def scale(self, img_path, scale):
new_file_path = self.nfn('resized')
img = Image(img_path)
img = img.scale(scale)
img.save(new_file_path)
self.transformations.append(new_file_path)
return new_file_path
def encuentraYFiltraBlobs(self,areaMin, areaMax, toleranciaWH, desviacionD, toleranciaLP, tipoDibujo): imagenBlobs = Image(self.rutaImagenTratada_Fase2).copy() blobs = imagenBlobs.findBlobs() self.todosLosCandidatos = blobs if blobs: blobs.image = imagenBlobs self.areaBlobs = blobs.area() blobs = self.filtroPorArea(blobs, areaMin, areaMax) self.numBlobsCandidatosPorArea = len(blobs) # Busca los blobs de forma circular , los blobs que pasan el filtro # se guardan en la lista self.articulaciones blobs = self.filtroPorForma(blobs, toleranciaWH, desviacionD, toleranciaLP) if tipoDibujo == 'blobs': self.dibujaBlobs(blobs) elif tipoDibujo == 'estructura': self.dibujaEstructura(imagenBlobs) # La imagen tratada tiene que ser guardada porque sino no funciona # la integracion con Tkinter imagenBlobs.save(self.rutaImagenBlobs) return Image(self.rutaImagenBlobs)
def send_email(percentage):
import smtplib
from email.MIMEMultipart import MIMEMultipart
from email.MIMEImage import MIMEImage
from email.MIMEText import MIMEText
# Prepare actual message
msg = MIMEMultipart()
msg['From'] = "*****@*****.**" # change to your mail
msg['To'] = "*****@*****.**" # change to your mail
msg['Subject'] = "RPi Camera Alarm!"
imgcv = Image("image.jpg")
imgcv.save("imagesend.jpg",
quality=50) # reducing quality of the image for smaller size
img1 = MIMEImage(open("imagesend.jpg", "rb").read(), _subtype="jpg")
img1.add_header('Content-Disposition', 'attachment; filename="image.jpg"')
msg.attach(img1)
part = MIMEText('text', "plain")
part.set_payload(("Raspberry Pi camera alarm activated with level {:f}"
).format(percentage))
msg.attach(part)
try:
server = smtplib.SMTP("mail.htnet.hr",
25) #change to your SMTP provider
server.ehlo()
server.starttls()
server.sendmail(msg['From'], msg['To'], msg.as_string())
server.quit()
print 'Successfully sent the mail'
except smtplib.SMTPException as e:
print(e)
def scale(self, img_path, scale):
new_file_path = self.nfn('resized')
img = Image(img_path)
img = img.scale(scale)
img.save(new_file_path)
self.transformations.append(new_file_path)
return new_file_path
def send_email(percentage):
import smtplib
from email.MIMEMultipart import MIMEMultipart
from email.MIMEImage import MIMEImage
from email.MIMEText import MIMEText
# Prepare actual message
msg = MIMEMultipart()
msg['From'] = "*****@*****.**" # change to your mail
msg['To'] = "*****@*****.**" # change to your mail
msg['Subject'] = "RPi Camera Alarm!"
imgcv = Image("image.jpg")
imgcv.save("imagesend.jpg", quality=50) # reducing quality of the image for smaller size
img1 = MIMEImage(open("imagesend.jpg","rb").read(), _subtype="jpg")
img1.add_header('Content-Disposition', 'attachment; filename="image.jpg"')
msg.attach(img1)
part = MIMEText('text', "plain")
part.set_payload(("Raspberry Pi camera alarm activated with level {:f}").format(percentage))
msg.attach(part)
try:
server = smtplib.SMTP("mail.htnet.hr", 25) #change to your SMTP provider
server.ehlo()
server.starttls()
server.sendmail(msg['From'], msg['To'], msg.as_string())
server.quit()
print 'Successfully sent the mail'
except smtplib.SMTPException as e:
print(e)
def encuentraYFiltraBlobs(self, tipoDibujo='estructura'):
imagenBlobs = Image(self.rutaImagenTratada_Fase2).copy()
blobs = imagenBlobs.findBlobs()
self.todosLosCandidatos = blobs
if blobs != []:
blobs.image = imagenBlobs
self.areaBlobs = blobs.area()
blobs = self.filtroPorArea(blobs)
self.numBlobsCandidatosPorArea = len(blobs)
# Busca los blobs de forma circular , los blobs que pasan el filtro
# se guardan en la lista self.articulaciones
blobs = self.filtroPorForma(blobs)
if tipoDibujo == 'blobs':
self.dibujaBlobs(blobs)
elif tipoDibujo == 'estructura':
self.listaAngulos = self.encuentraYDibujaAngulos(imagenBlobs)
# La imagen tratada tiene que ser guardada porque sino no funciona
# la integracion con Tkinter
imagenBlobs.save(self.rutaImagenBlobs)
return Image(self.rutaImagenBlobs)
def rotate(self, img_path, shoe_measurements):
img = Image(img_path)
new_file_path = self.nfn('rotated')
img = img.rotate(shoe_measurements.toe_heel_angle(), point=shoe_measurements.cleat_length_intersection())
self.transformations.append(new_file_path)
img.save(new_file_path)
return new_file_path
def addText(fileName, text):
image = Image(fileName)
draw = DrawingLayer((IMAGE_WIDTH, IMAGE_HEIGHT))
draw.rectangle((8, 8), (121, 18), filled=True, color=Color.YELLOW)
draw.setFontSize(20)
draw.text(text, (10, 9), color=Color.BLUE)
image.addDrawingLayer(draw)
image.save(fileName)
def rotate(self, img_path, shoe_measurements):
img = Image(img_path)
new_file_path = self.nfn('rotated')
img = img.rotate(shoe_measurements.toe_heel_angle(),
point=shoe_measurements.cleat_length_intersection())
self.transformations.append(new_file_path)
img.save(new_file_path)
return new_file_path
