def get_faces(image_path, api_mode=False, rescale_face_crop=0):
"""
Return a list of cropped faces given an image path
:param image_path: Path to image
:type image_path: str
:param api_mode: If api_mode is True get_faces returns a list of found HaarFeatures
:type api_mode: bool
:returns: list of images
"""
original_image = Image(image_path)
faces = original_image.findHaarFeatures(segment_face)
if api_mode:
return faces
else:
if rescale_face_crop:
return [
original_image.crop(
scale_bounding_box(face.boundingBox(), rescale_face_crop))
for face in faces
]
else:
return [face.crop() for face in faces]
def findFace(imgPath):
img = Image(imgPath)
faces = img.findHaarFeatures("face.xml")
if faces is not None:
#print("find faces!")
return True
else:
#print("Don't find andy faces!")
return False
def face_recognize(filename):
from SimpleCV import Image, Display, DrawingLayer
image = Image(filename)
faces = image.findHaarFeatures('face.xml')
if faces:
for face in faces:
face_layer = DrawingLayer((image.width, image.height))
face_box = face_layer.centeredRectangle(face.coordinates(), (face.width(), face.height()))
image.addDrawingLayer(face_layer)
image.applyLayers()
image.save(filename)
print('偵測到 {} 張人臉'.format(len(faces)))
else:
print('沒有偵測到人臉')
def face_recognize(filename):
from SimpleCV import Image, Display, DrawingLayer
image = Image(filename)
faces = image.findHaarFeatures('face.xml')
if faces:
for face in faces:
face_layer = DrawingLayer((image.width, image.height))
face_box = face_layer.centeredRectangle(
face.coordinates(), (face.width(), face.height()))
image.addDrawingLayer(face_layer)
image.applyLayers()
image.save(filename)
print('偵測到 {} 張人臉'.format(len(faces)))
else:
print('沒有偵測到人臉')
def get_faces(image_path, api_mode=False, rescale_face_crop=0):
"""
Return a list of cropped faces given an image path
:param image_path: Path to image
:type image_path: str
:param api_mode: If api_mode is True get_faces returns a list of found HaarFeatures
:type api_mode: bool
:returns: list of images
"""
original_image = Image(image_path)
faces = original_image.findHaarFeatures(segment_face)
if api_mode:
return faces
else:
if rescale_face_crop:
return [original_image.crop(scale_bounding_box(face.boundingBox(), rescale_face_crop)) for face in faces]
else:
return [face.crop() for face in faces]
# wiringpi.digitalWrite(65, 0) # imposta GPA0 a 0 (0V, off)
# wiringpi.pinMode(72, 1) # imposta GPA7 come output
# wiringpi.digitalWrite(72, 0) # imposta GPA7 a 0 (0V, off)
with picamera.PiCamera() as camera:
print "\n请输入脸型密码\n"
os.system('omxplayer --no-osd -no-keys password.wav')
while success_flag:
camera.start_preview()
time.sleep(5)
camera.capture('pifacepw.jpg')
image=Image("pifacepw.jpg")
camera.stop_preview()
faces = image.findHaarFeatures("face.xml") # recognize your face through the file HaarCFeatures "face"
if faces:
if not password:
faces.draw()
face = faces[-1]
password = face.crop().save("password.jpg")
print "已更新脸型密码库"
break
else:
faces.draw()
face = faces[-1]
template = face.crop()
template.save("passwordmatch.jpg")
keypoints = password.findKeypointMatch(template,quality,minDist,minMatch)
if keypoints:
print "\n识别正确,欢迎回来\n"
GPIO.setup(RedLED, GPIO.OUT)
GPIO.setup(GreenLED, GPIO.OUT)
GPIO.setup(YellowLED, GPIO.OUT)
GPIO.output(GreenLED, 0)
GPIO.output(RedLED, 0)
GPIO.output(YellowLED, 0)
with picamera.PiCamera() as camera:
while True:
camera.start_preview()
time.sleep(5)
camera.capture('pifacepw.jpg')
image = Image("pifacepw.jpg")
camera.stop_preview()
faces = image.findHaarFeatures("face.xml")
if faces:
if not password:
faces.draw()
face = faces[-1]
password = face.crop().save("password.jpg")
print "First Run Application"
print "Exit Program"
break
else:
faces.draw()
face = faces[-1]
template = face.crop()
template.save("passwordmatch.jpg")
