Code:

#!/usr/bin/env python
# opencv-picam-face.py - Opencv using picamera for face tracking using pan/tilt search and lock
# written by Claude Pageau -
# This is a little laggy but does work OK.
# Uses pipan.py module from openelectron.com RPI camera pan/tilt to control
# camera tracking or use your own pan/tilt module and modify code accordingly.
# if you are not using openelectrons.com pan/tilt hardware.
# Also picamera python module must be installed as well as opencv
# To install opencv and python for opencv
# sudo apt-get install libopencv-dev python-opencv
# To install picamera python module
# sudo apt-get install python-picamera
# You will also need to install python picamera.array tha includes numpy
# sudo pip install "picamera[array]"
#    Note
# v4l2 driver is not used since stream is created using picamera module
# using picamera.array
# If you have any questions email pageauc@gmail.com

import io
import time
import picamera
import picamera.array
import cv2
# openelectron.com python module and files from the OpenElectron RPI camera pan/tilt
# Copy pipan.py to 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 = 80
limit_y_top = 180
limit_y_level = 140
limit_x_left = 60
limit_x_right = 240

# To speed things up, lower the resolution of the camera
CAMERA_WIDTH = 320
CAMERA_HEIGHT = 240

# 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 = 60

# 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('haarcascade_frontalface_default.xml')

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

# Move the pan/tilt to a specific location. has built in limit checks.
def pan_goto(x,y):
   p.do_pan (int(x))
   p.do_tilt (int(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()

   while(True):
      with picamera.array.PiRGBArray(camera) as stream:
         camera.capture(stream, format='bgr')
         # 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 faces over the given image using the loaded cascade file
      faces = face_cascade.detectMultiScale(gray, 1.3, 5)

      for (x,y,w,h) in faces:
          if w > 0 :
            face_found = True
            start_time = time.time()

          # Opencv has built in image manipulation functions
          cv2.rectangle(image,(x,y),(x+w,y+h),(255,0,0),2)
          face_cx = x + w/2
          Nav_LR = cam_cx - face_cx
          pan_cx = pan_cx - Nav_LR /5
         
          face_cy = y + h/2
          Nav_UD = cam_cy - face_cy
          pan_cy = pan_cy - Nav_UD /4
          pan_goto(pan_cx, pan_cy)

          # Print Navigation required to center face in image
          print " Nav LR=%s UD=%s " % (Nav_LR, Nav_UD)

      elapsed_time = time.time() - start_time

      # start pan/tilt search for face if timer runs out
      if elapsed_time > wait_time:
          face_found = False
          print "Timer=%d  > %s seconds" % (elapsed_time, wait_time)
          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

          pan_goto (pan_cx, pan_cy)

      # Use opencv built in window to show the image
      # Leave out if your Raspberry Pi isn't set up to display windows
      cv2.imshow('Test Image',image)

      if cv2.waitKey(1) & 0xFF == ord('q'):
         # Close Window
         cv2.destroyAllWindows()
         exit



Statistics: Posted by pageauc — Fri Aug 22, 2014 1:53 am

Statistics: Posted by pageauc — Thu Aug 21, 2014 1:17 pm

Statistics: Posted by Alan — Thu Aug 21, 2014 7:58 am

Statistics: Posted by pageauc — Thu Aug 21, 2014 6:16 am

Code:

#!/usr/bin/env python
# opencv-test7 - Opencv face tracking face tracking with pan/tilt
# written by Claude Pageau - Still a work in progress so excuse the mess
# and unused variables.  Just trying to get something to work.
# This is a little laggy but does work OK.
# Uses pipan.py module for openelectron.com RPI camera pan/tilt to control
# camera tracking so you will need to use your own pan/tilt module if
# you are not using openelectrons.com hardware.
# Also picamera python module must be installed as well as opencv
# and v4l2 driver (execute sudo modprobe bcm2834-v4l2 command to
# install /dev/video0 device. 
# numby not being used so can be removed since changed code to
# use picamera.array instead.
# Still need to write a pan/tilt search for face routine to try to
# find a face if none found in current frame.   

import io
import time
import picamera
import picamera.array
import cv2
import numpy as np
import pipan

p = pipan.PiPan()
sleep_time = 0.5
pan_x_c = 150
pan_y_c = 130

# these variables are not currently used.  pipan module does
# bounds checking already so pan/tilt will not exceed limits.
limit_y_bottom = 80
limit_y_top = 180
limit_y_level = 140
limit_x_left = 60
limit_x_right = 240

#load a cascade file for detecting faces
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

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

#to speed things up, lower the resolution of the camera
CAMERA_WIDTH = 320
CAMERA_HEIGHT = 240

cam_cx = 160
cam_cy = 120

pan_cx = pan_x_c
pan_cy = pan_y_c

face_cx = cam_cx
face_cy = cam_cy

cx_ratio = limit_x_right/cam_cx
cy_ratio = limit_y_top/cam_cy

def pan_goto(x,y):
   p.do_pan (int(x))
   p.do_tilt (int(y))

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)   

   while(True):
      with picamera.array.PiRGBArray(camera) as stream:
         camera.capture(stream, format='bgr')
         # 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 faces over the given image using the loaded cascade file
      faces = face_cascade.detectMultiScale(gray, 1.3, 5)

      for (x,y,w,h) in faces:
          #opencv has built in image manipulation functions
          cv2.rectangle(image,(x,y),(x+w,y+h),(255,0,0),2)
          face_cx = x + w/2
          Nav_LR = cam_cx - face_cx
          pan_cx = pan_cx - Nav_LR /5
         
          face_cy = y + h/2
          Nav_UD = cam_cy - face_cy
          pan_cy = pan_cy - Nav_UD /4
          pan_goto(pan_cx, pan_cy)

          print " Nav LR=%s UD=%s " % (Nav_LR, Nav_UD)
   
      # use opencv built in window to show the image
      # leave out if your Raspberry Pi isn't set up to display windows
      cv2.imshow('Test Image',image)

      if cv2.waitKey(1) & 0xFF == ord('q'):
         # Close Window
         cv2.destroyAllWindows()
         break


Statistics: Posted by pageauc — Thu Aug 21, 2014 5:06 am

• Physically turn the camera around on your robot (if you're following our instructions then the camera will be the right way up, but obviously this may not apply if building your own custom robot).
• If you feel up to it then you can change the code of raspberry_pi_camera_streamer and recompile it.
• You could flip the image at a later point in the process. It should be possible to modify the web interface to flip the image, which might be an easier task if you're more familiar with HTML.

Statistics: Posted by Alan — Wed Aug 20, 2014 6:21 pm

Statistics: Posted by pageauc — Tue Aug 19, 2014 2:18 pm