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Apache 2.0 license🔥 On-device deployment ready Extends SAM2 for tracking objects in videos 🔥 Click-to-segment support EdgeTAM by Meta !

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Gradio

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23,301 görüntüleme • 1 yıl önce •via X (Twitter)

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Gradio1 yıl önce

EdgeTAM by Meta Launch the model locally with a powerful feature rich gradio app:

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Gradio1 yıl önce

The official Space is getting ready on @huggingface. Keep an eye out for it.

Alexander Myasoedov profil fotoğrafı
Alexander Myasoedov1 yıl önce

INTRODUCING: Agentic Security - LLM Security Scanner! 🔍 🔑 Features: Scans for prompt injections, jailbreaking & more. Provides detailed reports & options to customize attack rules. 🔗access the GitHub Link ↓

Benzer Videolar

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware check out this SAM2 vs SAMURAI comparison! - paper: - code: - license: Apache-2.0
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SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware check out this SAM2 vs SAMURAI comparison! - paper: - code: - license: Apache-2.0

SkalskiP

124,331 görüntüleme • 1 yıl önce

Segment Anything Model 2 (SAM 2) is a foundation model from Meta FAIR for promptable visual segmentation in images & videos. Available now for anyone to build on for free, open source under an Apache license. Try the demo ➡️
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Segment Anything Model 2 (SAM 2) is a foundation model from Meta FAIR for promptable visual segmentation in images & videos. Available now for anyone to build on for free, open source under an Apache license. Try the demo ➡️

AI at Meta

97,677 görüntüleme • 1 yıl önce

CVPR 2025 papers pt. 2 - SAMWISE SAMWISE adds language understanding and temporal reasoning to SAM2; you can segment and track objects in videos just by describing them more papers: ↓ more
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CVPR 2025 papers pt. 2 - SAMWISE SAMWISE adds language understanding and temporal reasoning to SAM2; you can segment and track objects in videos just by describing them more papers: ↓ more

SkalskiP

20,528 görüntüleme • 11 ay önce

Introducing Meta Segment Anything Model 2 (SAM 2) — the first unified model for real-time, promptable object segmentation in images & videos. SAM 2 is available today under Apache 2.0 so that anyone can use it to build their own experiences Details ➡️
1:20

Introducing Meta Segment Anything Model 2 (SAM 2) — the first unified model for real-time, promptable object segmentation in images & videos. SAM 2 is available today under Apache 2.0 so that anyone can use it to build their own experiences Details ➡️

AI at Meta

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Prove anything with LAGRANGE. Enabling support for scalable, production-ready proofs. Now available on our 1-click rollup deployment platform.
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Prove anything with LAGRANGE. Enabling support for scalable, production-ready proofs. Now available on our 1-click rollup deployment platform.

Caldera

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Scientists are now working on a real-life web-shooters inspired by Spider-Man. The device currently lifts objects over 80X its weight, under various conditions and extends up to 5 inches in length. (via
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Scientists are now working on a real-life web-shooters inspired by Spider-Man. The device currently lifts objects over 80X its weight, under various conditions and extends up to 5 inches in length. (via

Cosmic Marvel

123,830 görüntüleme • 1 yıl önce

MatAnyone -- Separate any objects from videos. Works on ALL OS (Mac, Windows, Linux). Just select some regions and click "Video Matting" to separate objects from videos. This 1-click launcher for the gradio app was written by anchorite - thank you!
0:58

MatAnyone -- Separate any objects from videos. Works on ALL OS (Mac, Windows, Linux). Just select some regions and click "Video Matting" to separate objects from videos. This 1-click launcher for the gradio app was written by anchorite - thank you!

cocktail peanut

17,479 görüntüleme • 1 yıl önce

NEW: Kokoro 82M - APACHE 2.0 licensed, Text to Speech model, trained on < 100 hours of audio 🔥
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NEW: Kokoro 82M - APACHE 2.0 licensed, Text to Speech model, trained on < 100 hours of audio 🔥

