serfiq_example.py

# Author: Jan Niklas Kolf, 2020
from face_image_quality import SER_FIQ
import cv2

if __name__ == "__main__":
    # Sample code of calculating the score of an image
    
    # Create the SER-FIQ Model
    # Choose the GPU, default is 0.
    ser_fiq = SER_FIQ(gpu=0)
        
    # Load the test image
    test_img = cv2.imread("./data/test_img.jpeg")
    
    # Align the image
    aligned_img = ser_fiq.apply_mtcnn(test_img)
    
    # Calculate the quality score of the image
    # T=100 (default) is a good choice
    # Alpha and r parameters can be used to scale your
    # score distribution.
    score = ser_fiq.get_score(aligned_img, T=100)
    
    print("SER-FIQ quality score of image 1 is", score)
    
    # Do the same thing for the second image as well
    test_img2 = cv2.imread("./data/test_img2.jpeg")
    
    aligned_img2 = ser_fiq.apply_mtcnn(test_img2)
    
    score2 = ser_fiq.get_score(aligned_img2, T=100)
   
    print("SER-FIQ quality score of image 2 is", score2)