Animals segmentation & tracking using Ultralytics YOLO26 🫎 How... I created this demo: - Data annotation using Ultralytics Platform. - YOLO26 model training using Platform. - Downloaded the trained model. - Run Inference on video files locally. #animal #ai #MachineLearningshow more

Football players detection + tracking using Ultralytics YOLO26 ⚽️... It took me 30 minutes to train the YOLO26 model on a custom dataset using Ultralytics Platform. Later, I used the object tracker (Bytetrack) for tracking the players; tracking could be improved further, and I am working on it this week. More info 👇 #soccer #football #MachineLearningshow more

Run promptable segmentation with Ultralytics YOLO26-E! 🧠 Segment objects... using natural language prompts with YOLO26-E, ideal for flexible visual search, rapid annotation, and interactive computer vision workflows. Get started ➡️ #Ultralytics #YOLO26 #AI #Researchshow more

Vehicle tracking using Ultralytics YOLO26 👀 In this demo,... I trained the YOLO26 model on a custom dataset and later used an object tracker (Bytetrack) to track the objects in the video file. Note: I also performed testing with Botsort, which is also a good tracker, but it's slow in comparision to Bytetrack. #Tracking #ComputerVision #MachineLearningshow more

People counting in zones using Ultralytics YOLO26 🧑‍🤝‍🧑 In... this demo, people are moving on elevators. I used a custom-trained YOLO26 model to detect and track each person, then applied the object counting in zones solution to count the number of people within each zone. 🙂 #people #retail #MachineLearningshow more

Depth anything v2 vs. Ultralytics YOLO26 depth | Speed... comparison 🚀 For this demo, I compared yolo26m-depth with depth-anything-v2-small on an NVIDIA RTX 3050 using the same input settings. Even though I used the medium YOLO26 model, it delivered nearly 2× the throughput: 22 FPS vs. 11 FPS. #Vehicles #MachineLearning #Researchshow 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

YOLOE-26 released by Ultralytics support text + visual prompts... 🤯 This was a part of the YOLO26 release. It's a zero-shot, promotable model, almost like YOLO-World, but it also offers real-time object segmentation. Highlights👇 #AI #MachineLearning #YOLOEshow more

Object detection + tracking + counting using Ultralytics YOLO26... 🚀 👉 Object detection tells you what is in a scene. 👉 Tracking follows each object across video frames. 👉 Counting turns those movements into actionable data. YOLO26 delivers fast, accurate detections, while multi-object tracking maintains unique identities across frames. Add configurable counting lines or regions to measure entries, exits, directional movement, and other real-world traffic metrics. #vehicles #MachineLearning #Highwayshow more

Detect small objects using @Ultralytics YOLO26 + SAHI 😍... A perfect combo when speed isn’t the priority, but accuracy is everything, especially when detecting tiny or distant objects in your images. learn how it works 👇 #AI #objectdetection #trafficanalysisshow more

⭐️3D Model Live Tracking Showcase ⭐️ Live Demo of... the 3D model i created using Blender!!show more

New ML gem on the hub: LDM3D by Intel.... This diffusion model generates image & depth from text prompts. Using a custom @gradio 6dof three.js component you can generate immersive 360-degree views from prompts demo: model:show more

Ready to get started with visual generative AI? Look... no further. Learn how to run image and video models locally on RTX GPUs using ComfyUI with LTX & BlackForestLabsAI - Unofficial FLUX in our blog below. 👇show more

Nah no, this is not a pre-made or baked... Blender model. It is created entirely from scratch using extruded geometry and procedural textures for the mustard hatching pattern on the model... all done with Google Gemini 3 pro AI. In fact, every Three.js 3D model you see on this website has been vibe coded with AI 😎 Live: Code:show more

NVIDIA DROPPED A MOTION DIFFUSION MODEL FOR HUMANOID ROBOTS... trained on 700 hours of mocap data kimodo generates high-quality 3D human and robot motions from text prompts you control it with: → full-body pose keyframes → end-effector positions/rotations → 2D paths and waypoints works on human skeletons and unitree G1 robot plug the outputs directly into mujoco or retarget to other robots using GMR has a web-based interactive demo with a timeline editor. runs locally needs ~17GB VRAM to run inference open source under apache 2.0show more

The first natively trained 1-bit model: BitNet 2B. Trained... on 4 trillion tokens. that can run on CPUs like Apple M2 Native 1.58-bit weights and 8bit activations W158A8 Outperforms LLaMA &close to Qwen 2.5 1.5B in while using only 0.4GB memory versus 2GB and processes tokens 40%show more

Hey friends! Here’s how I created the Arrivals PFP... (286 hand drawn traits) using AutoCad & Photoshop one by one, the process you’ll see in this video! #ArrivalsLab #NFTs #PFPsshow more

i trained this computer vision model just by asking... for "tennis players", using roboflow rapid and SAM3 the model picks out Alcaraz and Sinner, while correctly avoiding the ball boys and fans then I exported the model to python and wrote a script to filter the data, track movement history, and annotate the final video this was a quick experiment but I could expand the project to track player speeds, distance covered, shot count, etc. could use this for a sports analytics app that tracks live matches and calculates custom metricsshow more

The consistency of Kling 3.0 Motion Control is just... insane and it’s all on mobile now. 💃🤯 I created this by mapping a dance onto a static image using the Pollo AI app. The physics and facial details stay 100% on the model. 💎 Right now, Kling 3.0 is 50% OFF! PolloAI Creators #Kling3 #PolloAI #AI #ParadoxPixelsshow more