Vaibhav (VB) Srivastav

330,034 görüntüleme • 1 yıl önce

🚀 The Segment Anything Model (SAM) has been upgraded to SAM2, featuring an efficient image encoder for segmenting images and videos. But does SAM2 outperform SAM1 in medical image and video segmentation? We're thrilled to present our paper "Segment Anything in Medical Images and Videos: Benchmark and Deployment"! We comprehensively benchmark SAM2 across 11 medical image modalities and videos. 📄 Paper: 💻 Code: **Highlights:** 1. SAM2 doesn’t always outperform SAM1 in 2D medical images, but excels in video segmentation, making it more accurate and efficient for 3D images, such as CT and MR scans. 2. MedSAM still outperforms SAM2 on most 2D modalities, but SAM2 surpasses MedSAM for 3D image segmentation in a slice-by-slice approach. 3. Segmentation performance varies with model size; sometimes the smallest model outperforms larger ones. 4. Fine-tuning SAM2 significantly boosts its performance for medical image segmentation. While SAM2 may struggle with challenging objects that have unclear boundaries or low contrast, it excels in generating good initial segmentation masks for common medical images and videos. However, the official interface doesn’t support medical data formats and has limitations on video length. To address this, we've developed a 3D Slicer Plugin and Gradio API for efficient 3D medical image and video segmentation. We invite you to try them out and provide feedback! 🔧 Deployment: - 3D Slicer Plugin: - Gradio API: (Note: Due to GPU limitations, the online API is available for only 12 hours and may be slow. We highly recommend deploying the Gradio API with your own computing resources: A big shoutout to Jun Ma (JunMa) who recently joined our UHN AI hub (UHN AI Hub) as Machine Learning Lead, and kudos to all co-authors: Sumin Kim, Feifei Li, Mohammed Baharoon (Mohammed Baharoon), Reza Asakereh, and Hongwei Lyu! This is true teamwork! Looking forward to collaborating with the community to advance 3D medical image and video segmentation foundation models! University Health Network U of T Department of Computer Science Department of Laboratory Medicine & Pathobiology Temerty Centre for AI in Medicine (T-CAIREM) Vector Institute #MedTech #AIinHealthcare #DeepLearning #MedicalImaging #SAM2 #MedSAM #AIResearch
0:22

🚀 The Segment Anything Model (SAM) has been upgraded to SAM2, featuring an efficient image encoder for segmenting images and videos. But does SAM2 outperform SAM1 in medical image and video segmentation? We're thrilled to present our paper "Segment Anything in Medical Images and Videos: Benchmark and Deployment"! We comprehensively benchmark SAM2 across 11 medical image modalities and videos. 📄 Paper: 💻 Code: **Highlights:** 1. SAM2 doesn’t always outperform SAM1 in 2D medical images, but excels in video segmentation, making it more accurate and efficient for 3D images, such as CT and MR scans. 2. MedSAM still outperforms SAM2 on most 2D modalities, but SAM2 surpasses MedSAM for 3D image segmentation in a slice-by-slice approach. 3. Segmentation performance varies with model size; sometimes the smallest model outperforms larger ones. 4. Fine-tuning SAM2 significantly boosts its performance for medical image segmentation. While SAM2 may struggle with challenging objects that have unclear boundaries or low contrast, it excels in generating good initial segmentation masks for common medical images and videos. However, the official interface doesn’t support medical data formats and has limitations on video length. To address this, we've developed a 3D Slicer Plugin and Gradio API for efficient 3D medical image and video segmentation. We invite you to try them out and provide feedback! 🔧 Deployment: - 3D Slicer Plugin: - Gradio API: (Note: Due to GPU limitations, the online API is available for only 12 hours and may be slow. We highly recommend deploying the Gradio API with your own computing resources: A big shoutout to Jun Ma (JunMa) who recently joined our UHN AI hub (UHN AI Hub) as Machine Learning Lead, and kudos to all co-authors: Sumin Kim, Feifei Li, Mohammed Baharoon (Mohammed Baharoon), Reza Asakereh, and Hongwei Lyu! This is true teamwork! Looking forward to collaborating with the community to advance 3D medical image and video segmentation foundation models! University Health Network U of T Department of Computer Science Department of Laboratory Medicine & Pathobiology Temerty Centre for AI in Medicine (T-CAIREM) Vector Institute #MedTech #AIinHealthcare #DeepLearning #MedicalImaging #SAM2 #MedSAM #AIResearch

Bo Wang

178,419 görüntüleme • 1 yıl önce

FULL SEGMENT: Roman Reigns confronts Solo and the Bloodline 2.0 WHAT A SEGMENT. ROMAN BEAT THEM ALL BY HIMSELF THAT WAS CINEMA 🔥🔥🔥☝️ #SmackDown
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FULL SEGMENT: Roman Reigns confronts Solo and the Bloodline 2.0 WHAT A SEGMENT. ROMAN BEAT THEM ALL BY HIMSELF THAT WAS CINEMA 🔥🔥🔥☝️ #SmackDown

Nav

202,487 görüntüleme • 1 yıl önce

Managed to get LivePortait running near realtime within ComfyUI, now also without Insightface, using Google's MediaPipe (Apache-2.0 license) instead!
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Managed to get LivePortait running near realtime within ComfyUI, now also without Insightface, using Google's MediaPipe (Apache-2.0 license) instead!

