Arduino Garden

The following program detects weeds and plants, implementing OpenCV to threshold and find the edges of green objects. As of right now, the largest object is considered a plant while any other object above a certain size is considered a weed. One of the advantages of this program is that it performs under a range (albeit small) of lighting conditions. However, one of the disadvantages of using this program is that it does not implement any kind of machine learning. I aim to add in the future a neural network to identify plants regardless of size.

About

This was a project inspired by Farmbot and a group called Sustainable Earth at Carnegie Mellon University. Overall, it has been a rewarding experience to understand to program such a large project in pieces, put everything together, and ultimately see some promising results.

Requirements

1. Python 3.x

2. OpenCV 3.0 or higher (currently using 3.4.1)

3. numpy (latest available version preferred)

4. pillow (image resizing)

5. PyQt5 (for the Raspberry Pi interface)

   For more specific directions: https://raspberrypi.stackexchange.com/questions/62939/pyqt5-on-a-raspberry-pi

   PyQt4 is also possible, though the entire interface must be edited for that

6. serial (for Arduino communication, currently working on extension)

7. (FUTURE) tensorflow (normally runs on a 64-bit operating system, have not implemented)

How to use this repo

ImageControl.Controller Class

from Image import ImageControl imgControl = ImageControl.Controller()

Creating a new instance of the Controller will immediately create two objects, a Drawer and an Editor. The Drawer handles all drawing and outline functions with opencv. The Editor creates different thresholds for image processing, and calls the Grip pipeline object for filtering.

imgControl.image_grab()

Must be called in order to initialize the image. Can use a given image in the Camera folder or can take an image with a given camera.

imgControl.find_plants()

Finds a plant and weeds based on default thresholds. Future edits will allow for changes. Currently, the center-most object is identified as a plant, and all other objects identified as weeds.

imgControl.draw_all()

Outlines the plant in green and the weeds in blue, and displays the result.

ArduinoControl.Controller Class

from Arduino import ArduinoControl arduinoControl = ArduinoControl.Controller()

Creating an instance of Controller opens up serial communication with an Arduino. More testing will improve the consistency of the connection.

arduinoControl.water_cycle()

Commands such as watering are still being determined.

Future Edits

I am continuing to add Arduino communication capabilities to allow one to implement the weed detection on a Raspberry Pi. The PyQt5 interface is already implemented on Raspberry Pi 3+.