def correct_alignment(si, image_path):
new_file_path = step_file_path(si, 'correct-alignment')
img = Image(image_path)
if (img.width > img.height):
img.rotate(-90, fixed=False).save(new_file_path)
else:
img.save(new_file_path)
si.step_outputs.append(new_file_path)
return new_file_path
def correct_alignment(self, img_path):
new_file_path = self.nfn('correct-alignment')
img = Image(img_path)
if (img.width > img.height):
img.rotate(-90, fixed=False).save(new_file_path)
else:
img.save(new_file_path)
self.transformations.append(new_file_path)
return new_file_path
def correct_alignment(si, image_path): new_file_path = step_file_path(si, 'correct-alignment') img = Image(image_path) if (img.width > img.height): img.rotate(-90, fixed=False).save(new_file_path) else: img.save(new_file_path) si.step_outputs.append(new_file_path) return new_file_path
def correct_alignment(self, img_path):
new_file_path = self.nfn('correct-alignment')
img = Image(img_path)
if (img.width > img.height):
img.rotate(-90, fixed=False).save(new_file_path)
else:
img.save(new_file_path)
self.transformations.append(new_file_path)
return new_file_path
def run(self):
cam_mode=self.cam_mode
wsh = self.wsh
js = self.js
wsh2 = self.wsh2
d = "n"
c2 = self.c2
c = self.c
sqx = self.sqx
sqy = self.sqy
x = 0
y = 0
stat="live cam"
if cam_mode == 3:
img1 = c2.getImage()
if cam_mode==1:
img1 = c.getImage()
time.sleep(1)
with picamera.PiCamera() as camera:
camera.resolution = (544, 288)
camera.capture('imagesmall.jpg')
img2 = Image('imagesmall.jpg')
time.sleep(.5)
img1 = img1.sideBySide(img2)
img1 = img1.scale(544,288)
time.sleep(.5)
if cam_mode==2:
with picamera.PiCamera() as camera:
camera.resolution = (544, 288)
camera.capture('imagesmall.jpg')
img1 = Image('imagesmall.jpg')
self.img1 = img1
blobs = img1.findBlobs()
if blobs :
##blobs.draw()
img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,255))
img1.drawCircle((blobs[-1].centroid()),10,color=(255,100,100))
blobx1 = blobs[-1].x
bloby1 = blobs[-1].y
print blobx1
print bloby1
img1.drawText("ogp: live cam", 10, 10, fontsize=50)
img1.drawText(str(blobx1), blobx1, 250, color=(255,255,255), fontsize=20)
img1.drawText(str(bloby1), 10, bloby1, color=(255,255,255), fontsize=20)
img1.save(js.framebuffer)
sqx2=sqx+20
sqy2=sqy+20
time.sleep(.5)
wsh.write_message(wsh2, "live")
else:
wsh.write_message(wsh2, "live")
def build_bg():
for n in range(BG_PICS):
pn = bgname.format(n)
save_picture(pn)
sleep(FRAME_DELAY)
camera.stop_preview()
frames = ImageSet()
frames.load(bgdir)
img = Image(frames[0].size())
nframes = len(frames)
for frame in frames:
img = img + (frame / nframes)
img.save(bgf)
return img
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 activaCamara(): """ Se activa la camara para detectar movimiento utilizando el algormitmo running segmentation de SimpleCV""" global proximo screenLength = resolucion[0] min_blob_size = screenLength * 0.15 max_blob_size = screenLength * 0.75 ahora = datetime.datetime.now() img = util.tomaFoto(filename,brillo,resolucion,modoExposicion) rs.addImage(img) diffImg = rs.getSegmentedImage(False) if diffImg is not None: blobs = diffImg.dilate(3).findBlobs() if blobs is not None : print screenLength, min_blob_size, blobs[-1].length(), max_blob_size if blobs[-1].length() > min_blob_size and blobs[-1].length() < max_blob_size : print "El sensor ha detectado algo relevante" mensaje = 'Alerta ' + str(ahora) + ".jpg" imagen = Image (filename) os.chdir(RUTA_BASE_LOCAL_ALERTAS) blobs.image = imagen blobs[-1].draw(width=5, color=Color.GREEN) imagen.drawText(str(ahora), x= 20, y =10, fontsize=25) imagen.save(str(ahora)+'.jpg') os.chdir(RUTA_BASE_LOCAL) destinatarios = ['*****@*****.**', '*****@*****.**'] mensaje = 'Alerta de la alarma, visita https://www.dropbox.com para ver las fotos' mandaMensaje(mensaje, destinatarios) # --------------------------------------------- # Foto a intervalos regulares # --------------------------------------------- if ahora > proximo : print "tomada foto de cada hora" camara.tomaFoto(str(ahora) + ".jpg", brillo=50,resolucion=(640,480),preview=False,modoExposicion='auto') proximo = datetime.datetime.now() + periodo
def drawImage():
#Load Map
d = Display((1240, 820), title="London Map - Scotland Yard")
lMap = Image("maps/map.jpg")
#Check Position from players
#See corresponding pixel in list
#Draw Circle from players
circlesLayer = DrawingLayer((lMap.width, lMap.height))
circlesLayer.circle ((191,44), 20,color=Color.BLACK, filled=True, alpha = 255)
lMap.addDrawingLayer(circlesLayer)
#Display
lMap.applyLayers()
lMap.save(d)
'''Later create a "draw possibilites" areas in map for thief '''
def Run(cmdPipe):
steadyStateFPS = 10
desiredBuffer = 60*60 #1 minute * 60 seconds
numberOfFrames = steadyStateFPS*desiredBuffer;
fmt = '%Y-%m-%d %H:%M:%S'
disp = Display()
filelist = []
frameCounter = 101
sleepTime = .1
while disp.isNotDone():
# check command
if cmdPipe.poll():
cmd = cmdPipe.recv()
if cmd=='shutdown':
print('player', 0, "Shutting down.")
