从提取的人脸图像中提取人脸（调整提取人脸的大小）

Question

我试图获得从图像中提取的面部的最小可能大小，我的意思是，我想最小化检测面部的绘制矩形的大小。 例如：

输入图像：

所需的 output：

源代码：

import numpy as np
import cv2

face_cascade =cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
img=cv2.imread('swaa.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3,5,maxSize=(150,150))
for (x,y,w,h) in faces:
    img = cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
    roi_gray = gray[y:y+h, x:x+w]
    roi_color = img[y:y+h, x:x+w]
    cv2.imwrite("imgg1.png",roi_color)
    cv2.imwrite("imggg1.png",roi_gray)

cv2.imshow('img',img)
cv2.imwrite("img1.png",img)
cv2.waitKey(0)
cv2.destroyAllWindows()

图片来源： https://www.researchgate.net/publication/322649666_Emotion_Recognition_from_Facial_Expressions_using_Hybrid_Feature_Descriptors

更新：使用发布的解决方案，结果如下所示：

Answer 1

只需使用 cv2.resize function。 https://www.tutorialkart.com/opencv/python/opencv-python-resize-image/

import numpy as np
import cv2
H = 64
W = 64
face_cascade =cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
img=cv2.imread('swaa.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3,5,maxSize=(150,150))
for (x,y,w,h) in faces:
    img = cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
    roi_gray = cv2.resize(gray[y:y+h, x:x+w], (H, W))
    roi_color = cv2.resize(img[y:y+h, x:x+w], (H,W))
    cv2.imwrite("imgg1.png",roi_color)
    cv2.imwrite("imggg1.png",roi_gray)

cv2.imshow('img',img)
cv2.imwrite("img1.png",img)
cv2.waitKey(0)
cv2.destroyAllWindows()