template = Image("passwordmatch.jpg")
diff = template.resize(password.width,
def fancify():
if request.method == 'POST':
print request.data
cur_request = json.loads(request.data)
else:
#cur_request = """{"url": "", "debug":true}"""
#cur_request = """{"url": "", "debug":true}"""
#cur_request = """{"url": "", "debug":true}"""
cur_request = """{"url": "http://localhost/images/scrubs.jpg", "debug":true}"""
#cur_request = """{"url": "http://www.newrichstrategies.com/wp-content/uploads/2012/03/How-to-Find-Good-People-in-Your-Life.jpg", "debug":false}"""
#cur_request = """{"url": "http://greenobles.com/data_images/frank-lampard/frank-lampard-02.jpg", "debug":true}"""
#cur_request = """{"url": "http://www.billslater.com/barack__obama.jpg"}"""
#cur_request = """{"url": "http://celebrityroast.com/wp-content/uploads/2011/01/arnold-schwarzenegger-body-building.jpg", "debug":false}"""
#cur_request = """{"url": "http://face2face.si.edu/.a/6a00e550199efb8833010536a5483e970c-800wi", "debug":true}"""
#cur_request = """{"url": "http://collider.com/uploads/imageGallery/Scrubs/scrubs_cast_image__medium_.jpg", "debug":false}"""
#cur_request = """{"url": "http://localhost/images/Kevin_Bacon_at_the_2010_SAG_Awards.jpg", "debug":false}"""
#cur_request = """{"url": "http://cdn02.cdn.justjared.com/wp-content/uploads/headlines/2012/02/anna-faris-oscars-red-carpet-2012.jpg", "debug":true}"""
#cur_request = """{"url": "http://www.viewzone.com/attractive.female.jpg", "debug":true}"""
cur_request = json.loads(cur_request)
print cur_request["url"]
img = Image(str(cur_request["url"]))
img = img.scale(2.0)
debug = True
#if "debug" in cur_request:
# debug = cur_request["debug"]
chosen_faces = []
faces = img.findHaarFeatures(face_cascade)
if faces is not None:
for face in faces:
face_features = []
invalid_face = False
face_rect = Rect(face.x - (face.width() / 2), face.y - (face.height() / 2), face.width(), face.height())
for chosen_face in chosen_faces:
if face_rect.colliderect(chosen_face):
invalid_face = True
break
if invalid_face:
break
nose = None
mouth = None
left_eye = None
right_eye = None
cur_face = img.crop(face.x, face.y, face.width(), face.height(), centered=True)
#cur_face = face.crop()
noses = cur_face.findHaarFeatures(nose_cascade)
mouths = cur_face.findHaarFeatures(mouth_cascade)
eyes = cur_face.findHaarFeatures(eye_cascade)
face_left_edge = face.x - (face.width() / 2)
face_top_edge = face.y - (face.height() / 2)
if noses is not None:
nose = noses[0]
nose_dist = (abs(nose.x - (face.width() / 2)) +
abs(nose.y - (face.height() * 5 / 9)) +
abs(nose.width() - (face.width() / 4)))
for cur_nose in noses:
cur_dist = (abs(cur_nose.x - (face.width() / 2)) +
abs(cur_nose.y - (face.height() * 5 / 9)) +
abs(cur_nose.width() - (face.width() / 4)))
if cur_dist < nose_dist:
nose = cur_nose
nost_dist = cur_dist
if nose and (nose.y < (face.height() / 3)):
nose = None
if nose and mouths is not None:
mouth = mouths[0]
mouth_dist = abs(mouth.x - nose.x) + (abs(mouth.y - (face.height() * 4 / 5)) * 2)
for cur_mouth in mouths:
cur_dist = abs(cur_mouth.x - nose.x) + (abs(cur_mouth.y - (face.height() * 4/ 5)) * 2)
if (cur_dist < mouth_dist) and (cur_mouth.y > nose.y):
mouth = cur_mouth
mouth_dist = cur_dist
if nose and eyes:
right_eye = eyes[0]
right_eye_dist = (abs(right_eye.x - (3 * face.width() / 4)) * 2 +
abs(right_eye.y - (nose.y - (nose.height() / 2)) / 2) +
abs(right_eye.width() - (face.width() / 3)))
for cur_eye in eyes:
cur_right_dist = (abs(cur_eye.x - (3 * face.width() / 4)) +
abs(cur_eye.y - (nose.y - (nose.height() / 2)) / 2) +
abs(cur_eye.width() - (face.width() / 3)))
if (cur_right_dist <= right_eye_dist): # and (cur_eye.y < nose.y):
right_eye = cur_eye
right_eye_dist = cur_right_dist
if nose and right_eye and (((right_eye.y - (right_eye.height() / 2)) > nose.y) or (right_eye.x < nose.x)):
