Atomatic Attendence System

Atomatic Attendence System using face recognition

Steps to follow:

Step 0)Create a python environment with version 3.5.0(Compulsory step)

    Then activate your environment
    Install all the packages using following command
    pip install -r requirements.txt

Step 1)Create Dataset (refer Videotoimg.ipynb)

For better results use the camera that will be used at the time of attendance taking.

    Divide the images like in folderstructure.png

Step 2)Working with google Colab(if you don't know about Colab refer this https://medium.com/deep-learning-turkey/google-colab-free-gpu-tutorial-e113627b9f5d)

    Upload the dataset to google Drive and face_detection_model(Given above) folder
    Now the colab folder structure should look like colabstructure.png

step 3)Crop the faces and save them to original paths.(refer facex.ipynb)

    For better results I'm doing this.

step 4)Train the model(refer vggface.ipynb)

    Colab work is done.
    Now download the modelname.hdf5 file from the google drive,which is saved using model.save(modelname.hdf5)

step 5)Integrate the trained model with openCV to recognize the faces(refer output.ipynb) locally.

    The folder structure should look like project.png
    Run the output.ipynb locally

You can see the sample outputs in SampleOutputs folder.