break
if frameCounter > 100 or len(filelist) == 0:
frameCounter = 0
filelist = glob("images/*.jpg")
if len(filelist)>numberOfFrames:
sleepTime = 1.0/steadyStateFPS
print("player", 0, "number of frames in buffer="+str(len(filelist))+" desired="+str(numberOfFrames)+" setting sleeptime to "+str(sleepTime))
else:
sleepTime = (1.0/steadyStateFPS)+.01
print("player", 0, "number of frames in buffer="+str(len(filelist))+" desired="+str(numberOfFrames)+" setting sleeptime to "+str(sleepTime))
filename = filelist.pop(0)
img = Image(filename)
matchObj = re.search(r'[0-9- :]+', filename)
d1_ts = time.mktime(datetime.strptime(matchObj.group(), fmt).timetuple())
d2_ts = time.mktime(datetime.utcnow().timetuple())
offset = int(d1_ts-d2_ts)/60
img.drawText(str(offset), x=600, y=470)
img.save(disp)
os.remove(filename)
frameCounter = frameCounter+1
time.sleep(sleepTime)
class Scale:
global db, Gd
name = "Scale"
def __init__(self, fname):
self.img = Image(fname)
if not fname == "input.png":
self.img.save("input.png")
self.cropped = Cropx(self.img) # crop image
self.cropped.save("cropTest.png") # save intermediat results
[self.wt, self.fat, self.h2o] = Part(self, self.cropped) # partition cropped image
self.fat.save("fatTest.png")
self.h2o.save("h2oTest.png")
self.wt.save("wtTest.png")
# hunt for the appropriate number in each partitioned image
self.nwt = hunt(self.wt, "wt")
self.nfat = hunt(self.fat, "fat")
self.nh2o = hunt(self.h2o, "h2o")
return None
def save_trained_image(train_as, img):
image = Image(img)
trainPath = CLASSIFIER_TRAIN_PATH + '/' + train_as
# make sure the train/{class} directory exist
if not os.path.exists(trainPath):
os.makedirs(trainPath)
imageName = os.path.basename(img)
(filename, fileext) = os.path.splitext(imageName)
# make sure imageName is not duplicated by seq number
uniq = 1
imagePath = '%s/%s_%03d%s' % (trainPath, train_as, uniq, fileext)
while os.path.exists(imagePath):
imagePath = '%s/%s_%03d%s' % (trainPath, train_as, uniq, fileext)
uniq += 1
image.save(imagePath)
log("save_trained_image(train_as=%s, img=%s, saved=%s)" % (train_as, img, imagePath))
return {
"image": img,
"class": train_as,
"saved": imagePath
}
def get_image(url, file_name, dir='images/'):
"""Return PIL.Image
Get 'file_name' at 'dir'
if the file doesn't exists it download it and save it at dir+file_name
otherwise if the files exists open the file and return the reference
"""
img = None
if file_name:
output_file = dir + file_name if dir else file_name
if file_name in os.listdir(dir):
img = Image(output_file)
elif url:
buff = StringIO(get_web_content(url))
img = Image(buff)
img.save(output_file)
else:
print 'Error Impossible to get images files'
return img
def generate_negative_examples(argv):
image_dirs = argv[4:]
images = []
for image_dir in image_dirs:
# grab all images
images.extend(glob(path.join(image_dir, '*.jpg')))
images.extend(glob(path.join(image_dir, '*.JPG')))
images.extend(glob(path.join(image_dir, '*.png')))
images.extend(glob(path.join(image_dir, '*.PNG')))
images = set(images)
if len(images) < N:
print 'Not enough images! (got %d, need %d)' % (len(images), N)
return
width, height, output_dir = int(argv[1]), int(argv[2]), argv[3]
if path.exists(output_dir) and (not path.isdir(output_dir)):
print '%s is not a directory' % output_dir
return
elif not path.exists(output_dir):
os.mkdir(output_dir)
for i in xrange(N):
print 'generating %3d/%d...' % ((i+1), N)
img = Image(images.pop())
img = img.grayscale()
if img.width > MAX_WIDTH:
img = img.resize(MAX_WIDTH, int(1.0*img.height*MAX_WIDTH/img.width))
x, y = random.randint(0, img.width-width), random.randint(0, img.height-height)
img = img.crop(x, y, width, height)
path_to_save = path.join(output_dir, '%d.png' % (i+1))
img.save(path_to_save)
def detectCenter(image_file):
original = Image(image_file)
center_only = original.colorDistance((155,9,49))*8
mask = center_only.invert()
#mask.save("center_mask.jpg")
binarizedMask = mask.binarize().invert()
#binarizedMask.save("binarized_mask_center.jpg")
blobs = original.findBlobsFromMask(binarizedMask)
if blobs == None :
#print "No red found"
return detectGreenLowQuality(image_file)
bestBlob = blobs[-1]
bestBlob.drawMinRect(color=Color.RED,width =10)
bestBlob.image = original
original.save("align.png")
centroidX = bestBlob.minRectX()
centroidY = bestBlob.minRectY()
#Have to find out which part of the screen centroid is in
maxX = original.getNumpy().shape[0]
maxY = original.getNumpy().shape[1]+100
#assume width of 150 pixels
return align_center(maxX,maxY,centroidX,centroidY,80,80)
class Window:
world_size = 100
img_size = (world_size, world_size)
generation = 0
def __init__(self):
self.display = Display(self.img_size)
self.img = Image(self.img_size)
self.img.save(self.display)
def dot(self, x, y, size=0, color=Color.WHITE):
x = int(round(x))
y = int(round(y))
#print "Drawing robot particle at {}, {}".format(x, y)
self.img.dl().circle((x, y), size, color, filled=True)
def dot_red(self, x, y):
self.dot(x, y, 2, Color.RED)
def dots(self, coords, size=0, color=Color.WHITE):
for (x, y) in coords:
self.dot(x, y, size, color)
def clear(self):
self.img = Image(self.img_size)
#self.display.clear()
self.img.save(self.display)
def show(self):
self.img.save(self.display)
self.generation += 1
print "Generation = {}".format(self.generation)
self.wait_for_mouse()
def wait_for_mouse(self):
while True:
for event in pg.event.get():
if event.type == pg.MOUSEBUTTONDOWN:
print event
self.clear()
return
def rotate_and_resize(si, left_sm, right_sm):
