Python OpenCV-检测到人脸时需要显示文本

我有下面的全部代码，但希望在找到人脸后显示一组文本（例如“名称”）。我试过了，但没有任何进展：

if show_window:
    cv2.rectangle(image,(x,y),(x+w,y+h),(255,0,0),2)  
    font = cv2.FONT_HERSHEY_SIMPLEX   
    cv2.putText(img,'OpenCV Tuts!',(0,130), font, 1, (200,255,155),    

#!/usr/bin/env python
# opencv-picam-face.py - Opencv using picamera for face tracking using    pan/tilt search and lock

# Uses pipan.py module from openelectrons.com RPI camera pan/tilt to control

# Also picamera python module must be installed as well as opencv

# sudo apt-get install libopencv-dev python-opencv

# sudo apt-get install python-picamera
# v4l2 driver is not used since stream is created using picamera module


print("initializing program.  Please wait")
import io
import time
import picamera
import picamera.array
import cv2

# openelectron.com python module and files from the OpenElectron RPI camera pan/tilt
# make sure pipan.py is in same folder as this script.
import pipan

p = pipan.PiPan()

# Approx Center of Pan/Tilt motion
pan_x_c = 150
pan_y_c = 140

# bounds checking for pan/tilt search.
limit_y_bottom = 120
limit_y_top = 170
limit_y_level = 140
limit_x_left = 80
limit_x_right = 200

# To speed things up, lower the resolution of the camera
CAMERA_WIDTH = 320
CAMERA_HEIGHT = 240
inch_conv = 7.0
verbose = True  # display text messages in console window
if not verbose:
print("verbose is set to False so no status messages will be displayed")
show_window = True  # if desktop startx is running then show a window with     image and face rectangle 
if show_window:
print("You must start this script from a terminal on the startx desktop")

# Camera center of image
cam_cx = CAMERA_WIDTH / 2
cam_cy = CAMERA_HEIGHT / 2

# Face detection opencv center of face box
face_cx = cam_cx
face_cy = cam_cy

# Pan/Tilt motion center point
pan_cx = pan_x_c
pan_cy = pan_y_c

# Amount pan/tilt moves when searching
pan_move_x = 30
pan_move_y = 20

# Timer seconds to wait before starting pan/tilt search for face.
wait_time = 30

# load a cascade file for detecting faces. This file must be in
# same folder as this script. Can usually be found as part of opencv
face_cascade =         cv2.CascadeClassifier('/usr/share/opencv/haarcascades/haarcascade_frontalface_de fault.xml')

# Saving the picture to an in-program stream rather than a file
stream = io.BytesIO()

#---------------------------------------------------------------------------   --------------------
def pan_goto(x,y):    # Move the pan/tilt to a specific location. has built  in limit checks.
p.do_pan (int(x))
p.do_tilt (int(y))
if verbose:
    print("move camera to pan_cx=%i pan_cy=%i" % ( x, y))

# Start Main Program
with picamera.PiCamera() as camera:
camera.resolution = (CAMERA_WIDTH, CAMERA_HEIGHT)
camera.vflip = True
time.sleep(2)

# Put camera in a known good position.
pan_goto(pan_cx, pan_cy)   
face_found = False
start_time = time.time()

loop_cnt = 0
while(True):
    with picamera.array.PiRGBArray(camera) as stream:
        camera.capture(stream, format='bgr')
        time.sleep(.2)
        # At this point the image is available as stream.array
        image = stream.array

    # Convert to grayscale, which is easier
    gray = cv2.cvtColor(image, cv2. COLOR_BGR2GRAY)
    # Look for max two faces in image stream using the loaded cascade file
    faces = face_cascade.detectMultiScale(gray, 1.2, 2)

    for (x, y, w, h) in faces:
        if w > 0 :
            face_found = True
            loop_cnt = 0
            start_time = time.time()           
            face_dist = int(( CAMERA_WIDTH / w ) * inch_conv)   # Calculate distance from camera to Face            
            face_cx = x + w/2
            face_cy = y + h/2
            Nav_LR = cam_cx - face_cx
            Nav_UD = cam_cy - face_cy
            pan_cx = pan_cx - Nav_LR /5 
            pan_cy = pan_cy - Nav_UD /4
            pan_goto(pan_cx, pan_cy)
            # Print Navigation required to center face in image
            if verbose:
                print("Found: face_dist=%i inches at pan_cx=%i pan_cy=%i Nav_LR=%i Nav_UD=%i " % (face_dist, pan_cx, pan_cy, Nav_LR, Nav_UD))

        if show_window:
            cv2.rectangle(image,(x,y),(x+w,y+h),(255,0,0),2)    
    font = cv2.FONT_HERSHEY_SIMPLEX
    cv2.putText(image,'name',(0,130), font, 1, (200,255,155))       

    # start pan/tilt search for face if timer runs out 
    elapsed_time = time.time() - start_time
    if elapsed_time > wait_time:
        loop_cnt += 1  
        if loop_cnt > 3: # give camera a few cycles to find a face.
            loop_cnt = 0
        else:
            pan_cx = pan_cx + pan_move_x
            if pan_cx > limit_x_right:
                pan_cx = limit_x_left         
                pan_cy = pan_cy + pan_move_y
                if pan_cy > limit_y_top:
                    pan_cy = limit_y_bottom
            if verbose:
                print("Face Search: loop_cnt=%i Timer=%d  > %s seconds" % (loop_cnt, elapsed_time, wait_time))
            pan_goto (pan_cx, pan_cy)

    # Use opencv built in window to show the image in startx desktop window
    # Leave out if your Raspberry Pi isn't set up to display windows
    if show_window:
        cv2.imshow('openCV Image', image)
        if cv2.waitKey(1) & 0xFF == ord('q'):
        # cursor over opencv window on desktop then press ctrl-q to Close         Window
            cv2.destroyAllWindows()
            exit

---

以下代码对此进行了解释：

face_found = False   #---Initially set the flag to be False
for (x, y, w, h) in faces:
    if w > 0 :                 #--- Set the flag True if w>0 (i.e, if face is detected)
        face_found = True

        cv2.rectangle(image,(x,y),(x+w,y+h),(255,0,0),2)  #--- highlight the face   
        font = cv2.FONT_HERSHEY_SIMPLEX
        cv2.putText(image,'name',(0,130), font, 1, (200,255,155)) #---write the text
        cv2.imshow('Face having name', image)

---

您可以指定您所做的

face\u found

，以决定是否放置文本。对不起，您能否提供更多详细信息以帮助我进一步了解，我们将不胜感激