U-TRACKR

Detects an object's location using photogrammetry. Currently utilizes the Raspberry Pi with a camera module running Open-CV for object detection. Runs a server that provides a live video stream.

Setup

How to setup the camera on the pi:

"sudo apt-get update"
"sudo apt-get upgrade"
1. sudo raspi-config > 5 Enable Camera > Enable > Reboot
2. put camera module towards the closer end of the ethernet cable on pi, with the blue facing the ethernet.

"vcgencmd get_camera": Checks if the camera is supported or detected
pull up the pin connectors, put in the camera, then push it back down.

3. "raspistill -o image.jpg" for pics
4. "raspivid" -o video.h264 -t 10000" for videos

Select Interface Options, then Pi Camera and toggle on. Press Finish and exit.

You can verify that the camera works by running

raspistill -o image.jpg

which will save a image from the camera in your current directory. You can open up the file inspector and view the image.

Running the Program (BETA)

1. Installing Dependencies

• 1.1. Enable SSH on the Pi (if it is not already enabled)
  • 1.1.1. Enter sudo raspi-config in a terminal window
  • 1.1.2. Select Interfacing Options
  • 1.1.3. Navigate to and select SSH
  • 1.1.4. Choose Yes
  • 1.1.5. Select Ok
  • 1.1.6. Choose Finish

The following commands starting from 1.2 are to be run on your local machine, not the Pi.

• 1.2. Install Python 2.7.13

• 1.3. Install OpenCV 3.4.0

  • 1.3.1. For Windows, follow this guide to install OpenCV: http://opencvpython.blogspot.ca/2012/05/install-opencv-in-windows-for-python.html

  • 1.3.2. Follow this: https://stackoverflow.com/questions/11699298/opencv-2-4-videocapture-not-working-on-windows

    • copy opencv_ffmpeg340.dll to C:/Python27 (where 340 is the OpenCV version 3.4.0)
    • copy opencv_ffmpeg340_64.dll to C:/Python27 (where 340 is the OpenCV version 3.4.0)

• 1.4. Install the libraries using the following commands:

pip install imutils
pip install flask
pip install picamera[array]
pip install paramiko

2. Running the command

• 2.1. Turn on the Pi, and ensure it is connected to the same Wi-Fi network as your local machine.

• 2.2. Find the IP address by running 'ifconfig' and looking at wlan0 > inet addr

• 2.3. Replace the IP address in main.py from the one found in step 5.

• 2.4. Run

python main.py

Running the Program (ALPHA)

Installing Dependencies

1. https://www.pyimagesearch.com/2015/02/23/install-opencv-and-python-on-your-raspberry-pi-2-and-b/
2. https://www.pyimagesearch.com/2015/03/30/accessing-the-raspberry-pi-camera-with-opencv-and-python/
3. Install the libraries using the following commands:

pip install imutils
pip install flask
pip install picamera[array]

Running the command

Run the following commands:

source ~/.profile
workon cv
sudo modprobe bcm2835-v4l2

Note: The modprobe bcm2835-vl2 command prevents a common OpenCV assertion error when using the Pi Camera.

Go to the folder where this repository is stored, go to /alpha and run the following:

python main.py

You can view a live stream by visiting the ip address of your pi in a browser on the same network. You can find the ip address of your Raspberry Pi by typing ifconfig in the terminal and looking for the inet address.

Visit <raspberrypi_ip>:5000 in your browser to view the stream.

Alternatively, you can run a simple tracking app in /alpha/test to ensure the proper HSV values for object tracking.

python tracking.py

Useful Commands

Checking OpenCV version on Python

source ~/.profile
workon cv
python
>>> import cv2
>>> cv2.__version__