Headroid1
From The Artificial Intelligence Cookbook - having some fun with A.I.
I've documented the build instructions for Headroid1 here: Building a face-tracking robot (Headroid1) with Python in an afternoon.
An earlier demo is shown here Headroid1 - a face tracking robot.
Build requirements
- Python 2.5 on a Mac (Leopard)
- OpenCV 2.1 with Python bindings
- pySerial 2.5
- Philips SPC900NC webcam
Full source
#!/usr/bin/python
"""
This program is demonstration for face and object detection using haar-like features.
The program finds faces in a camera image or video stream and displays a red box around them.
Original C implementation by: ?
Python implementation by: Roman Stanchak, James Bowman
"""
import sys
from optparse import OptionParser
import time
import math
import datetime
import serial
import cv
# Parameters for haar detection
# From the API:
# The default parameters (scale_factor=2, min_neighbors=3, flags=0) are tuned
# for accurate yet slow object detection. For a faster operation on real video
# images the settings are:
# scale_factor=1.2, min_neighbors=2, flags=CV_HAAR_DO_CANNY_PRUNING,
# min_size=<minimum possible face size
min_size = (20, 20)
image_scale = 2
haar_scale = 1.2
min_neighbors = 2
haar_flags = 0
def detect_and_draw(img, cascade):
gray = cv.CreateImage((img.width,img.height), 8, 1)
small_img = cv.CreateImage((cv.Round(img.width / image_scale),
cv.Round (img.height / image_scale)), 8, 1)
# convert color input image to grayscale
cv.CvtColor(img, gray, cv.CV_BGR2GRAY)
# scale input image for faster processing
cv.Resize(gray, small_img, cv.CV_INTER_LINEAR)
cv.EqualizeHist(small_img, small_img)
centre = None
if(cascade):
t = cv.GetTickCount()
# HaarDetectObjects takes 0.02s
faces = cv.HaarDetectObjects(small_img, cascade, cv.CreateMemStorage(0),
haar_scale, min_neighbors, haar_flags, min_size)
t = cv.GetTickCount() - t
if faces:
for ((x, y, w, h), n) in faces:
# the input to cv.HaarDetectObjects was resized, so scale the
# bounding box of each face and convert it to two CvPoints
pt1 = (int(x * image_scale), int(y * image_scale))
pt2 = (int((x + w) * image_scale), int((y + h) * image_scale))
cv.Rectangle(img, pt1, pt2, cv.RGB(255, 0, 0), 3, 8, 0)
# get the xy corner co-ords, calc the centre location
x1 = pt1[0]
x2 = pt2[0]
y1 = pt1[1]
y2 = pt2[1]
centrex = x1+((x2-x1)/2)
centrey = y1+((y2-y1)/2)
centre = (centrex, centrey)
cv.ShowImage("result", img)
return centre
def move_servos(xygo):
position = '%da%db' % (xygo[0], xygo[1])
ser.write(position)
def get_delta(loc, span, max_delta, centre_tolerance):
"""How far do we move on this axis to get the webcam
centred on the face?
loc is the face's centre for this axis
span is the width or height for this axis
max_delta is the max nbr of degrees to move on this axis
centre_tolerance is the centre region where we don't allow movement
"""
framecentre = span/2
delta = framecentre - loc
if abs(delta) < centre_tolerance: # within X pixels of the centre
delta = 0 # so don't move - else we get weird oscillations
else:
is_neg = delta <= 0
to_get_near_centre = abs(delta) - centre_tolerance
if to_get_near_centre > 35:
delta = 4
else:
# move slower if we're closer to centre
if to_get_near_centre > 25:
delta = 3
else:
# move real slow if we're very near centre
delta = 1
if is_neg:
delta = delta * -1
return delta
if __name__ == '__main__':
# open a serial port
ser=serial.Serial(port='/dev/cu.usbserial',baudrate=19200,timeout=0)
ser.write('r')
xygo = (90,90)
move_servos(xygo)
# parse cmd line options, setup Haar classifier
parser = OptionParser(usage = "usage: %prog [options] [camera_index]")
parser.add_option("-c", "--cascade", action="store", dest="cascade", type="str", help="Haar cascade file, default %default", default = "/Users/ian/Documents/OpenCV-2.1.0//data/haarcascades/haarcascade_frontalface_alt.xml")
(options, args) = parser.parse_args()
cascade = cv.Load(options.cascade)
if len(args) != 1:
parser.print_help()
sys.exit(1)
input_name = args[0]
if input_name.isdigit():
capture = cv.CreateCameraCapture(int(input_name))
else:
print "We need a camera input! Specify camera index e.g. 0"
sys.exit(0)
cv.NamedWindow("result", 1)
if capture:
frame_copy = None
while True:
frame = cv.QueryFrame(capture)
if not frame:
cv.WaitKey(0)
break
if not frame_copy:
frame_copy = cv.CreateImage((frame.width,frame.height),
cv.IPL_DEPTH_8U, frame.nChannels)
if frame.origin == cv.IPL_ORIGIN_TL:
cv.Copy(frame, frame_copy)
else:
cv.Flip(frame, frame_copy, 0)
centre = detect_and_draw(frame_copy, cascade)
if centre is not None:
cx = centre[0]
cy = centre[1]
# modify the *-1 if your x or y directions are reversed!
xdelta = get_delta(cx, frame_copy.width, 6, 15) * -1
ydelta = get_delta(cy, frame_copy.height, 1, 25) * -1
# on my camera I introduce a delay after movements
# else my assembly wobbles and the webcam transmits
# a non-centred image, so weird oscillations can occur
total_delta = abs(xdelta)+abs(ydelta)
if total_delta > 0:
xygo = (xygo[0]+xdelta,xygo[1]+ydelta)
sleep_for = 1/10.0*min(total_delta, 10)
sleep_for = min(sleep_for, 0.4)
move_servos(xygo)
else:
sleep_for = 0
if cv.WaitKey(10) >= 0: # 10ms delay
break
cv.DestroyWindow("result")
