def mainModule(IP, PORT):
t0 = time.time()
"""
First get an image from Nao, then show it on the screen with PIL.
:param IP:
:param PORT:
"""
myBroker = ALBroker(
"myBroker",
"0.0.0.0", # listen to anyone
0, # find a free port and use it
IP, # parent broker IP
PORT) # parent broker port
camProxy = ALProxy("ALVideoDevice", IP, PORT)
resolution = 2 # VGA
colorSpace = 11 # RGB
videoClient = camProxy.subscribe("python_GVM", resolution, colorSpace, 30)
#get an image from Nao's camera
img0 = getImage(camProxy, videoClient)
#get dictionary of centers
dictOfCenters = shapeDetectionModule.getDetectedShapesCenters(
img0, shapeDetectionModule.dict)
#visualise
frame = shapeDetectionModule.visualize(img0, shapeDetectionModule.dict)
# #printing dictionary of centers:
# print dictOfCenters
#print the list of detected shapes:
for color in ["red", "green", "blue", "yellow"]:
for shape in ["triangle", "square", "circle"]:
print color, shape, dictOfCenters[color][shape]
#place bounding squares and centers on the frame
frame = shapeDetectionModule.outputResults(frame)
#show the recognized image
#showImage('contour', frame)
#save the recognized image
#cv2.imwrite(path+ "/recognizedImage.jpg", frame)
#save the dictionaryOfCenters:
save_obj(dictOfCenters, "dictOfCenters")
camProxy.unsubscribe(videoClient)
t1 = time.time()
total = t1 - t0
print "TOTAL TIME REQUIRED: "
print total
def mainModule(IP, PORT):
"""
First get an image from Nao, then show it on the screen with PIL.
:param IP:
:param PORT:
"""
myBroker = ALBroker(
"myBroker",
"0.0.0.0", # listen to anyone
0, # find a free port and use it
IP, # parent broker IP
PORT) # parent broker port
camProxy = ALProxy("ALVideoDevice", IP, PORT)
cameraIndex = 1
resolution = 2 # VGA
colorSpace = 11 # RGB
#camProxy.setActiveCamera("python_client", cameraIndex)
videoClient = camProxy.subscribeCamera("python_client", cameraIndex,
resolution, colorSpace, 30)
#frame = shapeDetectionModule.visualize(img0, shapeDetectionModule.dict)
#shapeDetectionModule.showImage('contour', frame)
#Change color range
#shapeDetectionModule.setColorLimits("green",(65,50,90),(100,200,200))
dict = {}
#dict=shapeDetectionModule.getDetectedShapesCenters(img0,shapeDetectionModule.dict)
dictColorParameters["green"].append(
shapeDetectionModule.getColorLimits("green"))
# print dictColorParameters
# print dictColorParameters["green"]
# print dictColorParameters["green"][0][0]
# print dictColorParameters["green"][0][1]
for numOfTimes in range(0, 10):
print numOfTimes
#get and process the image:
img0 = getImage(camProxy, videoClient)
dict = shapeDetectionModule.getDetectedShapesCenters(
img0, shapeDetectionModule.dict)
dictNumShapesDetected["green"]["triangle"].append(
len(dict["green"]["triangle"]))
dictNumShapesDetected["green"]["pentagon"].append(
len(dict["green"]["pentagon"]))
dictNumShapesDetected["green"]["square"].append(
len(dict["green"]["square"]))
dictNumShapesDetected["green"]["circle"].append(
len(dict["green"]["circle"]))
if len(dict["green"]["triangle"]) == 1 and len(
dict["green"]["pentagon"]) == 1 and len(
dict["green"]["square"]) == 1 and len(
dict["green"]["circle"]) == 1:
correctlyDetectedCases.append(1)
#shapeDetectionModule.dict=shapeDetectionModule.initDictionary()
print correctlyDetectedCases
print dictNumShapesDetected
original = shapeDetectionModule.convert2pil(img0)
#convert to numpy array
frame = np.asarray(original[:, :])
#array of colors
colors = ["red", "green", "blue", "yellow"]
#array of shapes
shapes = ["triangle", "pentagon", "square", "circle"]
#iterate over all colors and show contours of shape of corresponding color
for color in colors:
for shape in shapes:
centers = dict[color][shape]
#print (color+" "+shape+" ",centers)
if len(centers) != 0:
for center in centers:
cv2.circle(frame, (int(center[0]), int(center[1])), 3,
(255, 0, 0), -1)
text = str(int(center[0])) + " , " + str(int(center[1]))
cv2.putText(frame, text, (int(center[0]), int(center[1])),
cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.5,
(255, 255, 255), 1)
cv2.circle(frame, (int(center[0]), int(center[1])), 3,
(0, 255, 0), 1)
shapeDetectionModule.showImage('contour', frame)
cv2.imwrite(path + "/recognizedImage.jpg", frame)
camProxy.unsubscribe(videoClient)
def mainModule(IP, PORT):
"""
First get an image from Nao, then show it on the screen with PIL.
