def mainForTraining():
import pygamestuff
crosshair = pygamestuff.Crosshair([7, 2], quadratic=False)
vc = cv2.VideoCapture(0) # Initialize the default camera
if vc.isOpened(): # try to get the first frame
(readSuccessful, frame) = vc.read()
else:
print("Could not open camera.")
return
MAX_SAMPLES_TO_RECORD = 999999
recordedEvents = 0
HT = None
while readSuccessful and recordedEvents < MAX_SAMPLES_TO_RECORD and not crosshair.userWantsToQuit:
pupilOffsetXYList = getOffset(frame, allowDebugDisplay=False)
if pupilOffsetXYList is not None: #If we got eyes, check for a click. Else, wait until we do.
if crosshair.pollForClick():
crosshair.clearEvents()
#print( (xOffset,yOffset) )
#do learning here, to relate xOffset and yOffset to screenX,screenY
crosshair.record(pupilOffsetXYList)
print "recorded something"
crosshair.remove()
recordedEvents += 1
if recordedEvents > RANSAC_MIN_INLIERS:
## HT = fitTransformation(np.array(crosshair.result))
resultXYpxpy = np.array(crosshair.result)
features = getFeatures(resultXYpxpy[:, :-2])
featuresAndLabels = np.concatenate(
(features, resultXYpxpy[:, -2:]), axis=1)
HT = RANSACFitTransformation(featuresAndLabels)
print HT
if HT is not None: # draw predicted eye position
currentFeatures = getFeatures(
np.array((pupilOffsetXYList[0], pupilOffsetXYList[1])))
gazeCoords = currentFeatures.dot(HT)
crosshair.drawCrossAt((gazeCoords[0, 0], gazeCoords[0, 1]))
readSuccessful, frame = vc.read()
print "writing"
crosshair.write() #writes data to a csv for MATLAB
vc.release() #close the camera
crosshair.close()
print "HT:\n"
print HT
resultXYpxpy = np.array(crosshair.result)
print "eyeData:\n"
print getFeatures(resultXYpxpy[:, :-2])
print "resultXYpxpy:\n"
print resultXYpxpy[:, -2:]
def mainForTraining():
import pygamestuff
global port
crosshair = pygamestuff.Crosshair([7, 2], quadratic=False)
connection = socketConnection(port)
frame = receiveFrame(connection)
MAX_SAMPLES_TO_RECORD = 999999 # Number of samples to record before crashing
recordedEvents = 0 # Numbers of times you have clicked
HT = None
try:
while recordedEvents < MAX_SAMPLES_TO_RECORD and not crosshair.userWantsToQuit:
pupilOffsetXYList = getOffset(frame, allowDebugDisplay=False)
if pupilOffsetXYList is not None: # If we got eyes, check for a click. Else, wait until we do.
if crosshair.pollForClick(): # Looks for click
print(crosshair.resetRansac)
crosshair.clearEvents() # Resets any events
crosshair.record(
pupilOffsetXYList
) # Relates the XY Offset to the XY Screen
crosshair.remove() # Removes the corsshair
recordedEvents += 1 # Increase recorded event counter
if recordedEvents > RANSAC_MIN_INLIERS: # If enough points have been used for the ransac
resultXYpxpy = np.array(
crosshair.result
) # Creates an array of all the click locations
features = getFeatures(resultXYpxpy[:, :-2])
featuresAndLabels = np.concatenate(
(features, resultXYpxpy[:, -2:]), axis=1)
HT = RANSACFitTransformation(featuresAndLabels)
## print (HT)
if crosshair.resetRansac == True:
recordedEvents = 0
HT = None
print('everything reset')
if HT is not None: # draw predicted eye position
currentFeatures = getFeatures(
np.array((pupilOffsetXYList[0], pupilOffsetXYList[1])))
gazeCoords = currentFeatures.dot(HT)
crosshair.drawCrossAt((gazeCoords[0, 0], gazeCoords[0, 1]))
frame = receiveFrame(connection)
crosshair.write() # writes data to a csv for MATLAB
crosshair.close()
resultXYpxpy = np.array(
crosshair.result
) # This should be able to be saved and inputed in to create a pre-calibrated method
finally:
pass
def mainForTraining2():
import pygamestuff
crosshair = pygamestuff.Crosshair([7, 2], quadratic=False)
vc = cv2.VideoCapture(0) # Initialize the default camera
if vc.isOpened(): # try to get the first frame
(readSuccessful, frame) = vc.read()
else:
raise (Exception("failed to open camera."))
