As you can see in the code below, it only detects the faces with haar cascade, I would like to know how I show the webcam how many people are currently detected. For example, show in the corner of the webcam X people detected.
from __future__ import print_function
import cv2
cap = cv2.VideoCapture(0)
face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
while (cap.isOpened()):
ret,frame = cap.read()
gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.3, minNeighbors=5,
flags=cv2.CASCADE_SCALE_IMAGE,minSize=(50, 50), maxSize=None)
if len(faces) > 0:
print("detected person!")
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x - 10, y - 20), (x + w + 10, y + h + 10), (0, 255, 0), 2)
roi_gray = frame[y-15:y + h+10, x-10:x + w+10]
cv2.imshow("imagem", frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
Simply displaying the count of len(faces) may not solve the purpose,as you can have instances wherein there are multiple bounding boxes drawn over the same face.Therefore, I would suggest you to perform Non Maximal Suppression(NMS) on the result of your detections, followed by incrementing a counter for each time one calls the NMS operation. The final count of the counter will give you a better and more accurate result.