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 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 _removeAllButCentralGalaxyCluster(self):
e = self.ellipse
img = self.image
emask = Image(np.zeros((img.width, img.height), dtype=np.uint8))
if e and e.a and e.b and e.a != np.nan and e.b != np.nan:
try:
e.drawOntoLayer(emask)
except:
print "Got exception while processing %s" % self.id
pass
emask = emask.applyLayers().floodFill((img.width/2, img.height/2), color=Color.BLUE)
mask = emask.binarize().invert()
return img.applyBinaryMask(mask)
def constructMask(w, h, offset, expf=1.2):
# Create an alpha blur on the left followed by white
# using some exponential value to get better results
mask = Image((w, h))
offset = int(offset)
for i in range(0, offset):
factor = np.clip((float(i)**expf) / float(offset), 0.0, 1.0)
c = int(factor * 255.0)
#this is oddness in slice, need to submit bug report
mask[i:i + 1, 0:h] = (c, c, c)
mask.drawRectangle(offset,
0,
w - offset,
h,
color=(255, 255, 255),
width=-1)
mask = mask.applyLayers()
return mask
def __call__(self, image):
params = util.utf8convert(self.inspection.parameters)
retVal = []
mask = Image((image.width,image.height))
if( params.has_key('w') and params.has_key('h') and params.has_key('x') and params.has_key('y') ): #rectangle
if( params['x'] + params['w'] < image.width and
params['y'] + params['h'] < image.height and
params['y'] >= 0 and
params['x'] >= 0 ):
mask.drawRectangle(params['x'],params['y'],params['w'],params['h'],width=-1,color=Color.WHITE)
mask = mask.applyLayers()
fs = image.findBlobsFromMask(mask)
ff = M.FrameFeature()
if( fs is not None and len(fs) > 0 ):
#fs[-1].draw()
b = fs[-1]
b.__class__ = BlobRegion
c = b.meanColor()
b.mColor = (int(c[0]),int(c[1]),int(c[2]))
ff.setFeature(b) # a little hacky but I am sure that it works
retVal = [ff]
elif( params.has_key('x') and params.has_key('y') and params.has_key('r') ): # circle
if( params['x'] + params['r'] < image.width and
params['y'] + params['r'] < image.height and
params['x'] - params['r'] >= 0 and
params['y'] - params['r'] >= 0 ):
r = params['r']
x = params['x']
y = params['y']
mask.drawCircle((x,y),r,thickness=-1,color=Color.WHITE)
mask = mask.applyLayers()
fs = image.findBlobsFromMask(mask)
ff = M.FrameFeature()
if( fs is not None and len(fs) > 0 ):
#fs[-1].draw()
b = fs[-1]
b.__class__ = BlobRegion
c = b.meanColor()
b.mColor = (int(c[0]),int(c[1]),int(c[2]))
ff.setFeature(b)
retVal = [ff]
elif( params.has_key('contour') ):
contour = params['contour'] # this may bail out
if( len(contour) >= 3 ):
mask.dl().polygon(contour,filled=True,color=Color.WHITE)
mask = mask.applyLayers()
fs = image.findBlobsFromMask(mask)
ff = M.FrameFeature()
if( fs is not None and len(fs) > 0 ):
#fs[-1].draw()
b = fs[-1]
b.__class__ = BlobRegion
c = b.meanColor()
b.mColor = (int(c[0]),int(c[1]),int(c[2]))
ff.setFeature(b)
retVal = [ff]
if( params.has_key("saveFile") ):
image.save(params["saveFile"])
return retVal
from SimpleCV import Image, Color, Display
# load an image from imgur
img = Image('http://i.imgur.com/lfAeZ4n.png')
# use a keypoint detector to find areas of interest
feats = img.findKeypoints()
# draw the list of keypoints
feats.draw(color=Color.RED)
# show the resulting image.
img.show()
# apply the stuff we found to the image.
output = img.applyLayers()
