Live Rock Paper Scissor Detection in Raspberry Pi

Course Q&A TensorFlow: Data and Deployment Specialization Device-based Models with TensorFlow Lite
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Hi there,

I had some fun tweaking the optional assignment this week to run the rock, paper, scissor classifier to classify live camera feed from Raspberry Pi.

If anyone wants to give it a try, you can download the files from Github at:

There are four files:

  1. RPS_Camera.ipyb - Used to create the rock, paper, scissor classification model in Jupyter notebook. I used transfer learning for the model using mobilenet_v2 as feature extractor and adding one dense layer for classification. This code also saves the retrained model and coverts to tflite format.
  2. rps.tflite - Rock Paper Scissor tflite model.
  3. rps_main.py - Python script to execute rps.tflite on Raspberry Pi from command line.
  4. README.md - Instructions for command line execution.

I hope you would have fun and please share your feedback.

Thanks,
S

1 Like
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Hi Sumeet_Mahesh!
That’s great effort and work! Thanks for sharing your work and knowledge with us, will go through it and will have some fun with it :+1:
Regards,
Nithin