Script for generating a custom facial recognition dataset for deep learning applications.
Packages and other requirements to run fr-dataset is provided for conda in requirements.yml and for pip in requirements.txt.
for conda run:
$ conda env create -f requirements.yml
for pip run:
$ pip install -r requirements.txt
-isrc Path of the video file. If the video source comes from a webcam set: <0>
-sol Solution for facial detection. Options: or
-c Crop output frame. Options: <0> for no <1> for yes
-o Path of the output folder for writing frames
-n Name of the person
-res Folder of RESNET facial detector files compatible with the .dnn Opencv lib
-conf Minimum probability to filter weak detections
Example: $ python main.py -isrc 0 -sol dlib -c 0 -o output -n <name1>
Within the project repository it is necessary to create a folder named output to store the captured frames. Later, provide in the parse the name of the folder as in:
$ ... -o <output path>
The code for this project is based in: [1]