new_file_path = step_file_path(si, 'rotate')
img = Image(si.step_outputs[-1:][0])
rot = right_sm.toe_heel_angle() + left_sm.toe_heel_angle()
img = img.rotate(rot, fixed=True)
si.step_outputs.append(new_file_path)
img.save(new_file_path)
scale = left_sm.shoe_length() / right_sm.shoe_length()
new_file_path = step_file_path(si, 'scale-length')
img = img.scale(scale)
si.step_outputs.append(new_file_path)
img.save(new_file_path)
# We also resize the original file
orig_img = Image(si.step_outputs[0])
orig_img = orig_img.rotate(rot, fixed=True)
orig_img = orig_img.scale(scale)
new_file_path = step_file_path(si, 'transformed-original')
si.step_outputs.append(new_file_path)
orig_img.save(new_file_path)
return new_file_path
def rotate_and_resize(si, left_sm, right_sm): new_file_path = step_file_path(si, 'rotate') img = Image(si.step_outputs[-1:][0]) rot = right_sm.toe_heel_angle() + left_sm.toe_heel_angle() img = img.rotate(rot, fixed=True) si.step_outputs.append(new_file_path) img.save(new_file_path) scale = left_sm.shoe_length() / right_sm.shoe_length() new_file_path = step_file_path(si, 'scale-length') img = img.scale(scale) si.step_outputs.append(new_file_path) img.save(new_file_path) # We also resize the original file orig_img = Image(si.step_outputs[0]) orig_img = orig_img.rotate(rot, fixed=True) orig_img = orig_img.scale(scale) new_file_path = step_file_path(si, 'transformed-original') si.step_outputs.append(new_file_path) orig_img.save(new_file_path) return new_file_path
def run(self):
cam_mode=self.cam_mode
s.write('s')
wsh = self.wsh
js = self.js
wsh2 = self.wsh2
ms = 50
d = "n"
acu = int(1)
acd = int(1)
acl = int(1)
acr = int(1)
c2=self.c2
sqx=self.sqx
sqy=self.sqy
x=0
y=0
stat="centering"
if cam_mode == 3:
img1 = c2.getImage()
if cam_mode==1:
with picamera.PiCamera() as camera:
camera.resolution = (544, 288)
camera.capture('imagesmall.jpg')
img1 = Image('imagesmall.jpg')
if cam_mode==2:
with picamera.PiCamera() as camera:
camera.resolution = (544, 288)
camera.capture('imagesmall.jpg')
img1 = Image('imagesmall.jpg')
self.img1 = img1
blobs = img1.findBlobs()
if blobs :
##blobs.draw()
img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,255))
img1.drawCircle((blobs[-1].centroid()),10,color=(255,100,100))
blobx1 = blobs[-1].x
bloby1 = blobs[-1].y
print blobx1
print bloby1
img1.drawText("ogp: centering", 10, 10, fontsize=50)
img1.drawText(str(blobx1), 10, 200, color=(255,255,255), fontsize=50)
##img1.drawText(str(bloby1), 50, 200, color=(255,255,255), fontsize=50)
img1.drawText(str(bloby1), 10, 250, color=(255,255,255), fontsize=50)
img1.save(js.framebuffer)
sqx2=sqx+20
sqy2=sqy+20
if blobx1 > sqx2:
d = '_r'
s.write('4')
mov = acx(s, d, ms, acu, acd, acl, acr)
mov.run()
wsh.write_message(wsh2, "g_"+ str(d))
if blobx1 < sqx:
d = 'l'
s.write('2')
mov = acx(s, d, ms, acu, acd, acl, acr)
mov.run()
wsh.write_message(wsh2, "g_"+ str(d))
if bloby1 > sqy2:
d = 'd'
s.write('9')
mov = acx(s, d, ms, acu, acd, acl, acr)
mov.run()
wsh.write_message(wsh2, "g_"+ str(d))
if bloby1 < sqy:
d = 'u'
s.write('6')
mov = acx(s, d, ms, acu, acd, acl, acr)
mov.run()
wsh.write_message(wsh2, "g_"+ str(d))
wsh.write_message(wsh2, "c")
else:
wsh.write_message(wsh2, "c_" + "null" )
'This script is used to display the images saved in hdf5 file generated by simpleTrack.py script'
)
print('Call the script with filename as argument, for example:')
print(' python replay.py 20130805_14h03_simpleTrack.hdf5')
print('')
recordFilename = sys.argv[1]
print('Opening file ' + recordFilename)
recordFile = h5py.File(recordFilename, 'r')
imgs = recordFile.get('image')
kite = recordFile.get('kite')
i_time = 0 #index of time column
t = kite[0, i_time]
img = imgs[0, :, :, :, ]
s = img.shape
disp = Display((s[0] * 4, s[1] * 4))
for i_img in range(len(imgs[:, 0, 0, 0])):
dt = kite[i_img, 0] - t
time.sleep(dt)
t = kite[i_img, 0]
time.sleep(0.05)
img = imgs[i_img, :, :, :]
print(dt)
r = img[:, :, 0]
g = img[:, :, 1]
b = img[:, :, 2]
im = Image(img)
im.save(disp)
ret, frame = cap.read()
blob = b.detect(frame)
fcount = 0
for beest in blob:
if fcount > 100:
continue
tmpImg = Image(frame, cv2image=True).crop(int(beest.pt[0]),
int(beest.pt[1]),
box_dim,
box_dim,
centered=True)
if ((tmpImg.width + tmpImg.height) == 2 * box_dim):
# cv2.imshow('classify',tmpImg.getNumpyCv2())
tmpImg.save(display)
result = tkMessageBox.askquestion(
"Wildebeest!",
"Is this one? (no if you don't know)",
icon='warning',
type='yesnocancel')
if result == 'yes':
save_path = "yes/img-" + str(counter) + ".png"
tmpImg.save(save_path)
fcount += 1
counter += 1
if result == 'no':
save_path = "no/img-" + str(counter) + ".png"
tmpImg.save(save_path)
counter += 1
if result == 'cancel':
##b=histograma(imgGray)
b = imgGray.binarize(50)
ainv = imgGray.binarize(100)
a=ainv.__invert__()
##b.show()
##pylab.figure(1)
##pylab.subplot(311), a.show(), pylab.title('Imagen Original')
##a.show()
##histograma(imgGray)
##pylab.subplot(312), b.show(), pylab.title('Imagen Invertida')
##b.show()
a.save("a.png")
b.save("b.png")
ainv.save("ainv.png")
orig = cv2.imread("hola5Gray.png")
ainv = cv2.imread("ainv.png")
h=imgGray.histogram(255)
a = cv2.imread("a.png")
b = cv2.imread("b.png")
c=cv2.add(a,b)
pylab.subplot(2,2,1)
pylab.imshow(orig)
pylab.title('Imagen Original')
pylab.subplot(2,2,2)
from SimpleCV import Display, Image, Color
winsize = (640, 480)
display = Display(winsize)
img = Image(winsize)
img.save(display)
while not display.isDone():
if display.mouseLeft:
img.dl().circle((display.mouseX, display.mouseY), 5,
