def printMat(image):
"""Print out a text representation of an image"""
for row in range(image.rows):
print "[",
for col in range(image.cols):
print cv.mGet(image, row, col),
print "]"
print ""
def ComputeH(n,p1, p2, H): #int i A = cv.CreateMat(2*n, 9, CV_64FC1) U = cv.CreateMat(2*n, 2*n, CV_64FC1) D = cv.CreateMat(2*n, 9, CV_64FC1) V = cv.CreateMat(9, 9, CV_64FC1) cv.SetZero(A) #for(i=0 i<n i++) for i in range(n): # 2*i row cv.Mset(A,2*i,3,-p1[i].x) cv.Mset(A,2*i,4,-p1[i].y) cv.Mset(A,2*i,5,-1) cv.Mset(A,2*i,6,p2[i].y*p1[i].x) cv.Mset(A,2*i,7,p2[i].y*p1[i].y) cv.Mset(A,2*i,8,p2[i].y) # 2*i+1 row cv.Mset(A,2*i+1,0,p1[i].x) cv.Mset(A,2*i+1,1,p1[i].y) cv.Mset(A,2*i+1,2,1) cv.Mset(A,2*i+1,6,-p2[i].x*p1[i].x) cv.Mset(A,2*i+1,7,-p2[i].x*p1[i].y) cv.Mset(A,2*i+1,8,-p2[i].x) # SVD # The flags cause U and V to be returned transposed # Therefore, in OpenCV, A = U^T D V cv.SVD(A, D, U, V, cv.CV_SVD_U_T|cv.CV_SVD_V_T) # take the last column of V^T, i.e., last row of V #for(i=0 i<9 i++) for i in range(9): cv.Mset(H, i/3, i%3, cv.mGet(V, 8, i))
def Normalization(num,p,T): # double scale, tx, ty # double meanx, meany # double value # int i x = cv.CreateMat(3,1,CV_64FC1) xp = cv.CreateMat(3,1,CV_64FC1) meanx = 0 meany = 0 #for(i=0 i<num i++) for i in range(num): meanx += p[i].x meany += p[i].y meanx /= float(num) meany /= float(num) value = 0 #for(i=0 i<num i++) for i in range(num): value += sqrt(pow(p[i].x-meanx, 2.0) + pow(p[i].y-meany, 2.0)) value /= float(num) scale = sqrt(2.0)/value tx = -scale * meanx ty = -scale * meany cv.SetZero(T) cv.mSet(T,0,0,scale) cv.mSet(T,0,2,tx) cv.mSet(T,1,1,scale) cv.mSet(T,1,2,ty) cv.mSet(T,2,2,1.0) #Transform x' = T*x #for(i=0 i<num i++) for i in range(num): cv.mSet(x,0,0,p[i].x) cv.mSet(x,1,0,p[i].y) cv.mSet(x,2,0,1.0) #cvMatMul(T,x,xp) cv.matMulDeriv(T,x,xp) p[i].x = cv.mGet(xp,0,0)/cvmGet(xp,2,0) p[i].y = cv.mGet(xp,1,0)/cvmGet(xp,2,0)
def DartLocation(raw_dart_loc):
try:
if calibration.calibrationComplete:
print "Raw dart location:"
print raw_dart_loc
# temp_raw_loc = cv.CreateMat(3, 3, cv.CV_32FC1)
# cv.mSet(temp_raw_loc, 0, 0, float(raw_dart_loc[0]))
# cv.mSet(temp_raw_loc, 0, 1, float(raw_dart_loc[1]))
# cv.mSet(temp_raw_loc, 0, 2, 1.0)
#
# temp_new_loc = cv.CreateMat(3, 3, cv.CV_32FC1)
#
# cv.Mul(calibration.mapping, temp_raw_loc, temp_new_loc, 1)
#
# new_dart_loc = []
# new_dart_loc = (int( cv.mGet(temp_new_loc, 0, 0)/cv.mGet(temp_new_loc, 0, 2) ), int( cv.mGet(temp_new_loc, 0, 1)/cv.mGet(temp_new_loc, 0, 2) ))
raw_loc_mat = cv.CreateMat(calibration.image.height, calibration.image.width, cv.CV_32FC1)
new_loc_mat = cv.CreateMat(calibration.image.height, calibration.image.width, cv.CV_32FC1)
#y comes before x
cv.mSet( raw_loc_mat, raw_dart_loc[1], raw_dart_loc[0], 1.0 )
cv.WarpPerspective(raw_loc_mat, new_loc_mat, calibration.mapping)
for i in range (0, calibration.image.width):
for j in range(0, calibration.image.height):
if not (cv.mGet(new_loc_mat, j, i) == 0.0):
new_dart_loc = (i, j)
break
print "New dart location:"
print new_dart_loc
return new_dart_loc
#system not calibrated
except AttributeError as err1:
print err1
return (-1, -1)
except NameError as err2:
#not calibrated error
print err2
return (-2, -2)
def getFeatures(R, image, features, threshold):
global algorithm
global TOTAL_FEATURES
global size
if algorithm == 0:
size = SSD_WINDOW_SIZE
if algorithm == 1:
size = NCC_WINDOW_SIZE
feature_number = 0
for i in range(int(size / 2), np.shape(image)[1] - int(size / 2)):
for j in range(int(size / 2), np.shape(image)[0] - int(size / 2)):
if cv.mGet(
R, i, j
) > threshold: #threshold on the c o rne r re sp on se to prune interest points
if feature_number < TOTAL_FEATURES:
feature_number = feature_number + 1
features.append(
Feature(i, j)
) #adds the f e a t u r e t o the f e a t u r e l i s t
print "number of features: ", feature_number
def harrisCornerDetector(image):
image_height = np.shape(image)[0]
image_width = np.shape(image)[1]
#image d e r i v a t i v e al o n g x
# image_der_x = cv.CreateImage ( ( image_width , image_height ) , cv.IPL_DEPTH_32F , 1)
#image d e r i v a t i v e al o n g y
# image_der_y = cv.CreateImage ( ( image_width , image_height ) , cv.IPL_DEPTH_32F , 1)
#g re y s c a l e
grayscale = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
#A p pli e s S o bel Operator t o g e t the image d e r i v a t i v e s al on g x , y
# cv.Sobel ( grayscale_image1 , image_der_x , 1 ,0, 3 )
image_der_x = cv2.Sobel(grayscale, cv2.CV_32F, 1, 0, 3)
# cv.Sobel ( grayscale_image1 , image_der_y , 0, 1, 3 )
image_der_y = cv2.Sobel(grayscale, cv2.CV_32F, 1, 0, 3)
#C al c ul a t e s C
global WINDOW_SIZE #size o f mask
C = cv.CreateMat(2, 2, cv.CV_64FC1)
#v a r i a b l e s f o r SVD
U = cv.CreateMat(2, 2, cv.CV_64FC1)
D = cv.CreateMat(2, 2, cv.CV_64FC1)
I_x = 0
I_xy = 0
I_y = 0
R = cv.CreateMat(image_width, image_height, cv.CV_64FC1)
cv.Zero(R)
#C o n s t r u c t s the v a ri a n c e Matrix a t each p i x e l
#l o o p s through each p i x e l
print "Calculating the Covariance"
for i in range(int(WINDOW_SIZE / 2),
image_width - int(WINDOW_SIZE / 2 + 1)):
for j in range(int(WINDOW_SIZE / 2),
image_height - int(WINDOW_SIZE / 2 + 1)):
I_x = 0
I_xy = 0
I_y = 0
for index_x in range(-int(WINDOW_SIZE / 2),
int(WINDOW_SIZE / 2 + 1)):
for index_y in range(-int(WINDOW_SIZE / 2),
int(WINDOW_SIZE / 2 + 1)):
I_x = I_x + image_der_x[
j + index_y, i + index_x] * image_der_x[
j + index_y, i + index_x] / WINDOW_SIZE
I_xy = I_xy + image_der_x[
j + index_y, i + index_x] * image_der_y[
j + index_y, i + index_x] / WINDOW_SIZE
I_y = I_y + image_der_y[
j + index_y, i + index_x] * image_der_y[
j + index_y, i + index_x] / WINDOW_SIZE
cv.mSet(C, 0, 0, I_x)
cv.mSet(C, 1, 0, I_xy)
cv.mSet(C, 0, 1, I_xy)
cv.mSet(C, 1, 1, I_y)
#svd
cv.SVD(C, D, U, None, 0)
lambda1 = cv.mGet(D, 0, 0)
lambda2 = cv.mGet(D, 1, 1)
#corner Response
cv.mSet(
R, i, j, lambda1 * lambda2 - 0.04 * np.power(
(lambda1 + lambda2), 2))
R_final = cv.CreateMat(image_width, image_height, cv.CV_64FC1)
cv.Copy(R, R_final)
#a p pl y s non maximum s u p p r e s si o n -> el em e n t s o t h e r than maximum v al u e s i n a window are removed
for i in range(int(WINDOW_SIZE / 2), image_width - int(WINDOW_SIZE / 2)):
for j in range(int(WINDOW_SIZE / 2),
image_height - int(WINDOW_SIZE / 2)):
for index_x in range(-int(WINDOW_SIZE / 2),
int(WINDOW_SIZE / 2 + 1)):
for index_y in range(-int(WINDOW_SIZE / 2),
int(WINDOW_SIZE / 2 + 1)):
R_value = cv.mGet(R, i, j)
R_neighbor_value = cv.mGet(R, i + index_x, j + index_y)
if R_value != 0 and R_value < R_neighbor_value:
cv.mSet(R_final, i, j, 0)
break
return R_final
def Calibration():
global image
if from_video:
if from_camera:
capture = cv.CaptureFromCAM(0)
else:
capture = cv.CaptureFromFile(videofile)
## image = 0
cv.SetCaptureProperty(capture, cv.CV_CAP_PROP_FRAME_WIDTH, 640)
cv.SetCaptureProperty(capture, cv.CV_CAP_PROP_FRAME_HEIGHT, 480)
if from_camera:
##we wait for 40 frames...the picture at the very start is always kind of weird,
##wait for the picture to stabalize
for n in range(40):
## RetrieveFrame is just GrabFrame and RetrieveFrame combined into 1
## function call
image = cv.QueryFrame(capture)
## cv.GrabFrame(capture)
## image = cv.CloneImage(cv.RetrieveFrame(capture))
## need to clone this image...otherwise once the capture gets released we won't have access
## to the image anymore
image = cv.CloneImage(cv.QueryFrame(capture))
