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snapcon2022:presentation-notes [2022/08/01 15:07] – created shreyasnapcon2022:presentation-notes [2022/08/01 20:19] (current) – [Object Detection: Follow an Object with Drone (Ilgar, 3 mins, with Alonzo pilot)] rolf001
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-Introduction+====== Workshop Notes ======
  
--Image Classification +===== Preparation / Prerequisits =====
--Object detection +
--Mini drones with OD+
  
-Hands On+  * Download ... 
 +  * Install ... 
 +  * Print ...
  
--Connect SNAP to the web server +===== Introduction =====
--Image classification game+
  
-Reflection+  * 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  
 +  * https://wiki.eolab.de/doku.php?id=drones:mini_drones:snap_tello 
 + 
 +===== Jetbot and Object Detection with SNAP! (Ali, 3 mins, with Alonzo driver) ===== 
 + 
 +  * Object follower 
 +  * Jetbot Camera 
 +  * SNAP! is running remotely, could be running on Jetbot 
 +  * DetectNet (SSD-MobileNet V2, CoCo Dataset, 91 Classes) 
 +  * Closed Loop Control 
 +  * TODO: Short video! 
 + 
 + 
 +===== 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!
  
  
snapcon2022/presentation-notes.1659359264.txt.gz · Last modified: 2022/08/01 15:07 by shreya