Color.RED, filled=True)
img.save(display)
img.save("art.png")
def detectChargingStation(image_file):
debug = False
myColor1 = (8,33,64)
myColor2 = (70,80,100)
original = Image(image_file)
only_station = onlyBlueColor(original, myColor1)
#Different findBlobs
maskMean = original.hueDistance(color=(200,160,150))
mask = only_station.hueDistance(color=myColor1).binarize()
meanColor = (round(((maskMean.meanColor()[0]+maskMean.meanColor()[1]+maskMean.meanColor()[2])/3) * 10000)/10000)
blobs = original.findBlobsFromMask(mask, minsize=400)
if(meanColor > 190):
return 6
#print "Number of blobs found" , len(blobs)
try:
blobs.image = original
except Exception:
only_station = onlyBlueColor(original, myColor2)
mask = only_station.hueDistance(color=myColor2).binarize()
blobs = original.findBlobsFromMask(mask, minsize=400)
blobs.image = original
station_blob = chooseBestBlobCosine(blobs)
station_blob.drawMinRect(color=Color.RED)
centroidX = station_blob.minRectX()
centroidY = station_blob.minRectY()
#Have to find out which part of the screen centroid is in
maxX = original.getNumpy().shape[0]
maxY = original.getNumpy().shape[1]+100
if(debug):
centroidLayer = DrawingLayer((maxX,maxY))
centroidLayer.line((0,(1/3.0)*maxY),(maxX, (1/3.0)*maxY), color=Color.GREEN, width=2)
centroidLayer.line((0,(2/3.0)*maxY),(maxX, (2/3.0)*maxY), color=Color.GREEN, width=2)
centroidLayer.circle((int(centroidX), int(centroidY)), color=Color.GREEN, radius=5, filled=True)
original.addDrawingLayer(centroidLayer)
original.applyLayers()
mask.save("binarizeMask.png")
original.save("blobs.png")
only_station.save("blueFilter.png")
#print "Coordinates of centroid are "+str(centroidX)+", "+str(centroidY)
#print "Coordinates of max are "+str(maxX)+", "+str(maxY)
#if(station_blob.width() * station_blob.height() < 4000):
# return 2
blobArea = station_blob.width() * station_blob.height()
if(blobArea < 10000):
return 2
return chargingStationLocation_New(maxX,maxY,centroidX,centroidY,200, station_blob.width() / float(station_blob.height()), blobArea)
import socket
from PIL import Image as pil
from cStringIO import StringIO
from SimpleCV import Image, Display
display = Display()
HOST = "192.168.2.19"
PORT = 8000
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.bind((HOST, PORT))
s.listen(1)
conn, addr = s.accept()
print "Connected by", addr
while 1:
b = ""
while 1:
data = conn.recv(1024)
if not data:
break
b += data
if len(b) > 0:
img = Image(pil.open(StringIO(b)))
img.save(display)
# -*- coding: utf-8 -*-
from SimpleCV import Display, Image, Color
winsize = (640, 480)
display = Display(winsize)
img = Image(winsize)
img.save(display)
while not display.isDone():
if display.mouseLeft:
img.dl().circle((display.mouseX, display.mouseY),
4,
Color.WHITE,
filled=True)
img.save(display)
img.save("ex7.png")
from SimpleCV import Image, DrawingLayer, Color
from time import sleep
raspberryImage = Image("raspberries.jpg")
myDrawingLayer = DrawingLayer((raspberryImage.width, raspberryImage.height))
myDrawingLayer.rectangle((50,20), (250, 60), filled=True)
myDrawingLayer.setFontSize(45)
myDrawingLayer.text("Raspberries!", (50, 20), color=Color.WHITE)
raspberryImage.addDrawingLayer(myDrawingLayer)
raspberryImage.applyLayers()
raspberryImage.save("raspberries-titled.jpg")
# run this from X environment (rdp)
from SimpleCV import Image, Display
from time import sleep
myDisplay = Display()
rImage = Image("test.jpg")
rImage.save(myDisplay)
while not myDisplay.isDone():
sleep(0.1)
# -*- coding: utf-8 -*-
from SimpleCV import Display, Image
import time
img = Image("img-ex1.png")
display = Display()
img.save(display)
time.sleep(5)
exit()
from SimpleCV import Image
img = Image('ex15.png')
# Retrieve the RGB triplet from (100, 100)
(red, green, blue) = img.getPixel(100, 100)
# Change the color of the pixel(100,100)
img[100, 100] = (0, 0, blue)
# Show the image for feel seconds
img.show()
# Saves the result image with a diferent name
img.save('ex15-result.png')
# -*- coding: utf-8 -*-
from SimpleCV import Image
imgJPG = Image("ex8.jpg")
imgJPG.save("ex8PNG.png")
imgPNG = Image("ex8PNG.png")
imgPNG.resize(800, 600).show()
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~~'
def run(self):
wsh = self.wsh
## c = self.c
js = self.js
wsh2 = self.wsh2
acu = int(1)
acd = int(1)
acl = int(1)
acr = int(1)
irpic = pinoir2(js)
img1 = Image('imagesmall.jpg')
blobs = img1.findBlobs()
img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,255))
img1.drawCircle((blobs[-1].centroid()),10,color=(255,100,100))
acx1 = blobs[-1].x
acy1 = blobs[-1].y
img1.drawText("ogp: autocalibrating", 10, 10, fontsize=50)
img1.drawText(str(acx1), 10, 50, color=(255,255,255), fontsize=20)
img1.drawText(str(acy1), 10, 75, color=(255,255,255), fontsize=20)
img1.save(js.framebuffer)
d = 'r'
ms = 50
s.write('4')
mov = acx(s, d, ms, acu, acd, acl, acr)
mov.run()
time.sleep(1)
img1 = c.getImage()
blobs = img1.findBlobs()
img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,255))
img1.drawCircle((blobs[-1].centroid()),10,color=(255,100,100))
acx2 = blobs[-1].x
acy2 = blobs[-1].y
img1.drawText("ogp: autocalibrating", 10, 10, fontsize=50)
img1.drawText(str(acx1), 10, 50, color=(255,255,255), fontsize=20)
img1.drawText(str(acy1), 10, 75, color=(255,255,255), fontsize=20)
img1.drawText(str(acx2), 40, 50, color=(255,255,255), fontsize=20)
img1.drawText(str(acy2), 40, 75, color=(255,255,255), fontsize=20)
img1.save(js.framebuffer)
d = 'd'
ms = 50
s.write('9')
mov = acx(s, d, ms, acu, acd, acl, acr)
mov.run()
time.sleep(1)