return
MAX_SAMPLES_TO_RECORD = 999999
recordedEvents = 0
HT = None
try:
while readSuccessful and recordedEvents < MAX_SAMPLES_TO_RECORD and not crosshair.userWantsToQuit:
pupilOffsetXYList = getOffset2(frame)
if pupilOffsetXYList is not None: #If we got eyes, check for a click. Else, wait until we do.
if crosshair.pollForClick():
crosshair.clearEvents()
#print( (xOffset,yOffset) )
#do learning here, to relate xOffset and yOffset to screenX,screenY
crosshair.record(pupilOffsetXYList)
print("recorded something")
crosshair.remove()
recordedEvents += 1
print("Recorded Events", recordedEvents)
if recordedEvents > RANSAC_MIN_INLIERS:
resultXYpxpy = np.array(crosshair.result)
minSeedSize = 5
iterations = 800
maxInlierError = 240 #**2
pointX, pointY = ransac.ransac2(
resultXYpxpy, minSeedSize, iterations,
maxInlierError, RANSAC_MIN_INLIERS,
pupilOffsetXYList[0], pupilOffsetXYList[1])
crosshair.drawCrossAt((pointX, pointY))
readSuccessful, frame = vc.read()
print("writing")
crosshair.write() #writes data to a csv for MATLAB
crosshair.close()
finally:
vc.release() #close the camera
def mainEyeTrack():
import pygamestuff
crosshair = pygamestuff.Crosshair([7, 2], quadratic = False)
#crosshair.result = np.genfromtxt('1700wxoffsetyoffsetxy.csv',delimiter=',')
with open("1700wxoffsetyoffsetxy.csv", "rb") as fp: # Unpickling
crosshair.result = pickle.load(fp)
vc = cv2.VideoCapture(1) # Initialize the default camera
if vc.isOpened(): # try to get the first frame
(readSuccessful, frame) = vc.read()
else:
raise(Exception("failed to open camera."))
return
HT = None
try:
file = open("collectedData.txt", "w")
while readSuccessful and not crosshair.userWantsToQuit:
crosshair.checkEsc()
crosshair.clearEvents()
pupilOffsetXYList = getOffset(frame, allowDebugDisplay=False)
if pupilOffsetXYList is not None: #If we got eyes, check for a click. Else, wait until we do.
print "Found eyes"
crosshair.remove()
resultXYpxpy =np.array(crosshair.result)
features = getFeatures(resultXYpxpy[:,:-2])
featuresAndLabels = np.concatenate( (features, resultXYpxpy[:,-2:] ) , axis=1)
HT = RANSACFitTransformation(featuresAndLabels)
print HT
if HT is not None: # draw predicted eye position
print "PREDICTING EYE POSITION"
currentFeatures =getFeatures( np.array( (pupilOffsetXYList[0], pupilOffsetXYList[1]) ))
gazeCoords = currentFeatures.dot(HT)
crosshair.drawCrossAt( (gazeCoords[0,0], gazeCoords[0,1]) )
naive_dt = datetime.now()
file.write(str(gazeCoords[0,0]) + "," + str(gazeCoords[0,1]) + "," + str(naive_dt) + "\n")
readSuccessful, frame = vc.read()
crosshair.close()
file.close()
finally:
vc.release() #close the camera
def mainForTraining():
import pygamestuff
crosshair = pygamestuff.Crosshair([7, 2], quadratic = False)
vc = cv2.VideoCapture(0) # Initialize the default camera
if vc.isOpened(): # try to get the first frame
(readSuccessful, frame) = vc.read()
else:
raise(Exception("failed to open camera."))
return
MAX_SAMPLES_TO_RECORD = 999999
recordedEvents=0
HT = None
try:
while readSuccessful and recordedEvents < MAX_SAMPLES_TO_RECORD and not crosshair.userWantsToQuit:
pupilOffsetXYList = getOffset(frame, allowDebugDisplay=False)
if pupilOffsetXYList is not None: #If we got eyes, check for a click. Else, wait until we do.