Jukka Seppänen

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omg wow 🤯🤯🤯 AutoGLM, an AI agent by Z.ai which can use a phone Models are released under the MIT License, and all code is under the Apache-2.0 License, hosted on GitHub Blog post
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omg wow 🤯🤯🤯 AutoGLM, an AI agent by Z.ai which can use a phone Models are released under the MIT License, and all code is under the Apache-2.0 License, hosted on GitHub Blog post

Melvin Vivas

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Super excited to introduce SAM2 Studio! 🚀🤖 I've been getting a lot of questions lately on supporting AI inference tailored for patient data and sensitive workflows. We optimized SAM2 to run completely on-device in real time for all of your medical segmentation workflows - including surgical video segmentation, radiographs, pathology slides and more!
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Super excited to introduce SAM2 Studio! 🚀🤖 I've been getting a lot of questions lately on supporting AI inference tailored for patient data and sensitive workflows. We optimized SAM2 to run completely on-device in real time for all of your medical segmentation workflows - including surgical video segmentation, radiographs, pathology slides and more!

Cyril Zakka, MD

19,805 görüntüleme • 1 yıl önce

New AI research from Meta – CoTracker3 Simpler and Better Point Tracking by Pseudo-Labelling Real Videos. More details ➡️ Demo on Hugging Face ➡️ Building on our previous work on CoTracker, this new model demonstrates impressive tracking results where points can be tracked for a long time even when they're occluded or leave the field of view. CoTracker3 achieves state-of-the-art, outperforming all recent point tracking approaches on standard benchmarks — often by a substantial margin. We've released the research paper, code and a demo on Hugging Face — along with models available under an A-NC license to support further research in this space.
0:27

New AI research from Meta – CoTracker3 Simpler and Better Point Tracking by Pseudo-Labelling Real Videos. More details ➡️ Demo on Hugging Face ➡️ Building on our previous work on CoTracker, this new model demonstrates impressive tracking results where points can be tracked for a long time even when they're occluded or leave the field of view. CoTracker3 achieves state-of-the-art, outperforming all recent point tracking approaches on standard benchmarks — often by a substantial margin. We've released the research paper, code and a demo on Hugging Face — along with models available under an A-NC license to support further research in this space.

AI at Meta

218,898 görüntüleme • 1 yıl önce

SAM 2 from Meta FAIR is the first unified model for real-time, promptable object segmentation in images & videos. Using the model in our web-based demo you can segment, track and apply effects to objects in video in just a few clicks. Try SAM 2 ➡️
0:40

SAM 2 from Meta FAIR is the first unified model for real-time, promptable object segmentation in images & videos. Using the model in our web-based demo you can segment, track and apply effects to objects in video in just a few clicks. Try SAM 2 ➡️

AI at Meta

88,918 görüntüleme • 1 yıl önce

Infinite length Seedance 2.0 videos now live on Open-Higgsfield-AI 🔥 First in the world to support extending Seedance 2.0 videos indefinitely 🤯 As always ✅Free with BYOK ✅Open-source ✅ Cut Higgsfield subscription bill Link to project below👇
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Infinite length Seedance 2.0 videos now live on Open-Higgsfield-AI 🔥 First in the world to support extending Seedance 2.0 videos indefinitely 🤯 As always ✅Free with BYOK ✅Open-source ✅ Cut Higgsfield subscription bill Link to project below👇

Anil Chandra Naidu Matcha

22,153 görüntüleme • 2 ay önce

Ready for the license… riding like a pro already. 🔥💥
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Ready for the license… riding like a pro already. 🔥💥

Anamika

43,344 görüntüleme • 1 ay önce

I want to feature them on “Nana 2.0” music video. They nailed, it wanna support their dancing skills by putting them on TV 🔥
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I want to feature them on “Nana 2.0” music video. They nailed, it wanna support their dancing skills by putting them on TV 🔥

Djkarri

149,009 görüntüleme • 1 yıl önce

🎵 An open-source music generation model (ACE-Step) was just released by StepFun AI + ACE Studio! 📐 3.5B parameter open-weight model 🔓 Apache-2.0 license 🎙️ Supports lyric generation 🚀 Can generate 4m songs in just 20s on A100
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🎵 An open-source music generation model (ACE-Step) was just released by StepFun AI + ACE Studio! 📐 3.5B parameter open-weight model 🔓 Apache-2.0 license 🎙️ Supports lyric generation 🚀 Can generate 4m songs in just 20s on A100

mrfakename

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