Ivy

Ivy is an open-source video-based object counting software for tallying pretty much anything (vehicles, people, animals — you name it).

Need help setting up Ivy and analyzing the logs? Visit https://trafficlogic.co or send an email to [email protected].

Requirements

• Python 3 (tested with version 3.7)

Setup

• Clone this repo [email protected]:nicholaskajoh/ivy.git.
• Create and/or use a virtual environment (optional but recommended) mkvirtualenv -p python3.7 ivy.
• Install the dependencies in requirements.txt pip install -r requirements.txt.
• Choose a detector and install its dependencies where necessary (if you're not sure what to pick, we recommend you start with yolo).

Detector	Description	Dependencies
yolo	Perform detection using models created with the YOLO (You Only Look Once) neural net. https://pjreddie.com/darknet/yolo/
tfoda	Perform detection using models created with the Tensorflow Object Detection API. https://github.com/tensorflow/models/tree/master/research/object_detection	CPU: pip install tensorflow-cpu GPU: pip install tensorflow-gpu
detectron2	Perform detection using models created with FAIR's Detectron2 framework. https://github.com/facebookresearch/detectron2	python -m pip install 'git+https://github.com/facebookresearch/detectron2.git' (https://github.com/facebookresearch/detectron2/blob/master/INSTALL.md)
haarcascade	Perform detection using Haar feature-based cascade classifiers. https://docs.opencv.org/3.4/db/d28/tutorial_cascade_classifier.html

Run

• Create a .env file (based on .env.example) in the project's root directory and edit as appropriate.
• Run python -m main.
• Run using Docker docker build -t nicholaskajoh/ivy ..

Demo

Download ivy_demo_data.zip and unzip its contents in the data directory. It contains detection models and a sample video.

Test

python -m pytest

Debug

By default, Ivy runs in "debug mode" which provides you a window to monitor the object counting process. You can:

• press the p key to pause/play the counting process
• press the s key to capture a screenshot
• press the q key to quit the program
• click any point on the window to log the coordinates of the pixel in that position

Community

Got questions, contributions, suggestions, concerns? Let us know! Also follow us on Twitter @CountWithIvy to get notified about new features, fixes and initiatives.