First tests with Integration ChatGPT on a Raspberry Pi, into my Ironman Helmet. Creating my very own JARVIS #ironman #tonystark
The first phase was to connect a capacitive touch sensor to my Ironman Helmet that works reliably. Comment down ??, on what you would like to see next. Join our mailing list, to get the code.
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When your colleague develops a better app than you. Native OpenCV Python vs StreamLit Web App
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...
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Want to learn why Random Forests are one of the most popular and most powerful supervised Machine Learning algorithm in Machine Learning? What this video tutorial explaining the basics of Random Forests.
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Hey Guys, and welcome to another Fun and Easy Machine Learning Algorithm on Random Forests.
Random forest algorithm is a one of the most popular and most powerful supervised Machine Learning algorithm in Machine Learning that is capable of performing both regression and classification tasks. As the name suggest, this algorithm creates the forest with a number of decision trees.
In general, the more trees in the forest the more robust the prediction. In the same way in the random forest classifier, the higher the number of trees in the forest gives the high accuracy results.
To model multiple decision trees to create the forest you are not going to use the same method of constructing the decision with information gain or gini index approach, amongst other algorithms. If you are not aware of the concepts of decision tree classifier, Please check out my lecture here on Decision Tree CART for Machine learning. You will need to know how the decision tree classifier works before you can learn the working nature of the random forest algorithm.
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Are you looking to train U-NET for semantic segmentation, background removal, or salient feature highlighting in Google Colab? This step-by-step guide will walk you through the entire process, from setting up the environment to loading and training your own dataset
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Autonomous Race Car Demo
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Credit to Ashique Anowar for creating Automatic Race Car that can find it's way to the finish line. He used an Arduino Nano, a motor driver, two micro motors, IR sensor array and a 2s lipo battery. It's a simple right hand on the wall algorithm.
Source: https://lnkd.in/ghuJG67S
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#rc #race #racing #track #racetrack #automatic #algorithm #arduino #robotics #electronics #technology #iot #engineering #arduinoproject #programming #diy #arduinouno #diyelectronics #electricalengineering #electrical #robot #tech #esp #linux #raspberry #coding #microcontroller #projects #maker #python #pcb #raspberrypizero #d #artificialintelligence #embeddedsystems
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...
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Pose Estimation Computer Vision Tutorial #2 - People Counting OpenPose using OpenCV Python
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Hey guys and welcome back! So in this lecture and the next few, Im gona show you how to create a series of practical apps using Pose Estimation.
The first app will be a short and easy demo on how to detect and display the total amount people present in each frame. So basically, a person counting app using OpenPose.
Personally Object detection works better than using Pose Estimation at detecting people as models like Yolo V3 allow you to also detect people who are close up whereas Open Pose performs better when the person is further away from the camera and you can see his/her entire body. With this in mind, lets see how this can be done with Pose Estimation.
The video you are seeing now is the travel vlog of me and my wife Krishna taking a cruise on the MSC Sinfonia, on my other Youtube Channel Called RitznKrish-Travel the-world. 5 Random People who subscribe to this channel and comment stand to win the OpenPose full advanced course on Udemy/Teachable for FREE. Links are all down below.
I achieved 10.5 FPS on 1080GTX GPU for 1080P video on average.
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Learn YOLOv4 Object Detection | OpenCV Python | Computer Vision (2021)"
https://www.youtube.com/watch?v=Iw3tducClFw --~--
Want to learn how to build your OWN Spiderman EDITH Glasses AI prototype? Watch this tutorial series to see how I prototype my own glasses with an Intelligent AI.
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Project EDITH Glasses DIY - Phase 1 : AI Object Detection(Spider-Man Far From Home) DEMO
- AI Augmented Reality Tutorial Coming Soon -
Hey guys and welcome back. So in tutorial, Im going to show you how to add AI object detection functionality to our EDITH Glasses prototype. So, what is cool about this phase is that we are able to detect multiple objects simultaneously and in real-time. This makes it really easy to integrate the detections with a heads up display GUI animation.
If you missed the previous phases of Project EDITH. We prototyped facial recognition and face detection to be able to identify people similar to how it was done in Spiderman Far from Home.
In this video, Phase 3 we are going to continue object detection using a MobileNet AI model using OpenCV for Unity. There was an option for using Yolo but it was more process intensive and we have to keep processing power in the back of our minds, should we wish to port all this to a mobile platform like android.
As you can see from the demo we are able to detect multiple objects and instantiate our GUI animation objects which you can customize it based on your application
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In this video, we'll be diving into the world of object segmentation using a powerful deep learning model called U-NET. We'll cover the basics of the architecture and how it's used for image segmentation tasks. Then, we'll delve into the data processing aspect of U-NET, including how to prepare your data for training and how to fine-tune the model for your specific use case. Whether you're a beginner or an experienced machine learning practitioner, this video will give you a comprehensive understanding of U-NET and how to use it for object segmentation
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...
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We swapped Cillian Murphy for the OG Oppenheimer. This is a first draft, so it's a bit rough around the edges. We can show you how to do AI Face Swapping here - ⭐ https://www.augmentedstartups.com/ai-influencer-sign-up
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#deepfake
#faceswap
#Oppenheimer
...
https://www.youtube.com/watch?v=B8vnQmUSxfI