Pheebs

A Visual Object Tracking Application with Frame to Frame Data Propagation.

System requirements

• Python V3.6 or later
• IP camera with RTSP stream

Installation

1. Download the project from GitHub
2. Install the required dependencies by running ~/$ pip3 install -r requirements.txt

   Make sure you are in the root directory of the project

3. Open the detect.py file in a text editor of your preference
4. Find line 30 and replace the RTSP stream address with yours.

30.  cap = VideoStream('rtsp://admin:admin1@10.10.240.43:554/11').start()

The RTSP address should have the following format:

rtsp://<USERNAME>:<PASSWORD>@<IP_ADDRESS>:554/11

Start Pheebs

After completing the installation, in a terminal window navigate to the root of the project and run:

~/$ ./pheebs.sh

You should see a window with the feed from your camera and the following information in your terminal.

Centroid Tracking Algorithm

The centroid tracking algorithm I implemented for this project is based on Simple object tracking with OpenCV by Adrian Rosebrock

Project Presentation

The Project presentation is available on YouTube. Watch now

Dependencies

All Dependencies can be found in requirements.txt

absl-py==0.9.0
astor==0.8.1
cachetools==4.1.0
certifi==2018.4.16
chardet==3.0.4
Click==7.0
cmake==3.17.2
cycler==0.10.0
dlib==19.19.0
Flask==0.12.2
gast==0.2.2
google-auth==1.14.1
google-auth-oauthlib==0.4.1
google-pasta==0.2.0
grpcio==1.28.1
h5py==2.10.0
idna==2.7
imutils==0.5.3
ItsDangerous==1.0.0
Jinja2==2.10
joblib==0.14.1
Keras==2.3.1
Keras-Applications==1.0.8
Keras-Preprocessing==1.1.0
kiwisolver==1.2.0
Markdown==3.2.1
MarkupSafe==1.0
matplotlib==3.2.1
numpy==1.17.0
oauthlib==3.1.0
opencv-python==4.2.0.32
opencv-python-headless==4.2.0.32
opt-einsum==3.2.1
paho-mqtt==1.4.0
Pillow==7.1.2
protobuf==3.11.3
pyasn1==0.4.8
pyasn1-modules==0.2.8
pymessenger==0.0.7.0
pyparsing==2.4.7
python-dateutil==2.8.1
python-dotenv==0.9.1
PyYAML==5.3.1
requests==2.23.0
requests-oauthlib==1.3.0
requests-toolbelt==0.8.0
rsa==4.0
Rx==3.0.1
scikit-learn==0.22.1
scipy==1.4.1
six==1.14.0
sklearn==0.0
tensorboard==2.1.1
tensorflow==2.1.0
tensorflow-estimator==2.1.0
termcolor==1.1.0
urllib3==1.23
Werkzeug==0.14.1
wrapt==1.12.1

Inspired in Mykonos.