README.md

Playground

A python library consisting of pipelines for visual analysis of different sports using Computer Vision and Deep Learning.

Update : FPS Optimisation Code and Docs added for video detector.

To setup project, open up a new terminal and enter the following:

sh setup_conda.sh

OR

sh setup_pip.sh

To test, run test.py or simply open up a new terminal and enter the following code:

# For single image:

from Badminton.Badminton import Detector
obj = Detector()
obj.detect_players_image("Badminton/images/bad.jpg")

################################################################

# For video:

from Badminton.Badminton import Detector
obj = Detector()
obj.detect_players_video("Badminton/images/video2.mp4")

################################################################

# For using tiny yolo for better FPS:
# For video:

from Badminton.Badminton import Detector
obj = Detector(tiny=True)
obj.detect_players_video("Badminton/images/video2.mp4")

################################################################

# For Heatmap generation:

from Badminton.Badminton import Detector
obj = Detector()
obj.get_heatmap("Badminton/images/video2.mp4")

################################################################

To test this code in Windows simply change the code in test.py to

from Badminton.Badminton import Detector
obj = Detector(Windows=True)
obj.detect_players_video("Badminton/images/video2.mp4")