berak
January 11, 2022, 12:45pm
2
for starters, there’s a simple typo:
you want
roi_gray = gray[y:y + h, x:x + w]
(wont change much, since most face cascades are trained on quadratic rects)
also, you should not use the same MINSIZE to find eyes and faces, think of it.
in the end, the cascades approach is quite brittle, we got better tools nowadays,
import argparse
import numpy as np
import cv2 as cv
def str2bool(v):
if v.lower() in ['on', 'yes', 'true', 'y', 't']:
return True
elif v.lower() in ['off', 'no', 'false', 'n', 'f']:
return False
else:
raise NotImplementedError
parser = argparse.ArgumentParser()
parser.add_argument('--image1', '-i1', type=str, help='Path to the input image1. Omit for detecting on default camera.')
parser.add_argument('--image2', '-i2', type=str, help='Path to the input image2. When image1 and image2 parameters given then the program try to find a face on both images and runs face recognition algorithm.')
parser.add_argument('--video', '-v', type=str, help='Path to the input video.')
parser.add_argument('--scale', '-sc', type=float, default=1.0, help='Scale factor used to resize input video frames.')
parser.add_argument('--face_detection_model', '-fd', type=str, default='face_detection_yunet_2021dec.onnx', help='Path to the face detection model. Download the model at https://github.com/opencv/opencv_zoo/tree/master/models/face_detection_yunet')
parser.add_argument('--face_recognition_model', '-fr', type=str, default='face_recognition_sface_2021dec.onnx', help='Path to the face recognition model. Download the model at https://github.com/opencv/opencv_zoo/tree/master/models/face_recognition_sface')
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