# save the results.
output.save('juniperfeats.png')
img = Image('stenramchiffontest.jpg')
disp = Display()
img_blurred = img.gaussianBlur((101, 101))
# Make a mask
mask_size = 80
mask = Image((4 * mask_size, 4 * mask_size))
dl = DrawingLayer((4 * mask_size, 4 * mask_size))
# Draw a filled circle in the mask
dl.circle((2 * mask_size, 2 * mask_size),
mask_size,
filled=True,
color=Color.WHITE)
mask.addDrawingLayer(dl)
mask = mask.applyLayers()
blurred_mask = mask.gaussianBlur((101, 101))
t0 = time.time()
# Blur the mask to get progressive blur
n = 3
img_ = img.gaussianBlur((n, n))
old_n = 3
isDown = False
mouseRawXOld = 0
x = 0
while not disp.isDone():
t = time.time()
dt = t - t0
t0 = t
mouseRawX = disp.mouseRawX
from SimpleCV import Image, DrawingLayer, Color, Display
d = Display((1240, 820), title="London Map - Scotland Yard")
lMap = Image("C:\\Users\\flavio\\Documents\\Python\\Scotland Yard\\maps\\map.jpg")
circlesLayer = DrawingLayer((lMap.width, lMap.height))
circlesLayer.circle ((191,44), 20,color=Color.ORANGE, filled=True, alpha = 255)
lMap.addDrawingLayer(circlesLayer)
lMap.applyLayers()
lMap.save(d)
from SimpleCV import Image, Color, Display
# load an image from imgur
img = Image('http://i.imgur.com/lfAeZ4n.png')
# use a keypoint detector to find areas of interest
feats = img.findKeypoints()
# draw the list of keypoints
feats.draw(color=Color.RED)
# show the resulting image.
img.show()
# apply the stuff we found to the image.
output = img.applyLayers()
# save the results.
output.save('juniperfeats.png')
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)
def findMA(path, file_name_without_extension):
eye = Image(path)
(empty, eye_green, emptier) = eye.splitChannels(False)
eye_green = eye_green * 2.5
eye_gray = eye_green.grayscale()
eye_gray = eye_gray.smooth()
#Canny edge detection algorithm. t1 specifies the threshold value to begin an edge. t2 specifies the strength required
#build an edge off of a point found by T2.
eye_edges = eye_gray.edges(t1=70, t2=35)
edge_test = eye_gray + eye_edges
eye_final = eye_edges
#Perform closing to find individual objects
eye_final = eye_final.dilate(2)
eye_final = eye_final.erode()
eye_final = eye_final.dilate(4)
eye_final = eye_final.erode(3)
big_blobs = eye_final.findBlobs(minsize=500)
#create a blank image to mask
masked_image = Image(eye.size())
for b in big_blobs:
#set mask
b.image = masked_image
#draw the blob on your mask
b.draw(color=Color.WHITE)
eye_final = eye_final - masked_image.applyLayers()
eye_final = eye_final.erode()
eye_final = eye_final.grayscale()
print(eye_final[100, 200][0])
print(eye_final[200, 300])
print(eye_final[400, 600])
#eye_final.save("testthis.png")
if eye_final.findBlobs(maxsize=10):
small_blobs = eye_final.findBlobs(maxsize=10)
#create a blank image to mask
masked_small_image = Image(eye.size())
for b in small_blobs:
#set mask
b.image = masked_small_image
#draw the blob on your mask
b.draw(color=Color.WHITE)
eye_final = eye_final - masked_small_image.applyLayers()
# print("secondtime")
print(eye_final[100, 200])
print(eye_final[200, 300])
print(eye_final[400, 600])
if eye_final.findBlobs():
final_blobs = eye_final.findBlobs()
#Filter through objects to find only potential microaneurysms
masked_circle_image = Image(eye.size())
for b in final_blobs:
blob_height = b.height()
blob_width = b.width()
width_height_diff = abs(blob_height - blob_width)
if (width_height_diff > .2 * blob_height) | (width_height_diff >
.2 * blob_width):
b.image = masked_circle_image
b.draw(color=Color.WHITE)
if (b.area() < .45 * blob_height * blob_width):
b.image = masked_circle_image