img1 = c.getImage()
blobs = img1.findBlobs()
img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,255))
img1.drawCircle((blobs[-1].centroid()),10,color=(255,100,100))
acx3 = blobs[-1].x
acy3 = blobs[-1].y
img1.drawText("ogp: autocalibrating", 10, 10, fontsize=50)
img1.drawText(str(acx1), 10, 50, color=(255,255,255), fontsize=20)
img1.drawText(str(acy1), 10, 75, color=(255,255,255), fontsize=20)
img1.drawText(str(acx2), 40, 50, color=(255,255,255), fontsize=20)
img1.drawText(str(acy2), 40, 75, color=(255,255,255), fontsize=20)
img1.drawText(str(acx3), 70, 50, color=(255,255,255), fontsize=20)
img1.drawText(str(acy3), 70, 75, color=(255,255,255), fontsize=20)
img1.save(js.framebuffer)
d = 'l'
ms = 50
s.write('2')
mov = acx(s, d, ms, acu, acd, acl, acr)
mov.run()
time.sleep(1)
img1 = c.getImage()
blobs = img1.findBlobs()
img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,255))
img1.drawCircle((blobs[-1].centroid()),10,color=(255,100,100))
acx4 = blobs[-1].x
acy4 = blobs[-1].y
img1.drawText("ogp: autocalibrating", 10, 10, fontsize=50)
img1.drawText(str(acx1), 10, 50, color=(255,255,255), fontsize=20)
img1.drawText(str(acy1), 10, 75, color=(255,255,255), fontsize=20)
img1.drawText(str(acx2), 40, 50, color=(255,255,255), fontsize=20)
img1.drawText(str(acy2), 40, 75, color=(255,255,255), fontsize=20)
img1.drawText(str(acx3), 70, 50, color=(255,255,255), fontsize=20)
img1.drawText(str(acy3), 70, 75, color=(255,255,255), fontsize=20)
img1.drawText(str(acx4), 100, 50, color=(255,255,255), fontsize=20)
img1.drawText(str(acy4), 100, 75, color=(255,255,255), fontsize=20)
img1.save(js.framebuffer)
d = 'u'
ms = 50
s.write('6')
mov = acx(s, d, ms, acu, acd, acl, acr)
mov.run()
time.sleep(1)
img1 = c.getImage()
blobs = img1.findBlobs()
img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,255))
img1.drawCircle((blobs[-1].centroid()),10,color=(255,100,100))
acx5 = blobs[-1].x
acy5 = blobs[-1].y
img1.drawText("ogp: autocalibrating", 10, 10, fontsize=50)
img1.drawText(str(acx1), 10, 50, color=(255,255,255), fontsize=20)
img1.drawText(str(acy1), 10, 75, color=(255,255,255), fontsize=20)
img1.drawText(str(acx2), 40, 50, color=(255,255,255), fontsize=20)
img1.drawText(str(acy2), 40, 75, color=(255,255,255), fontsize=20)
img1.drawText(str(acx3), 70, 50, color=(255,255,255), fontsize=20)
img1.drawText(str(acy3), 70, 75, color=(255,255,255), fontsize=20)
img1.drawText(str(acx4), 100, 50, color=(255,255,255), fontsize=20)
img1.drawText(str(acy4), 100, 75, color=(255,255,255), fontsize=20)
img1.drawText(str(acx5), 130, 50, color=(255,255,255), fontsize=20)
img1.drawText(str(acy5), 130, 75, color=(255,255,255), fontsize=20)
img1.save(js.framebuffer)
cal1 = acx1 - acx2
cal2 = acy2 - acy3
cal3 = acx3 - acx4
cal4 = acy4 = acy5
time.sleep(2)
wsh.write_message(wsh2, "x_" + str(cal1) + "_" + str(cal2) + "_" + str(cal3)+ "_" + str(cal4) )
def histo(self):
cam_mode = self.cam_mode
js = self.js
ms = self.ms
w = self.w
cent = 0
rgb1 = 0
c2 = self.c2
wsh = self.wsh
wsh2 = self.wsh2
s.write('s')
if cam_mode == 3:
img1 = c2.getImage()
if cam_mode==1:
with picamera.PiCamera() as camera:
camera.resolution = (544, 288)
camera.capture('imagesmall.jpg')
img1 = Image('imagesmall.jpg')
if cam_mode==2:
with picamera.PiCamera() as camera:
camera.resolution = (544, 288)
camera.capture('imagesmall.jpg')
img1 = Image('imagesmall.jpg')
self.img1 = img1
blobs = img1.findBlobs()
if blobs:
print "blob"
x = self.x
y = self.y
p = self.p
p = p + 1
img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,255))
img1.drawCircle((blobs[0].centroid()),10,color=(255,100,100))
print blobs[-1].meanColor()
rgb1 = blobs[-1].meanColor()
cent = blobs[-1].centroid()
pth1 = "/var/www/images/image"
pth3 = ".png"
pth = pth1 + str(p) + pth3
print pth
img1.save(pth)
thumbnail = img1.crop(150,25,250,250)
thumbnail = thumbnail.scale(20,20)
thumb1 = "/var/www/images/thumbs/thumb"
thumb3 = ".png"
thumbpath = thumb1 + str(p) + thumb3
print thumbpath
thumbnail.save(thumbpath)
self.p = p
mySet.add((p,x,y,w,cent,rgb1))
self.mySet = mySet
wshx = str(self.x)
wshy = str(self.y)
centroidx = int(cent[0])
centroidy=int(cent[1])
rcolor=rgb1[0]
gcolor=rgb1[1]
bcolor=rgb1[2]
rcolor=int(rcolor)
gcolor=int(gcolor)
bcolor=int(bcolor)
wsh.write_message(wsh2, "rgb_" + str(rcolor)+"_"+str(gcolor)+"_"+str(bcolor))
wsh.write_message(wsh2, "x_" + str(centroidx)+"_"+str(centroidy))
img1.save(js.framebuffer)
wsh.write_message(wsh2, "d_" + wshx + "_" + wshy + "_" + str(p) )
else:
wshx = str(self.x)
wshy = str(self.y)
wsh.write_message(wsh2, wshx + " " + wshy + "dark")
print "dark"
#!/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)
from __future__ import print_function
from SimpleCV import Image, Color, VirtualCamera, Display
import SimpleCV as scv
# # video = VirtualCamera('', 'video')
# display = Display()
# while display.isNotDone():
# img = video.getImage()
# try:
# dist = img - img.colorDistance(Color.RED)
# dist.show()
# except KeyboardInterrupt:
# display.done = True
# if display.mouseRight:
# display.done = True
# display.quit()
img = Image('img/curb.JPG')
img = img.crop(0, 2*img.height/3, img.width, 5*img.height/6)
print(img.meanColor())
# img = img.binarize()
# img.findBlobs().draw()
# ls = img.findLines()
# for l in ls:
# l.draw()
# img.findBlobs().draw()
# img = img.colorDistance(Color.RED)
img.save('img/curb_processed.jpg')
from SimpleCV import Image, DrawingLayer, Color
from time import sleep
#open the image
raspberryImage = Image("raspberry.jpg")
#creates the layer to draw on
