (thanks Qiusheng!)

data labeling is dead. long live distillation. from data to object detection endpoint in 90 seconds. link: rapid.roboflow.com

Today's update on the upcoming R interface to Meta's SAM3: We'll have a Shiny gadget that allows you to interactively explore and segment imagery. Shown here in Positron: finding red cars in a parking lot at TCU, which are returned to your R session as an sf object.

i trained a computer vision model to detect football players, the ball, net, and goals scored using roboflow rapid, SAM3, and a python script this took me 2 hours and could be taken much further to create a sports analytics + tracking app and now let's enjoy Pirlo's panenka

Tested Meta's SAM 3 on some low quality dashcam footage and expected the segmentation to fall apart, but it still picked up every vehicle and even spotted people on the roadside that I hadn't noticed at all.

New tutorial | Text-prompt segmentation with AI at Meta SAM3 ✨ Learn how to segment objects in images and videos using single or multiple text prompts with SAM3. Watch here ➡️ bit.ly/48UI16s #SAM3 #SegmentAnything #Ultralytics

This definitely ranks up there in my list of favorite SAM 3 applications!