This is my Thesis at the University for the final BSc semester.
- OpenCV - 2.4.
- Python - 2.7.
- xlsxwriter package (
pip install xlsxwriter) - pandas package (
pip install pandas)
Install OpenCV as you can see on the offical site. Or you can use Anaconda enviroment for easy setup.
After the setup you should check settings_for_recognition.json because there you can see the global settings.
- Collect data and place it in input_images folder if you would like to prepare the data from that source. If you would like to use webcam than just skip this step.
- Run
python face_recognizer_menu.py - Choose from the menu points:
- 1: Prepare the training data from the folder (input_images)
- 2: Prepare training data from webcam (results will be saved to output_images)
- 3: Train the face recognizer with the prepared data (model will be saved to saved_model)
- 4: Test face recognition with a webcam
- 5: Recognize from camera and create attendance sheet
- 6: About
- 7: Exit from the application
cascades/
hc_face.xml
input_images/
It can be empty if you prepare data with a webcamera
Peter/
peter1.jpg
peter2.jpg
...
Dori/
dori1.jpg
dori2.jpg
...
Mona/
mona1.jpg
mona2.jpg
...
...
output_images/
There are generated folders and images for the training
saved_models/
Here you can saved the trained model
documentation/
Face_Detection_And_Recognition_By_Gabor_Vecsei.pdf
Gábor Vecsei
2016.12.09.