if crosshair.pollForClick():
crosshair.clearEvents()
#print( (xOffset,yOffset) )
#do learning here, to relate xOffset and yOffset to screenX,screenY
crosshair.record(pupilOffsetXYList)
print(len(pupilOffsetXYList),"pupil set")
print ("recorded something")
crosshair.remove()
recordedEvents += 1
if recordedEvents > RANSAC_MIN_INLIERS:
## HT = fitTransformation(np.array(crosshair.result))
resultXYpxpy =np.array(crosshair.result)
features = getFeatures(resultXYpxpy[:,:-2])
featuresAndLabels = np.concatenate( (features, resultXYpxpy[:,-2:] ) , axis=1)
HT = RANSACFitTransformation(featuresAndLabels)
print (HT)
if HT is not None: # draw predicted eye position
currentFeatures =getFeatures( np.array( (pupilOffsetXYList[0], pupilOffsetXYList[1]) ))
gazeCoords = currentFeatures.dot(HT)
print(gazeCoords.shape,":Shape of gazecoords")##delete after test
crosshair.drawCrossAt( (gazeCoords[0,0], gazeCoords[0,1]) )
mouse_x = resultXYpxpy[-1,-2]
mouse_y = resultXYpxpy[-1,-1]
two=""
two += str(mouse_x)+str(',') + str(mouse_y)+str(',')
two += str(gazeCoords[0,0])+str(',') + str(gazeCoords[0,1])+str(',')
one.write(two+"\n")
readSuccessful, frame = vc.read()
print ("writing")
crosshair.write() #writes data to a csv for MATLAB
crosshair.close()
print ("HT: ")
print (HT)
resultXYpxpy =np.array(crosshair.result)
print ("eyeData:")
print (getFeatures(resultXYpxpy[:,:-2]))
print ("resultXYpxpy:")
print (resultXYpxpy[:,-2:])
finally:
vc.release() #close the camera
def mainForTraining():
"""
En esta sección comienza la aplicación
"""
import pygamestuff
crosshair = pygamestuff.Crosshair([7, 2], quadratic = False)
vc = cv2.VideoCapture(0) # Initialize the default camera
if vc.isOpened(): # try to get the first frame
(readSuccessful, frame) = vc.read()
else:
raise(Exception("failed to open camera."))
return
MAX_SAMPLES_TO_RECORD = 999999
recordedEvents=0 #numero de fijaciones
HT = None
try:
coords = []
points = 0
clicks = 0
while readSuccessful and recordedEvents < MAX_SAMPLES_TO_RECORD and not crosshair.userWantsToQuit:
points += 1
pupilOffsetXYList = getOffset(frame, allowDebugDisplay=False)
if pupilOffsetXYList is not None: #si se obtienen los dos ojos, espera un click
if crosshair.pollForClick(): #si hace click se agregan los puntos a la calibracion
clicks += 1
print('clicks '+ str(clicks))
crosshair.clearEvents()
#print( (xOffset,yOffset) )
#do learning here, to relate xOffset and yOffset to screenX,screenY
crosshair.record(pupilOffsetXYList)
print ("recorded something")
crosshair.remove()
recordedEvents += 1
if recordedEvents > RANSAC_MIN_INLIERS:
## HT = fitTransformation(np.array(crosshair.result))
resultXYpxpy =np.array(crosshair.result)
features = getFeatures(resultXYpxpy[:,:-2])
featuresAndLabels = np.concatenate( (features, resultXYpxpy[:,-2:] ) , axis=1)
HT = RANSACFitTransformation(featuresAndLabels)
print (HT)
if HT is not None: # dibujar el circulo estimando la mirada
#print('ya empieza la estimacion')
#print(messagebox.askyesnocancel(message="Comenzará la calibración", title="Título"))
fixations = 0
currentFeatures = getFeatures( np.array( (pupilOffsetXYList[0], pupilOffsetXYList[1]) ))
gazeCoords = currentFeatures.dot(HT)
crosshair.drawCrossAt((gazeCoords[0,0], gazeCoords[0,1]))
print(gazeCoords[0,0], gazeCoords[0,1])
coords.append({
'fixation_number': fixations, 'x': gazeCoords[0,0],'y': gazeCoords[0,1] #las fijaciones son los puntos que detecta la aplicacion que un usuario mira
})
fixations += 1
readSuccessful, frame = vc.read()
# print ("writing")
crosshair.write() #writes data to a csv for MATLAB
crosshair.close()
# print ("HT:\n")
# print (HT)
resultXYpxpy = np.array(crosshair.result)
# print ("eyeData:\n")
# print (getFeatures(resultXYpxpy[:,:-2]))
# print ("coordenadas: \n")
# with open('1700wxoffsetyoffsetxy.csv') as tracker:
# fixation = csv.reader(tracker, delimiter=',', quotechar=',', quoting=csv.QUOTE_MINIMAL)
# for index_fixation, row in enumerate(fixation):
# item = {
# 'fixation_number': index_fixation, 'x': row[2],'y': row[3],
# }
# coords.append(item)
finally:
vc.release() #close the camera
makeModel(coords)