else:
## if we're capturing from a video file, then just take the first frame
image = cv.QueryFrame(capture)
else:
image = cv.LoadImage(str(r"dartboard_cam1.bmp"),
cv.CV_LOAD_IMAGE_COLOR)
#data we need for calibration:
#mapping for a perspective transform
global mapping
#center of the dartboard in x, y form
global center_dartboard
#initial angle of the 20 - 1 points divider
global ref_angle
#the radii of the rings, there are 6 of them
global ring_radius
global calibrationComplete
calibrationComplete = False
#for grabbing the user's clicks
global points
#either grab data from file or user
while calibrationComplete == False:
#Read calibration file, if exists
if os.path.isfile("calibrationData.pkl"):
try:
#for grabbing key presses in the python window showing the image
global keyPressEvent
keyPressEvent = Event()
global keyPress
#for synchronizing the image window thread
global windowReady
windowReady = Event()
#for synchronizing the drawing
global drawingFinished
drawingFinished = Event()
#start a fresh set of points
points = []
calFile = open('calibrationData.pkl', 'rb')
calData = CalibrationData()
calData = pickle.load(calFile)
#load the data into the global variables
points.append(calData.top)
points.append(calData.bottom)
points.append(calData.left)
points.append(calData.right) #index of 3
init_point_arr = calData.init_point_arr
center_dartboard = calData.center_dartboard
ref_angle = calData.ref_angle
ring_radius = []
ring_radius.append(calData.ring_radius[0])
ring_radius.append(calData.ring_radius[1])
ring_radius.append(calData.ring_radius[2])
ring_radius.append(calData.ring_radius[3])
ring_radius.append(calData.ring_radius[4])
ring_radius.append(
calData.ring_radius[5]) #append the 6 ring radii
#close the file once we are done reading the data
calFile.close()
#copy image for old calibration data
new_image = cv.CloneImage(image)
#have the image in another window and thread
t = Thread(target=CalibrationWindowThread2, args=(new_image, ))
t.start()
#wait for the image window to setup
windowReady.wait()
#now draw them out:
#*******************1. Transform image******************************
newtop = (round(new_image.height / 2),
round(new_image.height * 0.20))
newbottom = (round(new_image.height / 2),
round(new_image.height * 0.80))
#Note: the height is smaller than the width
newleft = (round(new_image.height * 0.20),
round(new_image.height / 2))
newright = (round(new_image.height * 0.80),
round(new_image.height / 2))
mapping = cv.CreateMat(3, 3, cv.CV_32FC1)
#get a fresh new image
new_image = cv.CloneImage(image)
cv.GetPerspectiveTransform(
[points[0], points[1], points[2], points[3]],
[newtop, newbottom, newleft, newright], mapping)
cv.WarpPerspective(image, new_image, mapping)
cv.ShowImage(prev_calibration_window, new_image)
#*******************************************************************
#********************2.Draw points dividers*************************
#find initial angle of the 20-1 divider
tempX_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
#correct the point with respect to the center
cv.mSet(tempX_mat, 0, 0,
init_point_arr[0] - center_dartboard[0])
tempY_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
#adjust the origin of y
cv.mSet(
tempY_mat, 0, 0, init_point_arr[1] -
(new_image.height - center_dartboard[1]))
init_mag_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
init_angle_reversed_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
#each point region is 360/12 = 18 degrees large
cv.CartToPolar(tempX_mat,
tempY_mat,
init_mag_mat,
init_angle_reversed_mat,
angleInDegrees=True)
#display dividers
