face_recognition

v_0.0

The code of v_0.0 only allows you to recognize faces from a webcam

v_1.0

The code of v_1.0 allows you to find and recognize faces in a video conference, as well as count the time of presence on the video using facenet_pytorch (MTCNN, InceptionResnetV1) and OpenCV.

v_2.0

• Added YoloV5_face for face recognition

Start

1. Cloning a repository:

   git clone https://github.com/mkgs210/face_recognition
   

2. Installing the required libraries:

   #facenet-pytorch==2.5.2
   #opencv-python==4.6.0.66
   #pandas==1.5.1
   #matplotlib==3.6.2
   pip install -r requirements.txt
   

3. Running the program with default options:

   python main.py
   

Passed parameters:

• -h or --help Displays description of all passed parameters
• -pcp or --photo_catalog_path The path to the photo folder. Inside this directory there should be signed folders with photos of people who will be present in the video (default=photos)
• -ud or --update_data Updates/Creates a file data.pt (call when updating photos). This file contains encoded faces of people (embeddings)(default=True)
• -dp or --data_path Path to the directory where the data.pt file is located (default= - the folder where the program is located)
• -wc or --web_cam Reading video from a webcam. Time log files will not be created (default=False)
• -ivp or --input_video_path Full path to input video (default=video.mp4)
• -dv or --do_video True - create a video in which all found and recognized faces will be marked. False - do not create (default=False)
• -ovp or --output_video_path Full path of output video with tagged faces (default=new_video.mp4)

An example of calling a program with parameters: python main.py -pcp photos -ud True -ivp video.mp4 -dv True -ovp new_video.mp4

Output data

At the first start, the InceptionResnetV1_VGGFace2 folder will be created and the InceptionResnetV1-vggface2 model will be loaded into it

At the end of the program, 4 files will be created:

• Time_{--input_video_path}.csv - file with calculated presence time on video

• Time_drop0_{--input_video_path}.csv - file with calculated time of presence on the video (values with zero time are discarded)

• barh_{--input_video_path}.jpg - a bar graph showing the percentage of time each person is present

• pie_{--input_video_path}.jpg - a pie chart showing the presence time of video participants relative to each other

Also, --do_video True will create a video called --output_video_path (default=new_video.mp4)