DeepFaceEmotion

A revised DeepFace to have callback function for saving emotion inside program

Background

Although the DeepFace project has an amazing abilities to retrieve facial attriburtes in realtime video analysis, the library is not able to provide a callback function so developers can obtain the identified attributes inside their codes. This limits the developer to write automated programs for data mining, for example, automatically retrive the attributes and save the attributes to a csv plain text file.

Hence, I revised the deepface class in the library to fulfile the needs.

Usage

Replace the attached deepface.py and commons/realtime.py inside the installed deepface lib in python package directory and perform the below example code:

from deepface import DeepFace

count=0

# this function ensures we can write codes to save the timestamp-based facial attributes during processing video
def call_back_func(emotions,age,gender,ts):
    global count
    count+=1
    print(emotions)
    print(age)
    print(gender)
    print()

DeepFace.stream(
    # db_path="../doctor_images",
                # source=0,
                source="video/test2.mp4",
                enable_face_recognition=False, call_back_func=call_back_func,time_threshold=2) # pass call_back_func to the stream function

# do some work based on the retrieved attributes in time series
print("Total Emotions Identification: ",count)

Credit

Say thanks to the DeepFace project.

Note

This revised feature may be unnecessary if the deepface library team adds new features to their library.