🌱 plantnotplant 🍂
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 × 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:
Arduino motor control software link
Onboard systems: MuleAI
Tensorflow 1.8.0
Numpy 1.14.4
Offline training: corral
3D CNN
Table of Contents
Features
TODO
Prerequisites
TODO
Quickstart
...
Environment variables
TODO
...
Code style
.
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