myDrawingLayer = DrawingLayer((raspberryImage.width, raspberryImage.height))
#drawings
myDrawingLayer.rectangle((50, 20), (250, 60), filled=True)
myDrawingLayer.setFontSize(45)
myDrawingLayer.text("Raspberry!", (50, 20), color=Color.WHITE)
#overlay
raspberryImage.addDrawingLayer(myDrawingLayer)
raspberryImage.applyLayers()
#save
raspberryImage.save("raspberry-tittled.jpg")
#!/usr/bin/env python
from SimpleCV import Color,Display,Image
display = Display()
while(display.isNotDone()):
img = Image('example.jpg')
barcode = img.findBarcode() #finds barcode data from image
if(barcode is not None): #if there is some data processed
barcode = barcode[0]
result = str(barcode.data)
print result #prints result of barcode in python shell
barcode = [] #reset barcode data to empty set
img.save(display) #shows the image on the screen
#! /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 Image, Display
import time
displayObject = Display()
img = Image('starry_night.png')
print 'Initial: %s' % (img.getPixel(25, 25),)
img.save(displayObject)
time.sleep(3)
hsv = img.toHSV()
print 'HSV: %s' % (hsv.getPixel(25, 25),)
hsv.save(displayObject)
time.sleep(3)
rgb = hsv.toRGB()
print 'RGB: %s' % (rgb.getPixel(25, 25),)
rgb.save(displayObject)
time.sleep(3)
gray = img.grayscale()
def run(self):
wsh = self.wsh
## c = self.c
js = self.js
wsh2 = self.wsh2
acu = int(1)
acd = int(1)
acl = int(1)
acr = int(1)
irpic = pinoir2(js)
img1 = Image('imagesmall.jpg')
blobs = img1.findBlobs()
img1.drawCircle((blobs[-1].x, blobs[-1].y), 30, color=(255, 255, 255))
img1.drawCircle((blobs[-1].centroid()), 10, color=(255, 100, 100))
acx1 = blobs[-1].x
acy1 = blobs[-1].y
img1.drawText("ogp: autocalibrating", 10, 10, fontsize=50)
img1.drawText(str(acx1), 10, 50, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acy1), 10, 75, color=(255, 255, 255), fontsize=20)
img1.save(js.framebuffer)
d = 'r'
ms = 50
s.write('4')
mov = acx(s, d, ms, acu, acd, acl, acr)
mov.run()
time.sleep(1)
img1 = c.getImage()
blobs = img1.findBlobs()
img1.drawCircle((blobs[-1].x, blobs[-1].y), 30, color=(255, 255, 255))
img1.drawCircle((blobs[-1].centroid()), 10, color=(255, 100, 100))
acx2 = blobs[-1].x
acy2 = blobs[-1].y
img1.drawText("ogp: autocalibrating", 10, 10, fontsize=50)
img1.drawText(str(acx1), 10, 50, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acy1), 10, 75, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acx2), 40, 50, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acy2), 40, 75, color=(255, 255, 255), fontsize=20)
img1.save(js.framebuffer)
d = 'd'
ms = 50
s.write('9')
mov = acx(s, d, ms, acu, acd, acl, acr)
mov.run()
time.sleep(1)
img1 = c.getImage()
blobs = img1.findBlobs()
img1.drawCircle((blobs[-1].x, blobs[-1].y), 30, color=(255, 255, 255))
img1.drawCircle((blobs[-1].centroid()), 10, color=(255, 100, 100))
acx3 = blobs[-1].x
acy3 = blobs[-1].y
img1.drawText("ogp: autocalibrating", 10, 10, fontsize=50)
img1.drawText(str(acx1), 10, 50, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acy1), 10, 75, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acx2), 40, 50, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acy2), 40, 75, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acx3), 70, 50, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acy3), 70, 75, color=(255, 255, 255), fontsize=20)
img1.save(js.framebuffer)
d = 'l'
ms = 50
s.write('2')
mov = acx(s, d, ms, acu, acd, acl, acr)
mov.run()
time.sleep(1)
img1 = c.getImage()
blobs = img1.findBlobs()
img1.drawCircle((blobs[-1].x, blobs[-1].y), 30, color=(255, 255, 255))
img1.drawCircle((blobs[-1].centroid()), 10, color=(255, 100, 100))
acx4 = blobs[-1].x
acy4 = blobs[-1].y
img1.drawText("ogp: autocalibrating", 10, 10, fontsize=50)
img1.drawText(str(acx1), 10, 50, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acy1), 10, 75, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acx2), 40, 50, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acy2), 40, 75, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acx3), 70, 50, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acy3), 70, 75, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acx4), 100, 50, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acy4), 100, 75, color=(255, 255, 255), fontsize=20)
img1.save(js.framebuffer)
d = 'u'
ms = 50
s.write('6')
mov = acx(s, d, ms, acu, acd, acl, acr)
mov.run()
time.sleep(1)
img1 = c.getImage()
blobs = img1.findBlobs()
img1.drawCircle((blobs[-1].x, blobs[-1].y), 30, color=(255, 255, 255))
img1.drawCircle((blobs[-1].centroid()), 10, color=(255, 100, 100))
acx5 = blobs[-1].x
acy5 = blobs[-1].y
img1.drawText("ogp: autocalibrating", 10, 10, fontsize=50)
img1.drawText(str(acx1), 10, 50, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acy1), 10, 75, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acx2), 40, 50, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acy2), 40, 75, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acx3), 70, 50, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acy3), 70, 75, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acx4), 100, 50, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acy4), 100, 75, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acx5), 130, 50, color=(255, 255, 255), fontsize=20)
img1.drawText(str(acy5), 130, 75, color=(255, 255, 255), fontsize=20)
img1.save(js.framebuffer)
cal1 = acx1 - acx2
cal2 = acy2 - acy3
cal3 = acx3 - acx4
cal4 = acy4 = acy5
time.sleep(2)
wsh.write_message(
