def main():
"""track a face with FIDO's head and base"""
global pos_x
global pos_y
init_publisher()
#color_tracker_window = "output"
#thresh_window = "thresh"
#blob_window = "blob"
cascade_fn = "../data/haarcascades/haarcascade_frontalface_alt.xml"
nested_fn = "../data/haarcascades/haarcascade_eye.xml"
cascade = cv2.CascadeClassifier(cascade_fn)
nested = cv2.CascadeClassifier(nested_fn)
cam = create_capture(-1)
cam.set(cv.CV_CAP_PROP_FRAME_HEIGHT, MAX_Y)
cam.set(cv.CV_CAP_PROP_FRAME_WIDTH, MAX_X)
#cv2.namedWindow(color_tracker_window, 1)
#cv2.moveWindow(color_tracker_window, 0, 0)
#cv2.namedWindow(thresh_window, 1)
#cv2.moveWindow(thresh_window, 700, 0)
#cv2.namedWindow(blob_window, 1)
#cv2.moveWindow(blob_window, 700, 500)
# PIDs for head, neck, and base movement.
# head & neck PID outputs are relative to center of view, so if the ball is centered, output = 0.
head_x_pid = pid.PID(kP=0.020, kI=0.002, kD=0.0, output_min=-HEAD_CENTER, output_max=HEAD_CENTER)
head_x_pid.set_setpoint(CENTER_X)
neck_y_pid = pid.PID(kP=0.020, kI=0.001, kD=0.0, output_min=-NECK_CENTER, output_max=NECK_CENTER)
neck_y_pid.set_setpoint(CENTER_Y)
# base tracks the head and tries to move so that the head will be centered
# output = rotational velocity (applied negatively to left wheel, positively to right)
base_r_pid = pid.PID(kP=1.5, kI=0.05, kD=0.0, output_min=-250, output_max=250)
base_r_pid.set_setpoint(HEAD_CENTER)
base_area_pid = pid.PID(kP=0.02, kI=0.002, kD=0.0, output_min=-250, output_max=250)
base_area_pid.set_setpoint(5500)
servo_if.init_servos()
time.sleep(0.25)
servo_if.set_servo(servo_if.NECK, NECK_START)
head_x = servo_if.get_servo_position(servo_if.HEAD)
neck_y = servo_if.get_servo_position(servo_if.NECK)
jaw_pos = servo_if.get_servo_position(servo_if.JAW)
head_x_output = 0
neck_y_output = 0
base_x_output = 0
base_area_output = 0
last_known_x = None
last_known_y = None
frame_number = 0
while True:
start_time = time.time()
frame_number += 1
ret, frame = cam.read()
#print "cam.read returned {0}".format(ret)
if not ret:
break
#cv2.imshow(color_tracker_window, frame)
#cv2.waitKey(1)
#blurred_image = cv2.GaussianBlur(frame, (9, 9), 0)
#thresholded_image = get_thresholded_image(blurred_image)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.equalizeHist(gray)
rects = detect_faces(gray, cascade)
area = 0
for x1, y1, x2, y2 in rects:
a = (x2 - x1) * (y2 - y1)
if a > area:
area = a
pos_x = (x1 + x2) / 2
pos_y = (y1 + y2) / 2
#cv2.imshow(thresh_window, thresholded_image)
#cv2.waitKey(1)
#Calculating the moments
#contours = None
#contours, hierarchy = cv2.findContours(thresholded_image,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
#area = 0
#if contours:
# for c in contours:
# moments = cv2.moments(c)
# a = moments['m00']
# if a > area:
# area = a
# moment10 = moments['m10']
# moment01 = moments['m01']
lastX = pos_x
lastY = pos_y
#make sure we have a big enough blob
if area > 100:
#Calculate the coordinates of the centroid
#pos_x = int(moment10 / area)
#pos_y = int(moment01 / area)
last_known_x = pos_x
last_known_y = pos_y
elif last_known_x is not None:
if head_x > HEAD_LEFT and head_x < HEAD_RIGHT and neck_y > NECK_DOWN and neck_y < NECK_UP:
pos_x = last_known_x
pos_y = CENTER_Y
else:
#servo_if.ramp_servo(servo_if.HEAD, HEAD_CENTER, -3 if head_x > HEAD_CENTER else 3)
#servo_if.ramp_servo(servo_if.NECK, NECK_START, -3 if neck_y > NECK_CENTER else 3)
pos_x = CENTER_X
pos_y = CENTER_Y
last_known_x = None
last_known_y = None
if area > 100:
head_x_output = head_x_pid.update(pos_x)
head_x = min(max(head_x + head_x_output, HEAD_LEFT), HEAD_RIGHT)
servo_if.set_servo(servo_if.HEAD, int(head_x))
neck_y_output = neck_y_pid.update(pos_y)
neck_y = min(max(neck_y - neck_y_output, NECK_DOWN), NECK_UP) # for screen coordinates, +y = down, but for neck coordinates, +y = up
servo_if.set_servo(servo_if.NECK, int(neck_y))
base_x_output = base_r_pid.update(head_x)
#base_x_output = 0
#base_area_output = base_area_pid.update(area) if area > 50 else 0
