使用边界框从图像中裁剪人脸

Question

This is the input frame :

I used RetinaFace to detect all the faces and general csv files from that. This is my csv file :

,bbox,score,landmarks
0,"[1811, 850, 1948, 1013]",0.999666452407836,"[[1828, 911], [1887, 913], [1841, 942], [1832, 974], [1876, 976]]"
1,"[346, 1285, 503, 1468]",0.9996420145034791,"[[365, 1361], [424, 1348], [385, 1395], [390, 1426], [439, 1416]]"
2,"[1543, 1418, 1702, 1618]",0.9995224475860591,"[[1578, 1514], [1647, 1498], [1619, 1554], [1610, 1585], [1658, 1572]]"

(only some of the rows are present above ).

And just to show my output image where all the faces where detected by RetinaFace : However I'm not able to get the faces separately :

frame = cv2.imread('input.jpg')
x,y,w,h = [1811, 850, 1948, 1013] # one of the bounding boxes
plt.imshow(frame[y:y+h, x:x+w])

It doesn't give the correct facial location. The output I get is :

Answer 1

I referred the retinaface code and found out that the bounding box is being extracted this way : link

x_min, y_min, x_max, y_max = annotation["bbox"]

Using indexes similar to the above indexing worked perfectly fine for me.

x,y,w,h = label
plt.imshow(frame[y:h, x:w])

Answer 2

Did you try its tensorflow re-implementation? Its extract faces function returns detected faces directly. Besides, it can align detected faces based on the landmark coordinations.

#!pip install retina-face
from retinaface import RetinaFace
import matplotlib.pyplot as plt
faces = RetinaFace.extract_faces("img.jpg", align = True)
for face in faces:
   plt.imshow(face)
   plt.show()