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. #MachineLearning #AI #Researchshow 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

Ultralytics YOLO11 vs Ultralytics YOLO26: Which one runs faster?... ⚡ Evaluate inference speed and performance across both models in the ONNX format to understand how YOLO26 improves efficiency for real-time computer vision applications. Read more ➡️ #Ultralytics #YOLO26 #AI #Research #ComputerVisionshow 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

Count rooftop panels with Ultralytics YOLO26 OBB! 🏠 Use... oriented bounding boxes to detect solar panels from aerial views and capture their orientation, enabling accurate counting for inspections, asset management, and infrastructure analytics. Explore more ➡️ #Ultralytics #YOLO26 #AI #ObjectCounting #ComputerVisionshow 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

Improve crosswalk safety with Ultralytics YOLO26! 🚸 Detect pedestrians,... vehicles, and high-risk interactions in real-time to support safer crossings, smarter alerts, and improved traffic monitoring. Read more ➡️ #Ultralytics #YOLO26 #RoadSafetyshow more

Detect worker falls in real time with Ultralytics YOLO26!... 📦 Combine object detection and pose estimation to identify when a person carrying luggage boxes falls, helping logistics teams improve warehouse safety and respond faster to incidents. Get started ➡️ #Ultralytics #YOLO26 #AI #Logistics #WorkplaceSafetyshow more

Monitor patient posture with Ultralytics YOLO26 Pose! Detect keypoints... in real time to identify positions like lying down vs. standing. Useful for patient monitoring, fall-risk alerts, and hospital/elder-care room analytics. Learn more ➡️ #AI #PoseEstimation #HealthTech #YOLO26show 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

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

Railway operators manage thousands of kilometers of track and... critical infrastructure every day!🚆 With Ultralytics YOLO26, teams can automatically monitor assets such as insulators, rail clamps, semaphores, and towers in images and video, improving asset visibility and supporting predictive maintenance workflows. Explore more ➡️ #RailwayOperations #MachineLearning #AIshow 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

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

Launching today: Ultralytics YOLO26! The fastest, most deployable YOLO... ever built. For years, shipping object detection meant extra steps and messy post-processing. YOLO26 changes the game with end-to-end, NMS-free inference, simpler deployment, and strikingly low latency. Built End-to-End. Built for the Edge. 👉 Get started today:show more

Smart parking pipeline in real-time with Ultralytics YOLO26 🚗... 🅿️ Over the weekend, I built a parking management system that monitors slot occupancy (occupied vs available). In busy parking areas where vehicles partially overlap slots or enter at angles, the system still maintains accurate detection and status updates in real time. More information 👇 #yolo26 #parkingproblem #machinelearningshow 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

Instance vs semantic segmentation difference | Ultralytics🚀 🧩Instance segmentation... answers: “Which pixels belong to each object?” 🎨Semantic segmentation answers: “Which pixels belong to each class?” #segmentation #MachineLearning #AIshow more

Mediapipe is cool, but Ultralytics YOLO26 Pose is on... another level 🔥🔥🔥 I ran a quick comparison between mediapipe and YOLO pose, and while both have their strengths, YOLO26 blew me away. My findings👇 Raw video credit: NVIDIA Team 😀 #AI #PoseEstimation #Peopleshow 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

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