ImageWarping

Creates a real time warped video output from webcam input.

Threading is used to obtain higher FPS(frames per second).

Accessing webcam/USB camera using the cv2.VideoCapture function and the .read() method is a blocking operation. The main thread of our Python script is completely blocked (i.e., “stalled”) until the frame is read from the camera device and returned to our script.

We can improve our FPS simply by creating a new thread that does nothing but poll the camera for new frames while our main thread handles processing the current frame.

We can increase our FPS by as much as 379% due to reduction in latency.

In order to accomplish this FPS increase/latency decrease, we have moved the reading of frames from a webcam or USB device to an entirely different thread, totally separate from our main Python script.

For a detailed explanation please refer: https://www.pyimagesearch.com/2015/12/21/increasing-webcam-fps-with-python-and-opencv/

To run in docker

Do the following:

1. Build the container

./build_container.sh

2. Run the container

./run_container.sh

3. Once inside the container

python fps.py

Note: Make sure the scripts build_container.sh and run_container.sh are executable. Note: If you face any problems try running in sudo.

To run on your local

1. Install all the requirements

pip3 install -r requirements.txt

2. Run fps.py

python fps.py