Python Flask Computer Vision Application

Application components

• Git repository in order to store Webs Service source code
• Container registry where to push Web Service image

Scenario

1. The application creates a Git repository where to store webservice source code
2. The application creates a Docker registry and pushes there webservice image
3. Application creates kubernetes custom resources for Jenkins operator to create Pipeline and start build of webservice
4. Application users get access to the links to their Web Service, Jenkins Pipeline and Git repository through the Control plane (Stacks > Applications > List)

This application uses OpenCV to stream video from a webcam to a web browser/HTML page using Flask and Python, and implements a basic motion detector.

It is based on the OpenCV streaming video tutorial by Adrian Rosebrock.

Local Deployment

Install required Python libraries:

pip install opencv flask numpy opencv-contrib-python imutils

The webstreaming.py file will use OpenCV to access our web camera, perform motion detection via SingleMotionDetector, and then serve the output frames to our web browser via the Flask web framework.

Start the app using the following command:

python webstreaming.py --ip 127.0.0.1 --port 8000

The object_detection.py file will use OpenCV to access our web camera, apply object detection to each frame, and then serve the output frames to our web browser via the Flask web framework.

Start the app using the following command:

python object_detection.py --ip 127.0.0.1 --port 8000 --prototxt MobileNetSSD_deploy.prototxt.txt --model MobileNetSSD_deploy.caffemodel --source http://131.173.8.23/mjpg/video.mjpg

Docker Deployment

This application can be run from Docker with the following steps:

docker build -t webstream .
docker run -ti -p 8000:8000 --rm webstream

It will default to showing the test_video.mp4 but can be configured for any source, depending on platform. On Mac the local webcam cannot be easily passed to the container, but remote addresses or file paths to videos can be. Maybe try:

docker run -ti -p 8000:8000 --rm webstream python3 webstreaming.py --source http://131.173.8.23/mjpg/video.mjpg

Result

View the webcam feed from the web browser:

http://127.0.0.1:8000/

After implementing the background subtractor, we combined it with the Flask web framework, enabling us to:

• Access frames from RPi camera module/USB webcam.
• Apply background subtraction/motion detection to each frame.
• Stream the results to a web page/web browser.
• Support multiple clients, browsers, or tabs.