print "Culling right_eye"
right_eye = None
if nose and mouth:
chosen_faces.append(face_rect)
x_face = face.x - (face.width() / 2)
y_face = face.y - (face.height() / 2)
x_nose = nose.x - (nose.width() / 2)
y_nose = nose.y - (nose.height() / 2)
# Setup TopHat Image
scale_factor = face.width() / 175.0
cur_hat = hat.copy()
cur_hat = cur_hat.scale(scale_factor)
cur_hat_mask = hat_mask.copy()
cur_hat_mask = cur_hat_mask.scale(scale_factor)
cur_hat_mask = cur_hat_mask.createAlphaMask(hue_lb=0, hue_ub=100)
# Calculate the hat position
if (face.y - face.height() / 2) > cur_hat.height:
x_hat = face.x - (cur_hat.width / 2)
y_hat = face.y - (face.height() * 7 / 10) - (cur_hat.height / 2)
img = img.blit(cur_hat, pos=(x_hat, y_hat), alphaMask=cur_hat_mask)
if mouth:
x_mouth = mouth.x - (mouth.width() / 2)
y_mouth = mouth.y - (mouth.height() / 2)
# Setup Mustache Image
cur_stache = stache.copy()
scale_factor = ((nose.width() / 300.0) + (face.width() / 600.0)) / 2.0
cur_stache = cur_stache.scale(scale_factor)
stache_mask = cur_stache.createAlphaMask(hue_lb=0, hue_ub=10).invert()
# Calculate the mustache position
bottom_of_nose = y_nose + (nose.height() * 4 / 5)
top_of_mouth = y_mouth
# if top_of_mouth > bottom_of_nose:
# top_of_mouth = bottom_of_nose
y_must = y_face + ((bottom_of_nose + top_of_mouth) / 2) - (cur_stache.height / 2)
middle_of_nose = nose.x
middle_of_mouth = mouth.x
x_must = x_face + ((middle_of_nose + middle_of_mouth) / 2) - (cur_stache.width / 2)
if right_eye:
x_right_eye = right_eye.x - (right_eye.width() / 2)
y_right_eye = right_eye.y - (right_eye.height() / 2)
# Setup Monocle Image
cur_mono = monocle.copy()
scale_factor = ((right_eye.width() / 65.0) + (face.width() / 200.0)) / 2.0
cur_mono = cur_mono.scale(scale_factor)
mono_mask = cur_mono.createAlphaMask(hue_lb=0, hue_ub=100).invert()
# Calculate Monocle Position
x_mono = x_face + x_right_eye
y_mono = y_face + y_right_eye
img = img.blit(cur_mono, pos=(x_mono, y_mono), alphaMask=mono_mask)
img = img.blit(cur_stache, pos=(x_must, y_must), alphaMask=stache_mask)
if debug:
noselayer = DrawingLayer((img.width, img.height))
nosebox_dimensions = (nose.width(), nose.height())
center_point = (face.x - (face.width() / 2) + nose.x,
face.y - (face.height() / 2) + nose.y)
nosebox = noselayer.centeredRectangle(center_point, nosebox_dimensions, width=3)
img.addDrawingLayer(noselayer)
img = img.applyLayers()
else:
print "Face culled:"
if not nose:
print " No Nose"
if not mouth:
print " No mouth"
if not right_eye:
print " No right eye"
print
if debug:
face_left_edge = face.x - (face.width() / 2)
face_top_edge = face.y - (face.height() / 2)
facelayer = DrawingLayer((img.width, img.height))
facebox_dimensions = (face.width(), face.height())
center_point = (face.x, face.y)
facebox = facelayer.centeredRectangle(center_point, facebox_dimensions, Color.BLUE)
img.addDrawingLayer(facelayer)
if noses:
for nose in noses:
noselayer = DrawingLayer((img.width, img.height))
nosebox_dimensions = (nose.width(), nose.height())
center_point = (face.x - (face.width() / 2) + nose.x,
face.y - (face.height() / 2) + nose.y)
nosebox = noselayer.centeredRectangle(center_point, nosebox_dimensions)
img.addDrawingLayer(noselayer)
if mouths:
for mouth in mouths:
mouthlayer = DrawingLayer((img.width, img.height))
mouthbox_dimensions = (mouth.width(), mouth.height())
center_point = (face.x - (face.width() / 2) + mouth.x,
face.y - (face.height() / 2) + mouth.y)
mouthbox = mouthlayer.centeredRectangle(center_point, mouthbox_dimensions, Color.GREEN)
img.addDrawingLayer(mouthlayer)
if eyes:
for right_eye in eyes:
right_eyelayer = DrawingLayer((img.width, img.height))
right_eyebox_dimensions = (right_eye.width(), right_eye.height())
right_eye_center_point = (face_left_edge + right_eye.x, face_top_edge + right_eye.y)
