snapcon2022:presentation-notes
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Table of Contents
Workshop Notes
Preparation / Prerequisits
- Download …
- Install …
- Print …
Introduction
- The work of the EOLab Team → Current state of development
- Image Classification
- Object detection
- Mini drones with OD
Hands On
- Connect SNAP to the server in Nvidia Jetson
- Image classification game
- Object Detection ??
Reflection
Main Achievements (internal discussion)
SNAP! and Mini-Drone (Harley, 3 mins, live, with Alonzo pilot)
- Tello SNAP Backend (Javascript backend, communication software interface, Wifi, client, binding to IP address), URL, eolab.de github
- One drone has a default IP, it is in “station” mode (the drone is AP, AP mode), 192.168.10.1
- Tello AP mode (client to Wifi), necessary for more than one drone in network and/or interaction with Jetson
- Tello SNAP! category (collection of SNAP! Javascript blocks), websocket interaction with the interface talking to the drone
Object Detection: Follow an Object with Drone (Ilgar, 3 mins, with Alonzo pilot)
- Based on Harley's presentation on Tello SNAP! interaction
- New aspect: Object detection, Jetson
- Challenges
- Video stream from Tello drone to SNAP! (25 fps)
- Video stream from SNAP! to Jetson (extacting stage in base64 format, send message, wait response, sequential, 7 fps)
- Receive response from Jetson to SNAP! (bounding box, class label, coordinate transformation to the stage)
- Frame rate incl. analysis is 7 fps
- Problem (not serious): Realtime delay (latency) within the Tello drone video stream!
- TODO: Short video!
Jetbot and Object Detection with SNAP! (Ali, 3 mins, with Alonzo driver)
- Object follower
- …
- …
snapcon2022/presentation-notes.1659372404.txt.gz · Last modified: 2022/08/01 18:46 by rolf001