Live High-Quality DSLR Capture Module for KBOS 22L/R Arrivals
@iot @edgeai @tensorflow-lite @opencv @debian @rpi4b @coral @canon
Automatically capture high-res photos for aircrafts on KBOS 22L/R Final Approach.
v1.0 (August 07, 2020): Workable on Debian x86 and ARMv7l, all clear on dependencies.
- Recompile tflite model for edgetpu and test speed increase
- MySQL/MongoDB: flight/aircraft/airline info for the plane captured, embedded in cyaned.co
- Integrated with project CYANED.CO: Switch between github.io and RPi server
- Flight info updates and auto matching
- (DEP) Sentry for boarder field monitoring, when an airplane is approaching, initialize DSLR
- Use videos in
raw_sentryto identify the least power necessary for sentry monitoring - Test live performance
- Crop live feed and picture in cv2, helpful in boosting performance?
- Single image and video object detection, screenshot, test correct rate
- Live monitoring and detection (only binary info req), test FPS
- Set init trigger params for DSLR
- Use videos in
This project is projected to have multiple stages:
- DONE: Automatically capture high quality photos for any aircraft on approach on 22L/R
- DONE: Process photo: object detection and trimming raw inputs
- PENDING: Fetch flight data: obtain live arrival data from FlightAware.com and identify flight
- PENDING: Build a server for live feeds based on LAMP
- PENDING: Flexibility to setup in a new environment, parameterized setups
- Make sure Coral is unplugged when
sudo apt install libedgetpu1-std - Saves from DSLR
gphoto2 --list-all-files; gphoto2 --get-files=XXX-XXX - tensorflow cross-compilation
- objdetapp example
- tensorflow lite official guide
- tflite on raspian
- docker ref
- docker ref
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