right_eyebox = right_eyelayer.centeredRectangle(right_eye_center_point, right_eyebox_dimensions)
img.addDrawingLayer(right_eyelayer)
img = img.applyLayers()
img = img.scale(0.5)
w_ratio = img.width / 800.0
h_ratio = img.height / 600.0
if h_ratio > 1.0 or w_ratio > 1.0:
if h_ratio > w_ratio:
img = img.resize(h=600)
else:
img = img.resize(w=800)
output = StringIO.StringIO()
img.getPIL().save(output, format="JPEG") #, quality=85, optimize=True)
img_contents = output.getvalue()
mimetype = "image/jpeg"
return app.response_class(img_contents, mimetype=mimetype, direct_passthrough=False)
from SimpleCV import Image
from os import getcwd, walk
f = []
for (dirpath, dirnames, filenames) in walk(getcwd()):
f.extend(filenames)
break
#print(f)
for imgFile in f:
img = Image(imgFile)
feat = img.findHaarFeatures('face.xml', min_neighbors=5)
count = 0
for face in feat:
i = face.crop()
i.save('face' + str(count) + '_' + imgFile)
with picamera.PiCamera() as camera:
while True:
#acquire image
print "Please align your face with the camera"
time.sleep(1)
camera.start_preview()
#add overlay
o = camera.add_overlay(np.getbuffer(a), layer = 3, alpha = 64)
time.sleep(10)
camera.capture('pipw.jpg')
camera.remove_overlay(o)
#process image
image = Image("pipw.jpg")
camera.stop_preview()
faces = image.findHaarFeatures("face.xml")
faces.draw()
face = faces[-1]
#link image to your name and personal greeting
print "Please Enter Your Name"
name = raw_input()
print("Please enter a personalized greeting message:")
greeting = raw_input()
print("Please enter the exact name of your favorite subreddit: ")
myCity = raw_input()
print("Please enter the zip code of your current location:")
myzip = raw_input()
#save image as password_yourName.jpg
face.crop().save("Saved_Passwords/password_" + str(name) + ".jpg")
while disp.isNotDone():
x = None
y = None
width = None
height = None
coordinates = (x, y)
tempApple = None
exist = True
if disp.mouseLeft:
exist = not exist
if disp.mouseRight:
cycle()
# Look for a face
tempImage = image
faces = image.findHaarFeatures('face')
if faces is not None:
# Get the largest face
faces = faces.sortArea()
bigFace = faces[-1]
# Draw a green box around the face
bigFace.draw()
width = bigFace.width()
height = bigFace.height()
(x, y) = bigFace.coordinates()
coordinates = (x - width / 2, y - height / 2)
if exist == True:
tempApple = apple.scale(width, height)
mask = tempApple.invert().invert()
tempImage = tempImage.blit(img=tempApple, pos=coordinates, mask=mask)
tempImage.save(disp)
face_method.append(new)
if add_new:
faces.append(new)
ind = 0
for paint in db:
print str(ind)
i = ImageCV('./barroco/' + str(paint ['id']) + '.jpg')
paint['resolution'] = {'width':i.size()[0], 'height':i.size()[1]}
paint['faces'] = []
paint['face_methods'] = {}
for xml in xmls:
faces = i.findHaarFeatures(
'/usr/local/share/OpenCV/haarcascades/' + xml['file'])
face_method = []
paint['face_methods'][xml['code']]=face_method
if faces:
for f in faces:
fuzzy_add({ 'x':f.coordinates()[0],
'y':f.coordinates()[1],
'width':f.width(),
'height':f.height() },
paint['faces'],
face_method)
ind+=1
if ind >= 100:
break;
from SimpleCV import Camera, Display, Image, HaarCascade
display = Display()
#lenna = Image("c:\\lenna.png")
#face = lenna.crop(200,200,200,200)
lenna = Image("C:\\Users\\Vijay\\Pictures\\aidan july 2010 pictures 008.jpg")
segment = HaarCascade("C:\\haarcascade_fullbody.xml")
autoface = lenna.findHaarFeatures(segment)
if ( autoface is not None ):
face = autoface[-1].crop()
while display.isNotDone():
face.show()
from SimpleCV import Image
image = Image("./TestFiles/faces.jpg")
faces = image.findHaarFeatures('face.xml', min_neighbors=5)
faces.draw(width=4)
image.show()
# open display
display = Display()
print "Display opening..."
