SimpleGPSApp Lesson 01 vs Vision Detector

GREAT FUN - GPS 3D MapKit & Speedometer iOS Project - showing RAW GPS Speed of MTS (Meters per Second) & hundredths MPH & KMPH! On the way to Full Level 5 Self Driving for a new EV we are developing (by Summer 2022), this XCODE project is yours, with lots of useful, very simplified code/methods you can copy and use in your own project, Xcode 13, Swift 5, available to copy to your desktop using iTunes/Music File Share. Beginner to Advanced iOS Developer Lessons! We have always learned best and quickest by looking at working App's. Included in this lesson is the full XCODE PROJECT itself for you to use in your own App projects, saving you months of headache to find the answers!:*) We will make you understand! This is the first in a series to help ALL other Apple iOS, iPhone/iPad App Developers, Beginners to Advanced. We've kept the code very, very simple so a 9 year old could get it! Feel free to use any part of this project in your own projects. These are things that have taken months to learn all in this very optimized code for iPhone/iPad App. The Xcode Project is included within the app and can be copied from the iTunes/Music File Share app to your desktop. Highlights in this lesson includes; LocationManager, CLLocationManager, GPS, Speed MPH and KMPH conversion, 3D MapKit, Tracking Mode, iTunes File Sharing, Web/URL link, Buttons with Automated Titles, printing app events to Console/Debug Area, converting large decimal numbers to 2 place, labels, buttons, switches, Case/Logic Switch in Swift, rounding to integer of decimal numbers, variables, integers, text, hidden lessons include a vertical slider and much more! We have plans for many more in the near future! AND if you're interested in getting involved in our LEVEL 5, FULL SELF DRIVING EV PROJECT (for Summer 2022), contact us via our WebSite! CODING IS FUN! JOHNAVATAR.com Pacific Palisades, CA 90402

Vision Detector is an AI image analysis tool that supports CoreML machine learning models, multi-modal Large Language Models, and on-device Apple Intelligence. Choose the mode that best fits your use case. You can choose one of the following image input sources: - Live video by the built-in camera - Still image by the built-in camera - Photo Library - Files (iCloud, Google Drive, Dropbox, etc.) For live video inputs, continuous inference is performed on the camera feed. However, the frame rate and other parameters depend on the device. # Notification Center Vision Detector can call Notification Center for predefined conditions. Broadcasting notifications sends notifications to all Apple devices signed in with the same Apple Account. ## CoreML Mode Vision Detector locally executes CoreML models using Apple’s Vision framework. Before using this mode, prepare a machine learning model in the CoreML format (.mlmodel or .mlpackage) using Create ML. Import ML models via iCloud or AirDrop. Vision Detector supports the following types of CoreML models: - Image classification - Object detection - Object Segmentation - Style transfer Built-in Vision framework is also available for human mask and image classification. ## Vision LLM Mode Vision Detector can use multi-modal large language model (LLMs). Define what to do with the prompt as follows: - If the image is a screenshot, answer the name of the software - Call a notification when you see a cat - Count the number of persons in the image, and notify when it changes ## Apple Intelligence mode The images are completely processed on your device locally with your prompt.