Python 如何使用Haar cascade进行人脸检测，如何使用kalman滤波器进行跟踪？

我是计算机视觉新手，我正在尝试使用haar cascade进行人脸检测和卡尔曼滤波进行跟踪，我打算在raspberry pi 3B上运行代码。因此，无法使用任何深度学习方法进行跟踪。 如何在代码中使用cv2.kalmanfilter（）（）进行跟踪并为遍历路径画一条线？ 如果有人能给我指点，那将是很大的帮助 我的代码是：

from __future__ import print_function
import numpy as np
import cv2
from imutils.video import WebcamVideoStream
from imutils.video import FPS
import argparse
import imutils
import cv2
 
faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
#faceCascade = cv2.CascadeClassifier('haarcascade_profileface.xml')
fps = FPS().start()
cap = cv2.VideoCapture(0)
cap.set(3,640) # set Width
cap.set(4,480) # set Height

while True:
    ret, img = cap.read()
    #img = cv2.flip(img, -1)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = faceCascade.detectMultiScale(
        gray,     
        scaleFactor=1.2,
        minNeighbors=5,     
        minSize=(20, 20)
    )

    for (x,y,w,h) in faces:
        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.imshow('video',img)
    fps.update()
    k = cv2.waitKey(30) & 0xff
    if k == 27: # press 'ESC' to quit
        break
fps.stop()
print("[INFO] approx. FPS: {:.2f}".format(fps.fps()))
cap.release()
cv2.destroyAllWindows()

---

在deepface中运行人脸检测非常简单。detectFace函数分别在背景中应用人脸检测和对齐

#!pip install deepface
from deepface import DeepFace
backends = ['opencv', 'ssd', 'dlib', 'mtcnn']
detected_face = DeepFace.detectFace("img.jpg", detector_backend = backends[0])

您也可以手动运行检测和对齐。如果对齐不在您的范围内，您可以通过这种方式跳过此步骤

from deepface.commons import functions
img = functions.load_image("img.jpg")
backends = ['opencv', 'ssd', 'dlib', 'mtcnn']

detected_face = functions.detect_face(img = img, detector_backend = backends[3])
plt.imshow(detected_face)

aligned_face = functions.align_face(img = img, detector_backend = backends[3])
plt.imshow(aligned_face)

processed_img = functions.detect_face(img = aligned_face, detector_backend = backends[3])
plt.imshow(processed_img)