MLOptic’s Post

Learn how you can make surfaces touch-reactive by processing a Kinect 2 depth map to get position data out of it, in our new tutorial! This is really useful technique to know if it's not possible to track people directly. Watch the tutorial now on YouTube: https://iihq.tv/3R3ICLd #interactiveimmersivehq #touchdesigner #kinect #depthmapping

🎄🤖 MSTVision Techmas Countdown: The Advent of Code 🤖🎄 Greetings, fellow coders and tech enthusiasts! 🚀 As we countdown to Techmas, let's unravel the four mysteries behind each advent door. Join us on a 2bit journey through the countdown! 🎅🏽🔍 To start with the first advent, we step into the first pixel of our Countdown and explore the artistry of high-res industrial imaging. How do pixels piece together to form a visual masterpiece in automation? Share your pixel ponderings! #PixelPerfection #MSTVisionTechmasCountdown #MSTVision

Recently i have learned about NeRF technology, and i was exited to test it on objects, that's hard to process via Metashape or something like it. So, results wasn't stunning, but still impressive. Check it here: ( http://bit.ly/47yTUfD ) #Realitycapture #photogrammetry #digitaltwins #NeRF

Good News: If you are in s6, or at uni, this publication will give you another reason to dream! You will learn the practical application of geometric and arithmetic series, together with a concept of factorials. I will slowly introduce you to the idea of recursion. Lovely! #Computing101 #relatives #clandevs #ClanDevs

People Position Tracking in Park using Ultralytics YOLOv8 😍🔥🔥 ✅ Pretrained YOLOv8 model has been used here :) ✅ BotSort object tracker is used for better precision in visuals :) ✅ Real-time speed with YOLOv8 medium model 🚀 Get started with Ultralytics: https://lnkd.in/dRj5XyPx #computervision #objectdetection #yolov8 #peopleanalytics #computervisionapplications

Afribold Quantum Opulence Trading Robot https://lnkd.in/dx3vniiv (Click the link- free download demo) Quantum-powered precision: Cutting-edge trading algorithms, trained on vast troves of historical data and real-time market movements, predicts price fluctuations with unrivaled accuracy for maximum profit.

⚡ I was just inspecting the Ultralytics YOLOv8 model's prediction results and when I saw "result.boxes" in results list, an idea formed in my mind. 💡 I know YOLO, itself, is able to segment objects but I decided to use the coordinates of predicted bounding boxes and use them with SAM (Segment Anything model) introduced by Meta Research to segement kidney stones detected by YOLO. The result was satisfying but at some point I had to work on IOU of YOLO model parameter to solve the problem of multiple overlaying bounding boxes. I'd also like to shout-out Roboflow because I learned how to use SAM in their blog and for the amazing Supervision toolkit. You can take a look at my notebook for this task in my GitHub: https://lnkd.in/e8NMWxXc #YOLOv8 #objectdetection #segmentation #Al #deeplearning #machinelearning #Technology #computervision #medicalimaging

https://lnkd.in/gC2GyYW7 Ah, there we go! Let's try again to provide the link to the PDF of my sample Champions character, gladiator. He was fun to write, and I am told he was fun to play, too. A bit of background: Several years ago, HERO Games began licensing other people to produce their own supplements. I wrote and published one called "Shared Origins: The Dynatron." In comic books, some super-scientists can give other people super-powers. The supervillain Red Giant did this, inventing a machine he calls the Dynatron -- except he's not a super-scientist, he's apparently just a competent electrical engineer who got lucky. Or is he? Because nobody else can build a working dynatron, and much better scientists and whole government programs have tried. The supplement not only provides game stats for Red Giant, other characters who gained super-powers from the dynatron, and the miraculous machine itself, it explores the story possibilities of the dynatron. Gladiator is a bonus character, illustrating one more way the machine could be used to create character origins. Dean Shomshak

Hello Connections.... Successfully Completed the Object Detection Project Using YOLO v8 Model! I am thrilled to share that I have successfully completed my first project in object detection using the YOLO v8 model on Google Colab! Under the excellent guidance of my mentor Sai Satish Sir from AlMER Society - Artificial Intelligence Medical and Engineering Researchers Society developed a model that detects cars and trucks. Key Highlights: ->Utilized YOLO v8 model for object detection ->Implemented the project on Google Colab ->Successfully detected players detection #ObjectDetection #YOLOv #A1 #ComputerVision #MachineLearning #DeepLearning #GoogleColab #CricketVideo #AimerSociety #LearningJourney #AIMERS #AIMERSOCIETY #APSCHE