Core AI: Realtime video image detection, tracking, and segmentation... with SAM 3 and RF-DETR. All running on-device. I will share the code in the comments.show more

introducing: fruit xylophone a computer vision music experiment built... with mediapipe hand tracking and roboflow RF-DETR object detection (running in realtime in the browser using transformers js)show more

RF-DETR is now available in Hugging Face transformers state... of the art in both detection and segmentation, outperforming YOLO architectures - checkpoints: - demo: - docs:show more

Gemma 4 watches raw video. Understands the scene. Then... prompts SAM 3 to segment and RF-DETR to track. One AI directing two others. Fighter jets. Crowds. Aerial defense footage. All three models running locally on a MacBook. No cloud. What scene should I point this at next?show more

RF-DETR just landed to Hugging Face transformers 🥵🔥 sota... real-time detection & segmentation models by Roboflow 💜 > play with our real-time demo > fine-tune the models on your use case with our tutorials (takes a toaster's VRAM) > or just hand them to your agents 😄show more

Comparing AI video results: • Gen-3 • Kling AI... 1.5 • Hailuo MiniMax • Luma Dream Machine I used a FLUX1.1 [pro] image as the input. Each model ran the same prompt 3 times, and I chose the best results: "Smooth side tracking shot of a woman jogging at twilight with the city skyline in the background, sharp focus on the woman as she pumps her arms with each stride as she jogs, depth of field, advertising commercial" Running, jogging, and walking are difficult for AI video models, and none of them produced a smooth result, but this is the worst they will be.show more

The new Dell XPS, with Intel® Core™ Ultra Processors... and on-device AI, delivers!show more

The new Dell XPS, with Intel® Core™ Ultra Processors... and on-device AI, delivers!show more

another experiment with fruit, computer vision, and projection mapping... live object detections (roboflow RF-DETR model) are used to control the animated scene (threejs) i also added mediapipe segmentation to the pipeline to create collisions with my silhouette, but i haven't gotten a hang of it yet more experiments are underwayshow more

RoadScan-AI-Automated-Pothole-Detection-Tracking RoadScan AI is a computer vision system built... to automatically detect and track potholes in road footage — including dashcam, drone, and fixed-camera video. At its core, the system uses a YOLO11n model fine-tuned on a custom pothole dataset, paired with ByteTrack for multi-object tracking. This enables the system to maintain a consistent identity for each pothole across frames rather than treating every detection as a new, isolated event.show more

Worth mentioning to all the people on me about... the pupil detection. It's a bug in the Comfy implementation and will get sorted.... this is day 1 testing remember. Here is the same video ran on Wan's website - near perfect pupil tracking.show more

🚀 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 #AIResearchshow more

GPT Image 2 + Seedance 2.0 Prompt Share Forest... Rebirth Storyboard and video prompt in the replies. Created on Martini Art AIshow more

A few people asked if we show videos. No,... we do not! It’s all realtime animation, created with code, running in the browser. We run CHROME to check if 1 pixel in the software is *exactly* 1 pixel on the hardware and if we get the right framerate.show more

Sidebar for AI application built with React and TypeScript... 🚀 Code in the comments and within Atheros Pass 🧑‍💻show more

Google’s Gemma 4 E2B running on-device on iPhone 17... Pro Gemma 4 is built from the same research as Gemini 3, has image understanding capabilities and can reason if needed Running at ~40tk/s with MLX optimized for Apple Siliconshow more

i built an app to search old travel photos... on my computer with natural language queries using free local AI models: - smolVLM to describe the scene and colours - roboflow RF-DETR to detect objects - chromaDB to store metadata labels and run semantic search - python + streamlit for the interface fast and free search has been achieved internallyshow more

Pothole detection on the road in real time using... Ultralytics YOLO26! 🕳️ Manual road inspections are slow, costly, and hard to scale. With object detection, potholes can be identified directly from street-level images or video feeds, enabling faster and more consistent road condition monitoring. How I built this demo: ✅ Trained a segmentation model on a custom dataset. ✅ Generated mask contours for each pothole. ✅ Leveraged the onnx-exported model for faster processing. #Pothole #RoadDamage #AIshow more

The NEW YORK KNICKS championship inspired me to build... an AI basketball coach to improve my 1v1 game Built with: - Robloflow RF-DETR to detect players/ball/rim - MediaPipe to capture body angles - OpenCV to analyze and annotate the clipshow more

Multiple gliding rack focus prompt share thread, created in... Kling AI 2.6 Image to video with native audio unless stated. Prompt and samples in comments ⬇️ 🔊🔊 1. Cyberpunk Club - ID needed!show more