while display.isNotDone():
pir_output = GPIO.input(37)
num_imgs = 0
if pir_output:
num_imgs = num_imgs + 1
print "capturing image..."
os.system('raspistill -n -w 500 -h 500 -o cam.jpg')
img = Image("cam.jpg")
print 'searching for features...'
profile_features = img.findHaarFeatures('profile.xml')
lower_features = img.findHaarFeatures('lower_body.xml')
upper_features = img.findHaarFeatures('upper_body.xml')
face_features = img.findHaarFeatures('face.xml')
if (face_features is not None and len(face_features) != 0):
img.show()
print 'Face features found at:'
for f in face_features:
coord = f.coordinates
print coord
string1 = b'Face detected! \n'
string1_encode = string1.encode()
ser.write(string1) #string1_encode)
elif (profile_features is not None and len(profile_features) != 0):
img.show()
print 'Profile features found at:'
import os
filename = 'frame' # Save each loop's image under the same name so it's overwritten
try:
print 'Press Ctrl+C to exit.'
while True:
# Take an image using raspistill. The small resolution helps speed things up
print 'Capturing...'
os.system('raspistill -n -w 500 -h 500 -o %s.jpg' % filename)
img = Image('%s.jpg' % filename) # Pass the captured image to SimpleCV
print 'Searching...'
# This is the bit that does all the work:
# Try putting 'upper_body.xml' or 'eye.xml' in place of 'face.xml'
faces = img.findHaarFeatures('face.xml')
if faces != []: # If any faces are found
print 'Face(s) found at:'
for face in faces:
# Print the coordinates for each face found
coOrd = face.coordinates()
print '%s' % coOrd
else:
print 'No faces found.'
print '--------------------' # This just breaks things up for easy viewing
except KeyboardInterrupt:
print 'Exit'
def doface(aa, f1, cc, f2, ee):
camera = PiCamera()
#imgg = Image('img1.jpg')
#disp = Display(imgg.size())
dsize = (640, 480)
disp = Display(dsize)
#drawing = Image('mustache.png')
#maskk = drawing.createAlphaMask()
#camera.start_preview()
#sleep(2)
#['right_eye.xml', 'lefteye.xml', 'face3.xml', 'glasses.xml',
# 'right_ear.xml', 'fullbody.xml', 'profile.xml', 'upper_body2.xml',
# 'face.xml', 'face4.xml', 'two_eyes_big.xml', 'right_eye2.xml',
# 'left_ear.xml', 'nose.xml', 'upper_body.xml', 'left_eye2.xml',
# 'two_eyes_small.xml', 'face2.xml', 'eye.xml', 'face_cv2.xml',
# 'mouth.xml', 'lower_body.xml']
while disp.isNotDone():
camera.capture('img2.png')
img = Image('img2.png')
img = img.resize(640, 480)
#whatt = img.listHaarFeatures()
faces = img.findHaarFeatures('face.xml')
print 'faces:', faces
if faces: #is not None:
face = faces.sortArea()[-1]
#print 'size:',face.size
if aa == 'none':
break
elif aa == 'block':
face.draw()
else:
f0draw = aa + '.png'
draw0 = Image('use/' + f0draw)
face = face.blit(draw0, pos=(100, 200))
#bigFace = face[-1]
myface = face.crop()
if f1 and cc is not None:
feature01 = f1 + '.xml'
f1draw = cc + '.png'
draw1 = Image('/home/pi/cv/use/' + f1draw)
feature1s = myface.findHaarFeatures(feature01)
if feature1s is not None:
feature1 = feature1s.sortArea()[-1]
xpos1 = face.points[0][0] + feature1.x - (draw1.width / 2)
ypos1 = face.points[0][
1] + feature1.y #+ (2*draw1.height/3)
#pos = (xmust,ymust)
img = img.blit(draw1, pos=(xpos1, ypos1)) #mask=maskk)
if f2 and ee is not None:
feature02 = f2 + '.xml'
f2draw = ee + '.png'
draw2 = Image('/home/pi/cv/use/' + f2draw)
feature2s = myface.findHaarFeatures(feature02)
if feature2s is not None:
feature2 = feature2s.sortArea()[-1]
xpos2 = face.points[0][0] + feature2.x - (draw2.width / 2)
