fzjcdt / hand_controller

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Hand Controller


DEMO

demo

TODO:

  • Build an environment of tensorflow-gpu, opencv, etc.
  • Build a data set and train a model.
  • Load cpm and classification models to detect gestures and react accordingly.
  • Optimize multiple model loading.
  • The heat map is a grayscale map that does not require 3 channels, and using one channel to reduce the amount of calculation.
  • Add a layer of convolution and pooling layer to become AlexNet, the input size does not need to be compressed to 100*100.
  • Increase data sets and add other categories to improve generalization.
  • Pay more attention to the precision rate, ignore the recall rate, and remove the results with the closest predictions.

REFERENCE

Improved on the basis of Convolutional Pose Machinesm and HandGestureClassify

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Language:Python 100.0%