current_point = (int(round(init_point_arr[0])),
int(round(init_point_arr[1])))
next_angle = cv.CreateMat(1, 1, cv.CV_32FC1)
cv.mSet(next_angle, 0, 0, 360 - ref_angle)
temp_angle = 360.0 - ref_angle
#draw point dividers counterclockwise, just like how angle is calculated, arctan(y/x)
for i in range(0, 20):
cv.Line(new_image, center_dartboard, current_point,
cv.CV_RGB(0, 0, 255), 1, 8)
#calculate the cartesian coordinate of the next point divider
temp_angle = 360.0 - temp_angle
temp_angle += 18.0
if temp_angle >= 360.0:
temp_angle -= 360.0
#make temp_angle reversed
temp_angle = 360.0 - temp_angle
#print temp_angle
cv.mSet(next_angle, 0, 0, temp_angle)
cv.PolarToCart(init_mag_mat,
next_angle,
tempX_mat,
tempY_mat,
angleInDegrees=True)
#current_point = []
#adjust the cartesian points
current_point = (int(
round(cv.mGet(tempX_mat, 0, 0) + center_dartboard[0])),
int(
round(
cv.mGet(tempY_mat, 0, 0) +
(new_image.height -
center_dartboard[1]))))
#print current_point
cv.ShowImage(prev_calibration_window, new_image)
#*************************************************************************
#**********************3. Draw rings**************************************
for i in range(0, 6):
#display the rings
cv.Circle(new_image, center_dartboard, ring_radius[i],
cv.CV_RGB(0, 255, 0), 1, 8)
cv.ShowImage(prev_calibration_window, new_image)
#*************************************************************************
#we are finished drawing, signal
drawingFinished.set()
#wait for key press
print "Previous calibration data detected. Would you like to keep this calibration data? Press 'y' for yes"
#wait indefinitely for a key press
keyPressEvent.wait()
#ASCII 121 is character 'y'
if keyPress == 121:
#we are good with the previous calibration data
calibrationComplete = True
else:
calibrationComplete = False
#delete the calibration file and start over
os.remove("calibrationData.pkl")
#corrupted file
except EOFError as err:
print err
#Manual calibration
else:
#use two events to emulate wait for mouse click event
global e
global key
e = Event()
key = Event()
#start a fresh set of points
points = []
#copy image for manual calibration
new_image = cv.CloneImage(image)
t = Thread(target=CalibrationWindowThread, args=(new_image, ))
t.start()
print "Please select the center of the 20 points outermost rim."
e.wait()
e.clear()
cv.Circle(new_image, points[0], 3, cv.CV_RGB(255, 0, 0), 2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the center of the 3 points outermost rim."
e.wait()
e.clear()
cv.Circle(new_image, points[1], 3, cv.CV_RGB(255, 0, 0), 2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the center of the 11 points outermost rim."
e.wait()
e.clear()
cv.Circle(new_image, points[2], 3, cv.CV_RGB(255, 0, 0), 2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the center of the 6 points outermost rim."
e.wait()
e.clear()
cv.Circle(new_image, points[3], 3, cv.CV_RGB(255, 0, 0), 2, 8)
cv.ShowImage(window_name, new_image)
#calculate the desired circle dimensions
newtop = (round(new_image.height / 2),
round(new_image.height * 0.20))
newbottom = (round(new_image.height / 2),
round(new_image.height * 0.80))
#Note: the height is smaller than the width
newleft = (round(new_image.height * 0.20),
round(new_image.height / 2))
newright = (round(new_image.height * 0.80),
round(new_image.height / 2))
mapping = cv.CreateMat(3, 3, cv.CV_32FC1)
#get a fresh new image
new_image = cv.CloneImage(image)
cv.GetPerspectiveTransform(
[points[0], points[1], points[2], points[3]],
[newtop, newbottom, newleft, newright], mapping)
cv.WarpPerspective(image, new_image, mapping)
cv.ShowImage(window_name, new_image)
print "The dartboard image has now been normalized."
