Under the hood, Parkerr uses tensorflow.js a javascript library to run machine learning models entirely in the browser. Parkerr uses YOLO7 (You Only Look Once v7) a real-time object detection computer vision model. YOLO is fast, accurate models and simple to train. My implementation with Parkerr involves mapping the model's output to a custom data structure and integrating it into the application's data pipeline and state to be suitable for a parking app.

Parkerr currently implements remote communication through a P2P solution using PeerJS, a javascript library that implements a WebRTC configuration using PeerServer Cloud services and Google stuns servers.

Parkerr can take webcam footage or remote video communication through another device that has a built-in camera and modern browser.

Other than site website analytics, none. Parkerr processes all of the video footage on the client side and all remote communication is p2p and private.

The auto-detect feature works by collecting a snapshot of all of the detected vehicles for a few seconds and then suppresses all of the vehicles that have not been in a consistent position. If you were to try and use the auto-detect feature on an empty parking lot no selections will be made, if attempted on a full parking lot then all the parking spaces will be marked.

Yes! That is possible and was implemented, Originally the architecture of this project, I created a flask server that receives base64/blobs from the client and processes the input using yolo3 model with OpenCV, works fine on a small scale but needs additional configuration and refactoring for larger scales. Such as a server with a powerful GPU and autoscaling.

human, bicycle, car, motorcycle, airplane, bus, train, truck, boat, traffic light, fire hydrant, stop sign, parking meter, bench, bird, cat, dog, horse, sheep, cow, elephant, bear, zebra, giraffe, backpack, umbrella, handbag, tie, suitcase, frisbee, skis, snowboard, sports ball, kite, baseball bat, baseball glove, skateboard, surfboard, tennis racket, bottle, wine glass, cup, fork, knife, spoon, bowl, banana, apple, sandwich, orange, broccoli, carrot, hot dog, pizza, donut, cake, chair, couch, potted plant, bed, dining table, toilet, tv, laptop, mouse, remote, keyboard, cell phone, microwave, oven, toaster, sink, refrigerator, book, clock, vase, scissors, teddy bear, hair drier, toothbrush.