Muhammad Rizwan Munawar

Count the objects using the new annotator: @ultralytics sweep 💙💙💙 It will support instance segmentation, object detection, object tracking, object counting, and many other computer vision tasks. This feature will be available next week 🚀 #visionai #ml #counting #fruits

How many caps are assembled? @ultralytics YOLO11 is here to help 🔥 The model used here is trained on the custom dataset, and YOLO11 nano varient has been used here for testing. If you haven't checked the Solutions, you can explore here ➡️ docs.ultralytics.com/solutions/ #research…

OBB object counting is now supported in the @ultralytics Python package! 🔥🔥 Open your CLI, and run these two commands: 1️⃣ pip install -U ultralytics 2️⃣ yolo solutions model=yolo11n-obb.pt source="path/to/video/file.mp4" For technical changes, you can explore the PR…

New in-house dataset released by @ultralytics, 12 indoor classes! 🔥 It features ~3,000 real-world images covering 12 common indoor object classes like sofa, chair, table, bed, photo frame, door, and more, captured in natural home settings to reflect real deployment scenarios.…

Build a parking management system in three steps using @ultralytics YOLO 🚀 ✅️Extract the frame from the video stream, just a single frame. ✅️With the help of the parking slots annotator, annotate different parking regions. ✅️Use the parking management system code for…

5️⃣ object detection and image segmentation use cases with @ultralytics 🎉 ✅ Tomato detection ✅ Teeth segmentation ✅ Pill detection ✅ Cabbage detection ✅ Fire detection 💡All models were trained on the custom dataset using Ultralytics YOLO11. #ml #research #usecases #ai

Reasoning capabilities of @Google Gemini 2.5 Pro + @ultralytics utilities 🤯 Prompts: Detect the 2d bounding box around: ✅indoor waterfall ✅ morning light,  blue cushion, grey curtain. ✅ mirror inside closet, chairs ✅ house where car is parked Notebook ➡️…