b.draw(color=Color.WHITE)
#remove large pointless blobs
if (b.area() > 1500):
b.image = masked_circle_image
b.draw(color=Color.WHITE)
#Save different objects
#eye_final.save("Output1.png")
#masked_circle_image.applyLayers().save("Output2.png")
eye_final = eye_final - masked_circle_image.applyLayers()
eye_example = eye_final + eye
# print("third time")
print(eye_final[100, 200])
print(eye_final[200, 300])
print(eye_final[400, 600])
eye_example.save(file_name_without_extension + '_MAoverlay.tif')
print("overlay saved")
eye_final.save(file_name_without_extension + '_MA.tif')
print("MA saved")
# print("fourth time")
print(eye_final[140, 140])
print(eye_final[180, 180])
print(eye_final[350, 350])
# print('lag gye')
return eye_final
big_blobs = eye_final.findBlobs(minsize=500)
#create a blank image to mask
masked_image = Image(eye.size())
for b in big_blobs:
#set mask
b.image = masked_image
#draw the blob on your mask
b.draw(color = Color.WHITE)
eye_final = eye_final - masked_image.applyLayers()
eye_final = eye_final.erode()
#eye_final.save("testthis.png")
if eye_final.findBlobs(maxsize=10):
small_blobs = eye_final.findBlobs(maxsize=10)
#create a blank image to mask
masked_small_image = Image(eye.size())
for b in small_blobs:
#set mask
b.image = masked_small_image
from SimpleCV import Color, Image
import time
img = Image("sportsballs.jpg")
circles = img.findCircle(canny=200, thresh=250, distance=15)
circles.sortArea()
circles.draw(width=4)
circles[0].draw(color=Color.RED, width=4)
img_with_circles = img.applyLayers()
edges_in_image = img.edges(t2=200)
final = img.sideBySide(edges_in_image.sideBySide(img_with_circles)).scale(0.5)
final.show()
time.sleep(15)
invertidos=green.invert()#se invierte la imagen para obtener manchas negras en la foto
blob=invertidos.findBlobs()#se ve si se encuentrasn las mannchas en la foto invertida
blob.show(width=2)
pruebalunar.addDrawingLayer(invertidos.dl())
pruebalunar.show()
pruebalunar.save("porfavorguardate2.png") #guardamos la imagen
#enncontrar manchas por color especifico para el cual tenemos:
brown_distance=green.colorDistance(Color.BLACK).invert()##cmo buscamos de color negro , le pknemos black
blobs2_=brown_distance.findBlobs()
blobs2_.draw(color=Color.PUCE ,width=3)#se va hacer el mismo ejemplo de la guia
brown_distance.show()
green.addDrawingLayer(brown_distance.dl())
green.show()
green.save("Porfavorguaradte5.png")
#lineas=pruebalunar.findLines()
#lineas.draw(width=3)
#pruebalunar.show()
circles=pruebalunar.findCircle(canny=100,thresh=350,distance=15)
circles=circles.sortArea()
circles.draw(width=4)
img_with_circles= pruebalunar.applyLayers()
edges_in_image= pruebalunar.edges(t2=200)
final=pruebalunar.sideBySide(edges_in_image.sideBySide(img_with_circles)).scale(0.5)
final.show()
final.save("porfavorguardate.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)
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)
if __name__ == '__main__':
cam = Camera(0)
img = Image()
samples = 0
coordinates = redCoords = (0,0)
text = " "
while True:
img = cam.getImage()
# Make image black and white
tmp = findRedDot(img)
if (tmp != None):
coordinates= (coordinates[0]+tmp[0][0], coordinates[1]+tmp[0][1])
samples+=1
if samples == 10:
samples = 0
coordinates = (coordinates[0]/10, coordinates[1]/10)
text = str(coordinates)
redCoords = coordinates
coordinates = (0,0)
redcircle = DrawingLayer((img.width, img.height))
redcircle.circle(redCoords, 5, filled=True, color=(0,255,0)) #add circle point 10,10, radius 10.
img.addDrawingLayer(redcircle)
img.applyLayers()
img.drawText(text)
img.show()