Build custom segmentation models with YOLOv8 and SAM! 🚀

Full guide: https://eranfeit.net/segment-anything-tutorial-generate-yolov8-masks-fast/

Watch: https://youtu.be/8cir9HkenEY

#Ultralytics #SegmentAnything #AI

無異 (@taekie)

메타의 SAM(Segment Anything Model)을 시험해 본 결과를 공유. 스포츠 중계 영상에서는 카메라 시점과 줌 변동을 추적해 스트레칭 처리하는 기술이 핵심이라고 설명하며, 관련 예시로 작년 로잔 박윤재 발레리노 영상을 링크함.

https://x.com/taekie/status/2022565770543403222

#meta #segmentanything #computervision #tracking

Review of the QGIS GeoAI plugin

https://videos.qwast-gis.com/w/dMS9CD17L8WEfnmi5AWEJ2

Meta’s SAM 3 is the new AI superpower for visuals. Find & select anything in photos/videos, just by typing, clicking, or dropping an example. No more tedious edits, just instant results.

Check out my fun explainer here:
https://techglimmer.io/meta-segment-anything-model-3-sam3-explained/

#Meta #AI #SegmentAnything #Sam3 #PhotoEditing

Meta’s latest SAM 3 model shows promise but stumbles on niche technical terms and complex logical prompts. While its zero‑shot abilities shine on general images, medical‑imaging tasks and 3‑D segmentation still lag behind Llama and Gemini. Find out what this means for open‑source vision research and where the community can help improve it. #MetaSAM3 #SegmentAnything #ZeroShotAI #MedicalImaging

🔗 https://aidailypost.com/news/metas-sam-3-falters-niche-technical-terms-complex-logical-prompts

Meta ra mắt SAM 3: Công nghệ phân đoạn hình ảnh với concept.
#SAM3 #Meta #TríTuệNhânTạo #AI #SegmentAnything
#CôngNghệMới #TríTuệArtificial #MetaSuperintelligenceLabs

https://www.reddit.com/r/LocalLLaMA/comments/1p1df5y/sam_3_segment_anything_with_concepts_by_meta/

I'd love to work on shows where SAM2 is good enough. But we have actors with fine hair detail and the comps need to survive 4K inspection so.... Indian roto vendors it is :-/

https://floss.social/@kdenlive/114416926889657357

There's a #SegmentAnything toolset for #Nuke: https://github.com/Theo-SAMINADIN-td/NukeSamurai

It works but the lack of temporal stability makes it break down when actors are not moving. All the cool test footage is people running or objects moving around which is much more forgiving.

I am honestly floored at the #SegmentAnything implementation for #ImageJ / #Fiji

Even running on a laptop, once loaded, it's incredibly quick.

Moreover, it's a super-simple install which is a major barrier to many #AI #DeepLearning implementations.

Time to play around with some #Microscopy and #DigitalPathology data!

Details here: https://github.com/segment-anything-models-java/SAMJ-IJ
Photo source: https://www.pexels.com/photo/photo-of-railway-on-mountain-near-houses-1658967/