π± plantnotplant π
Plant classification subsystem
Hacking towards an automous AI rover hardware and software platform classify plants!
Research plan:
- Deep learning pipeline for state transitions
- Recognize center of plant and perform classificaiton
- Recognize end of track without relying on hardware
- Deep learning pipeline for data labeling
- From hand-written label, recognize species of plant
- From hand-written label, apply data labels
- Height of plant
- Number of plants
- ??
- Deep learning classification
- Collect N camera positions at a single plant
- Is 3D CNN better, or just a single position?
Botony:
Ocimum Γ africanum, (Thai Basil)
Origanum vulgare (Oregano)
Hardware:
- Rasperry-pi as master
- Camera: Night / Standard / Fisheye?
- Python stack
- Keras/Tensorflow
- Open CV
- 2-axis mounted camera controlled by Arduino
- Stepper motor for linear
- Servo for camera scanning
Motor 1.7 A / stage
DRV 8825 max continuous current: 1.5 A
Target current: 1.3 A (derated)
VREF = Current limit / 2 = 0.65V
SEE: https://forum.arduino.cc/index.php?topic=415724.0
Communication protocols:
Arduino slave, connected by I2C bus to RPi master.
Bluetooth PS3 controller.
WiFi networking.
Software:
link
Arduino motor control softwareMuleAI
Onboard systems:Tensorflow 1.8.0
Numpy 1.14.4
corral
Offline training:3D CNN
Table of Contents
Features
TODO
Prerequisites
TODO
Quickstart
...
Environment variables
TODO
...
Code style
. β
Testing
Automatic tests are setup via Travis, executing tox
.
Our test use pytest framework.
New Version
The bumpversion.sh
script helps to bump the project version. You can execute the script using as first argument {major|minor|patch} to bump accordingly the version.
License
todo