Hand Gesture Identifier (Numbers)

An attempt to identify number from hand gestures using OpenCV Image Recognition.

To run the program on your machine:

1. clone the repo: https://github.com/mukeshmk/hand-gesture.git
2. create a virtual environment inside the folder: python -m venv .venv
3. activate the virtual environment: .venv\Scripts\activate (in case of Windows)
4. install the required packages for the game to run using: pip install -r requirements.txt
5. run the code: python file_name.py
6. make sure to deactivate once your done.

To Generate data for training the model:

• run python generate-training-data.py --label label_value --sample num_of_samples
• This program will open a start video capture using the default camera (device: 0) of your machine.
• In the video you will see a red colour rectangle:
• Hold you hand in the rectangle and make gesture as per lable_value make sure to throw in some variety.
• This will capture num_of_samples number of images and store it under training_data\label_value directory
• Do this for the following labels: 1, 2, 3, 4, 5 and empty.
• Check sample images provided under sample_images directory.

To Train your own model:

• run python train.py
• This will create a model with the name hand-gesture-model.h5 (NOTE: will replace the existing file if model is not renamed)
• This model has a base of a 5 layered Convolutional2D NN with MaxPooling2D.
• The top classification layer using a 50% DropOut and Dense Layer.
• The output layer is also a Dense Layer with softmax activation function.
• All other layers use relu activation.

To have your hand gestures recognised on the fly:

• run 'python hand-gesture.py`
• This will open up a video capture using the default camera of your machine.
• Hold your hand out in the indicated box.
• Using the model trained from 'train.py` file, the hand gestures are predected.