Vision algorithm - SEMS

This repository aim to run a script (main.py) to process n videos/streams.

• Algorithms implemented:
  • People Counter
  • People Tracker
  • 2D Distance Violation
• Uses Flask to publish the image post-processed into a web-page to localhost:8080.
• Communicates directly with SEMS backend to request the source of the videos/streams and to publish all vision data calculated.

It also aims to run a script using ros (roslaunch sems_vision covid19_measures.py) to process the video stream of a zed2 camera.

• Algorithms implemented:
  • Mask Usage
  • 3D Distance Violation

The code is tested using Ubuntu 18.

System Requirements

• python3
• python-pip
• Pipenv

Python Requirements

Pipenv

• Create a new python 3.10 environment

pipenv --python 3.10

• Install dependencies

pipenv install

• Run the script

pipenv run python main.py

Dependencies

Instead of managing dependencies through pip, install them using pipenv. This will ensure the dependencies are correctly added to the Pipfile.

pipenv install (DEPEDENCY)

Usage script

Open main.py, modify global variables if needed.

CAMARAIDS = [6, 7]
BACK_ENDPOINT = ["http://sems.back.ngrok.io/", "http://localhost:3001/"][0]
NGROK_AVAILABLE = True
GPU_AVAILABLE = True
VERBOSE = False
CONFIDENCE_ = 0.3
SKIP_FRAMES_ = 25

Requirements:

• Valid CamaraIDS.
• Backend running.
• yoloV3.
• Python Dependencies.
• Videos Folder.

Run main.py inside the pipenv environment

Open localhost:8080, all cameras should be displayed over there.