https://github.com/kanpuriyanawab/handsigns

A CNN built using Keras and TensorFlow 2.2.1 as backend that uses OpenCV camera to count the fingers on taking snap
https://github.com/kanpuriyanawab/handsigns

jupyter-notebook opencv python3 tensorflow

Last synced: about 2 months ago
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A CNN built using Keras and TensorFlow 2.2.1 as backend that uses OpenCV camera to count the fingers on taking snap

• Host: GitHub
• URL: https://github.com/kanpuriyanawab/handsigns
• Owner: kanpuriyanawab
• License: mit
• Created: 2020-05-07T06:34:39.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2021-01-11T06:01:49.000Z (over 5 years ago)
• Last Synced: 2025-06-07T09:39:53.964Z (about 1 year ago)
• Topics: jupyter-notebook, opencv, python3, tensorflow
• Language: Jupyter Notebook
• Homepage: https://shivanshuman021.github.io/HandSigns/
• Size: 42.3 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# Count Your Fingers And look for result in Terminal :D

A Classifier that implemnts Convolutional Neural Networks (CNNs) to count the number of fingers

Trained using SIGNS dataset is a collection of 6 signs representing numbers from 0 to 5.


LinkedIn:

Anshuman Mishra



Download dataset from here:

https://github.com/shivanshuman021/HandSigns-Indentifier/tree/master/datasets

Network Architecture





Convolution Operation : A Review





Watch Me testing it ! See count in Terminal on left side





Here are some more tests ! 



    

        

    

    

    

   

        

   

   

  


  
Dependencies

 1. Python 3 

2. TensorFlow 2.2.1
  

    Visit https://www.tensorflow.org/install 

3. Keras 



4. OpenCV 
   

    Visit https://pypi.org/project/opencv-python


 Try yourself !

😜

In a Terminal / Command Prompt Type 

    $ git clone "https://github.com/shivanshuman021/HandSigns-Indentifier.git"


 Navigate to the cloned repository in a terminal run:

    $ python main.py 

 Camera window named test will be loaded . Press SPACE to capture snapshot !

Press ESC Key to exit