wsh2, "x_" + str(cal1) + "_" + str(cal2) + "_" + str(cal3) + "_" +
str(cal4))
from SimpleCV import Image,Display,DrawingLayer,Color
from time import sleep
myDisplay = Display()
raspberryImage = Image("test.jpg")
myDrawingLayer = DrawingLayer((raspberryImage.width, raspberryImage.height))
myDrawingLayer.rectangle((50,20),(250,60),filled=True)
myDrawingLayer.setFontSize(45)
myDrawingLayer.text("Raspberries!",(50,20),color=Color.WHITE)
raspberryImage.addDrawingLayer(myDrawingLayer)
raspberryImage.applyLayers()
raspberryImage.save(myDisplay)
while not myDisplay.isDone():
sleep(0.1)
def histo(self):
cam_mode = self.cam_mode
js = self.js
ms = self.ms
w = self.w
cent = 0
rgb1 = 0
c2 = self.c2
wsh = self.wsh
wsh2 = self.wsh2
s.write('s')
if cam_mode == 3:
img1 = c2.getImage()
if cam_mode == 1:
with picamera.PiCamera() as camera:
camera.resolution = (544, 288)
camera.capture('imagesmall.jpg')
img1 = Image('imagesmall.jpg')
if cam_mode == 2:
with picamera.PiCamera() as camera:
camera.resolution = (544, 288)
camera.capture('imagesmall.jpg')
img1 = Image('imagesmall.jpg')
self.img1 = img1
blobs = img1.findBlobs()
if blobs:
print "blob"
x = self.x
y = self.y
p = self.p
p = p + 1
img1.drawCircle((blobs[-1].x, blobs[-1].y),
30,
color=(255, 255, 255))
img1.drawCircle((blobs[0].centroid()), 10, color=(255, 100, 100))
print blobs[-1].meanColor()
rgb1 = blobs[-1].meanColor()
cent = blobs[-1].centroid()
pth1 = "/var/www/images/image"
pth3 = ".png"
pth = pth1 + str(p) + pth3
print pth
img1.save(pth)
thumbnail = img1.crop(150, 25, 250, 250)
thumbnail = thumbnail.scale(20, 20)
thumb1 = "/var/www/images/thumbs/thumb"
thumb3 = ".png"
thumbpath = thumb1 + str(p) + thumb3
print thumbpath
thumbnail.save(thumbpath)
self.p = p
mySet.add((p, x, y, w, cent, rgb1))
self.mySet = mySet
wshx = str(self.x)
wshy = str(self.y)
centroidx = int(cent[0])
centroidy = int(cent[1])
rcolor = rgb1[0]
gcolor = rgb1[1]
bcolor = rgb1[2]
rcolor = int(rcolor)
gcolor = int(gcolor)
bcolor = int(bcolor)
wsh.write_message(
wsh2,
"rgb_" + str(rcolor) + "_" + str(gcolor) + "_" + str(bcolor))
wsh.write_message(wsh2,
"x_" + str(centroidx) + "_" + str(centroidy))
img1.save(js.framebuffer)
wsh.write_message(wsh2, "d_" + wshx + "_" + wshy + "_" + str(p))
else:
wshx = str(self.x)
wshy = str(self.y)
wsh.write_message(wsh2, wshx + " " + wshy + "dark")
print "dark"
def get_bounding_box(keyword, url, filename):
# get the image
img = Image(url)
# resize the image so things aren't so slow, if necessary
w, h = img.size()
if w > 1200 or h > 1200:
maxdim = max(w, h)
ratio = math.ceil(maxdim/800.0)
print " resizing..."
img = img.resize(w=int(w/ratio), h=int(h/ratio))
else:
ratio = 1
# get the canvas
disp = Display((800, 800))
# text overlay
textlayer = DrawingLayer(img.size())
textlayer.setFontSize(30)
cx, cy = 10, 10
for xoff in range(-2, 3):
for yoff in range(-2, 3):
textlayer.text(keyword, (cx + xoff, cy + yoff), color=Color.BLACK)
textlayer.text(keyword, (cx, cy), color=Color.WHITE)
# two points to declare a bounding box
point1 = None
point2 = None
while disp.isNotDone():
cursor = (disp.mouseX, disp.mouseY)
if disp.leftButtonUp:
if point1 and point2:
point1 = None
point2 = None
if point1:
point2 = disp.leftButtonUpPosition()
else:
point1 = disp.leftButtonUpPosition()
bb = None
if point1 and point2:
bb = disp.pointsToBoundingBox(point1, point2)
elif point1 and not point2:
bb = disp.pointsToBoundingBox(point1, cursor)
img.clearLayers()
drawlayer = DrawingLayer(img.size())
if bb:
drawlayer.rectangle((bb[0], bb[1]), (bb[2], bb[3]), color=Color.RED)
# keyboard commands
if pygame.key.get_pressed()[pygame.K_s]:
# skip for now
raise Skip()
elif pygame.key.get_pressed()[pygame.K_b]:
# mark it as an invalid picture
raise BadImage()
elif pygame.key.get_pressed()[pygame.K_RETURN]:
if point1 and point2:
bb = disp.pointsToBoundingBox(scale(ratio, point1), scale(ratio, point2))
return bb
elif not point1 and not point2:
bb = disp.pointsToBoundingBox((0, 0), (w, h))
return bb
drawlayer.line((cursor[0], 0), (cursor[0], img.height), color=Color.BLUE)
drawlayer.line((0, cursor[1]), (img.width, cursor[1]), color=Color.BLUE)
#drawlayer.circle(cursor, 2, color=Color.BLUE, filled=True)
img.addDrawingLayer(textlayer)
img.addDrawingLayer(drawlayer)
img.save(disp)
#!/usr/bin/env python
# author: Powen Ko
from SimpleCV import Image, Display
from time import sleep
import urllib
url="https://chart.googleapis.com/chart?chs=150x150&cht=qr&chl=Hello%20world&choe=UTF-8"
filename="out.jpg"
urllib.urlretrieve(url,filename)
Display1 = Display()
img = Image(filename)
img.save(Display1) # 顯示在畫面上
while not Display1.isDone():
sleep(1)
from SimpleCV import Image, Display
from time import sleep
Display1 = Display()
Image1 = Image("raspberrypi.png")
Image1.save(Display1)
while not Display1.isDone():
sleep(1)
result = Image(output, cv2image=True)
# return result
return result
#disp = Display((800,600))
disp = Display((1296, 972))
vals = []
last = (0, 0)
# Load the video from the rpi
#vc = VirtualCamera("/var/www/html/vid_files/video.h264","video")
# Sometimes there is crud at the begining, buffer it out
#for i in range(0,10):
# img = vc.getImage()
img = Image("pi3.jpg")
img.save(disp)
# Show the user a frame let them left click the center
# of the "donut" and the right inner and outer edge
# in that order. Press esc to exit the display
while not disp.isDone():
test = disp.leftButtonDownPosition()
if (test != last and test is not None):
last = test
vals.append(test)
# 0 = xc yc
# 1 = r1
# 2 = r2
# center of the "donut"
Cx = vals[0][0]
Cy = vals[0][1]