:param IP:
:param PORT:
"""
myBroker = ALBroker("myBroker",
"0.0.0.0", # listen to anyone
0, # find a free port and use it
IP, # parent broker IP
PORT) # parent broker port
camProxy = ALProxy("ALVideoDevice", IP, PORT)
cameraIndex=1
resolution = 2 # VGA
colorSpace = 11 # RGB
#camProxy.setActiveCamera("python_client", cameraIndex)
videoClient = camProxy.subscribeCamera("python_client", cameraIndex, resolution, colorSpace, 30)
# Get a camera image.
# image[6] contains the image data passed as an array of ASCII chars.
naoImage = camProxy.getImageRemote(videoClient)
camProxy.unsubscribe(videoClient)
# Get the image size and pixel array.
imageWidth = naoImage[0]
imageHeight = naoImage[1]
array = naoImage[6]
#Create a PIL Image Instance from our pixel array.
img0= Image.frombytes("RGB", (imageWidth, imageHeight), array)
#Convert to PIL image
original=shapeDetectionModule.convert2pil(img0)
#convert to numpy array
frame=np.asarray(original[:,:])
#frame = shapeDetectionModule.visualize(img0, shapeDetectionModule.dict)
#shapeDetectionModule.showImage('contour', frame)
dict={}
dict=shapeDetectionModule.getDetectedShapesCenters(img0,shapeDetectionModule.dict)
#array of colors
colors=["red","green","blue","yellow"]
#array of shapes
shapes = ["triangle","pentagon","square","circle"]
#iterate over all colors and show contours of shape of corresponding color
for color in colors:
for shape in shapes:
centers=dict[color][shape]
print (color+" "+shape+" ",centers)
if len(centers)!=0:
for center in centers:
cv2.circle(frame, (int(center[0]),int(center[1])), 3, (255, 0, 0), -1)
text=str(int(center[0]))+" , "+str(int(center[1]))
cv2.putText(frame,text, (int(center[0]), int(center[1])), cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.5, (255,255,255),1)
# cv2.circle(frame, center, radius, (0, 255, 0), 1)
shapeDetectionModule.showImage('contour', frame)
cv2.imwrite(path+ "/recognizedImage.jpg", frame)
#TODO
#change the rectangle with min area to just a rectangle:
#
#
# def labelDetectedObject(cnt, frame, text):
# #bounding rectangle
# x,y,w,h = cv2.boundingRect(cnt)
# cv2.rectangle(frame,(x,y),(x+w,y+h),(0,0,255),2)
# center = (int(x+w/2),int(y+h/2))
# centerCoords="( "+str(int(center[0]))+" , "+str(int(center[1]))+" )"
# cv2.putText(frame,text, (int(center[0]), int(center[1])), cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.5, (255,255,255),1)
# cv2.putText(frame,centerCoords, (int(center[0]), int(center[1]+10)), cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.4, (0,255,255),1)
# #put a circle in the center
cv2.circle(frame,center,3,(0, 0, 255),-1,8,0)