base_area_output = 0
left_motor_speed = min(max(base_x_output - base_area_output, -50), 50)
right_motor_speed = min(max(-base_x_output - base_area_output, -50), 50)
set_motor_speed(int(left_motor_speed), int(right_motor_speed)) # for +output, left motor goes forward, right motor goes backward
jaw_pos = int((float(area) - 100.0) / 5000.0 * (servo_if.JAW_OPEN - servo_if.JAW_CLOSED_EMPTY) + servo_if.JAW_CLOSED_EMPTY)
jaw_pos = max(min(jaw_pos, servo_if.JAW_OPEN), servo_if.JAW_CLOSED_EMPTY)
servo_if.set_servo(servo_if.JAW, jaw_pos)
end_time = time.time()
if not frame_number % 10:
print '{}. {} x: {} y: {} area: {} head: {} {} neck: {} {} base: {} {} jaw_pos: {} elapsed: {}'.format(frame_number, datetime.now(), pos_x, pos_y, area, head_x, head_x_output, neck_y, neck_y_output, base_x_output, base_area_output, jaw_pos, end_time - start_time)
#cv2.imshow(blob_window, thresholded_image)
time.sleep(0.001)
#c = cv2.waitKey(3)
#if(c!=-1):
# break
print "exiting"
def main():
"""track a tennis ball with FIDO's head and base"""
global cam
global brain, tail
global inputs, outputs, prev_outputs
global cascade, nested
global debug, quit_request
try:
opts, args = getopt.gnu_getopt(sys.argv, "hd", ["help", "debug"])
except getopt.GetoptError as err:
print err
print 'fido_main.py [--help] [--debug]'
sys.exit(2)
print "opts = ", opts
print "args = ", args
for opt, arg in opts:
print "opt = ", opt
if opt in ('-h', '--help'):
print 'fido_main.py [--help] [--debug]'
sys.exit()
elif opt in ('-d', '--debug'):
debug = True
print "debug = {}".format(debug)
cascade_fn = "../data/haarcascades/haarcascade_frontalface_alt.xml"
#nested_fn = "../data/haarcascades/haarcascade_eye.xml"
cascade = cv2.CascadeClassifier(cascade_fn)
#nested = cv2.CascadeClassifier(nested_fn)
cam = create_capture(-1)
cam.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, MAX_Y)
cam.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH, MAX_X)
if debug:
cv2.namedWindow("output", 1)
cv2.moveWindow("output", 0, 540)
init_pids()
init_publisher()
init_subscriptions()
init_sighandler()
servo_if.init_servos()
time.sleep(0.25)
servo_if.set_servo(servo_if.NECK, servo_if.NECK_START)
outputs['legs'] = servo_if.legs_position
outputs['head'] = servo_if.get_servo_position(servo_if.HEAD)
outputs['neck'] = servo_if.get_servo_position(servo_if.NECK)
outputs['jaw'] = servo_if.get_servo_position(servo_if.JAW)
outputs['tail'] = servo_if.get_servo_position(servo_if.TAIL)
prev_outputs['left_wheel'] = outputs['left_wheel']
prev_outputs['right_wheel'] = outputs['right_wheel']
prev_outputs['legs'] = outputs['legs']
prev_outputs['neck'] = outputs['neck']
prev_outputs['head'] = outputs['head']
prev_outputs['jaw'] = outputs['jaw']
prev_outputs['tail'] = outputs['tail']
brain = fido_fsm.FidoBrain(inputs, outputs)
tail = fido_fsm.FidoTail(inputs, outputs)
frame_number = 0
if debug:
cv2.cv.SetMouseCallback("output", on_mouse, 0)
while not quit_request:
start_time = time.time()
frame_number += 1
read_inputs()
if not inputs['cam_status']:
print "camera read failure"
break
update_pids()
brain.run()
tail.run()
write_outputs()
if debug:
s = inputs['hsv_image'][y_co, x_co]
cv2.putText(inputs['cam_frame'], str(s[0])+","+str(s[1])+","+str(s[2]), (x_co,y_co), cv2.FONT_HERSHEY_SIMPLEX, 1, 255)
cv2.imshow("output", inputs['cam_frame'])
end_time = time.time()
if True: #not frame_number % 10:
print '{}. {} v: {} ir: {} {} {} x: {} y: {} area: {} {} brain: {} tail: {} head: {} neck: {} base: {} {} jaw: {} elapsed: {}'.format(frame_number, datetime.now(), batt_v, inputs['ir_l'], inputs['ir_m'], inputs['ir_r'], inputs['ball_x'], inputs['ball_y'], inputs['avg_ball_area'], inputs['face_area'], brain.state(), tail.state(), outputs['head'], outputs['neck'], outputs['left_wheel'], outputs['right_wheel'], outputs['jaw'], end_time - start_time)
k = cv2.waitKey(10)
if k > 0:
print "key pressed, exiting"
exit(1)
time.sleep(max(0.05 - (time.time() - start_time), 0.001))