ypos2 = face.points[0][
1] + feature2.y #+ (2*draw2.height/3)
#pos = (xmust,ymust)
img = img.blit(draw2, pos=(xpos2, ypos2)) #mask=maskk)
img.save(disp)
else:
print 'no face~~'
while (1):
try:
# camera.start_preview()
time.sleep(3)
print "Capturing image"
camera.capture('_foto.jpg')
# camera.stop_preview()
print "processing"
# camera.stop_preview()
foto=Image("_foto.jpg")
# foto=Image("test3.jpeg")
print(foto.listHaarFeatures())
features=foto.findHaarFeatures('face.xml', 1.3, 3)
if features:
features.sortArea() #largest face first
for face in features:
print "Face found at coordinate : " + str(face.coordinates()) + " Area: " + str(face.area())
facecount = facecount+1
# face.draw()
face.crop().save('face-f_%d.jpg' % facecount)
# foto.save('foto_%d.jpg' % facecount)
# else:
# print "None found"
# features=foto.findHaarFeatures('profile.xml', 1.3, 3)
# if features:
# features.sortArea() #largest face first
#! /usr/bin/python2.7
# Program to Test Haar Features
import picamera
from SimpleCV import Image
import time
with picamera.PiCamera() as camera:
camera.resolution = (640, 480)
camera.start_preview()
time.sleep(2)
camera.capture('foto.jpg')
foto = Image("foto.jpg")
print(foto.listHaarFeatures())
trovati = foto.findHaarFeatures('face.xml')
if trovati:
for trovato in trovati:
print "Face Found at Coordinates : " + str(trovato.coordinates())
trovato.draw()
else:
print "Not Found"
camera.stop_preview()
foto.save('foto1.jpg')
foto.show()
time.sleep(10)
from SimpleCV import Display, Image
import os
filename = 'frame' # Save each loop's image under the same name so it's overwritten
try:
print 'Press Ctrl+C to exit.'
while True:
# Take an image using raspistill. The small resolution helps speed things up
print 'Capturing...'
os.system('raspistill -n -w 500 -h 500 -o %s.jpg' % filename)
img = Image('%s.jpg' % filename) # Pass the captured image to SimpleCV
print 'Searching...'
# This is the bit that does all the work:
# Try putting 'upper_body.xml' or 'eye.xml' in place of 'face.xml'
faces = img.findHaarFeatures('face.xml')
if faces != []: # If any faces are found
print 'Face(s) found at:'
for face in faces:
# Print the coordinates for each face found
coOrd = face.coordinates()
print '%s' % coOrd
else:
print 'No faces found.'
print '--------------------' # This just breaks things up for easy viewing
except KeyboardInterrupt:
print 'Exit'
#!/usr/bin/python2.7
# Programma test Haar Features
import picamera
from SimpleCV import Image
import time
with picamera.PiCamera() as camera:
camera.resolution = (640, 480)
camera.start_preview()
time.sleep(10)
camera.capture('foto.jpg')
foto = Image("foto.jpg")
print(foto.listHaarFeatures())
trovati = foto.findHaarFeatures('face.xml')
if trovati:
for trovato in trovati:
print "Found all coordinate : " + str(trovato.coordinates())
trovato.draw()
else:
print "No found"
camera.stop_preview()
foto.save('foto1.jpg')
foto.show()
time.sleep(10)
#!/usr/bin/python2.7
#A proof-of-concept image processing code
from picamera import PiCamera
from SimpleCV import Image
import time
camera = PiCamera()
camera.resolution = (640, 480)
camera.start_preview()
time.sleep(5)
camera.capture('image.jpg')
img = Image("image.jpg")
eyes = img.findHaarFeatures('two_eyes_big.xml')
if (eyes is not None):
eyes = eyes[-1].crop()
eyes.show()
else:
print "Not found"
camera.stop_preview()
img.show()
zoomEyes = eyes.scale(3)
zoomEyes.save('eyes.jpg')
zoomEyes.show()
time.sleep(5)