print ""
center_dartboard = []
print "Please select the middle of the dartboard. i.e. the middle of the double bull's eye"
e.wait()
e.clear()
center_dartboard = points[4]
center_dartboard = (int(round(center_dartboard[0])),
int(round(center_dartboard[1])))
cv.Circle(new_image, center_dartboard, 3, cv.CV_RGB(255, 0, 0), 2,
8)
cv.ShowImage(window_name, new_image)
init_point_arr = []
print "Please select the outermost intersection of the 20 points and 1 ponit line."
e.wait()
e.clear()
init_point_arr = points[5]
cv.Circle(new_image, init_point_arr, 3, cv.CV_RGB(255, 0, 0), 2, 8)
cv.ShowImage(window_name, new_image)
#find initial angle of the 20-1 divider
tempX_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
#correct the point with respect to the center
cv.mSet(tempX_mat, 0, 0, init_point_arr[0] - center_dartboard[0])
tempY_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
#adjust the origin of y
cv.mSet(
tempY_mat, 0, 0,
init_point_arr[1] - (new_image.height - center_dartboard[1]))
init_mag_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
init_angle_reversed_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
#each point region is 360/12 = 18 degrees large
cv.CartToPolar(tempX_mat,
tempY_mat,
init_mag_mat,
init_angle_reversed_mat,
angleInDegrees=True)
ref_angle = 360.0 - cv.mGet(init_angle_reversed_mat, 0, 0)
global ref_mag
ref_mag = cv.mGet(init_mag_mat, 0, 0)
#print cv.mGet(init_mag_mat, 0, 0)
#print "Initial angle"
#print init_angle_val
#display dividers
current_point = (int(round(init_point_arr[0])),
int(round(init_point_arr[1])))
next_angle = cv.CreateMat(1, 1, cv.CV_32FC1)
cv.mSet(next_angle, 0, 0, 360 - ref_angle)
temp_angle = 360.0 - ref_angle
#draw point dividers counterclockwise, just like how angle is calculated, arctan(y/x)
for i in range(0, 20):
cv.Line(new_image, center_dartboard, current_point,
cv.CV_RGB(0, 0, 255), 1, 8)
#calculate the cartesian coordinate of the next point divider
temp_angle = 360.0 - temp_angle
temp_angle += 18.0
if temp_angle >= 360.0:
temp_angle -= 360.0
#make temp_angle reversed
temp_angle = 360.0 - temp_angle
#print temp_angle
cv.mSet(next_angle, 0, 0, temp_angle)
cv.PolarToCart(init_mag_mat,
next_angle,
tempX_mat,
tempY_mat,
angleInDegrees=True)
#current_point = []
#adjust the cartesian points
current_point = (
int(round(cv.mGet(tempX_mat, 0, 0) + center_dartboard[0])),
int(
round(
cv.mGet(tempY_mat, 0, 0) +
(new_image.height - center_dartboard[1]))))
#print current_point
cv.ShowImage(window_name, new_image)
ring_arr = []
print "Please select the first ring (any point). i.e. the ring that encloses the double bull's eye."
e.wait()
e.clear()
ring_arr.append(points[6])
cv.Circle(new_image, points[6], 3, cv.CV_RGB(255, 0, 0), 2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the second ring (any point). i.e. the ring that encloses the bull's eye."
e.wait()
e.clear()
ring_arr.append(points[7])
cv.Circle(new_image, points[7], 3, cv.CV_RGB(255, 0, 0), 2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the third ring (any point). i.e. the closer ring that encloses the triple score region."
e.wait()
e.clear()
ring_arr.append(points[8])
cv.Circle(new_image, points[8], 3, cv.CV_RGB(255, 0, 0), 2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the fourth ring (any point). i.e. the further ring that encloses the triple score region."
e.wait()
e.clear()
ring_arr.append(points[9])
cv.Circle(new_image, points[9], 3, cv.CV_RGB(255, 0, 0), 2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the fifth ring (any point). i.e. the closer ring that encloses the double score region."
e.wait()
e.clear()
ring_arr.append(points[10])
cv.Circle(new_image, points[10], 3, cv.CV_RGB(255, 0, 0), 2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the sixth ring (any point). i.e. the further ring that encloses the double score region."
e.wait()
e.clear()
ring_arr.append(points[11])
cv.Circle(new_image, points[11], 3, cv.CV_RGB(255, 0, 0), 2, 8)
cv.ShowImage(window_name, new_image)
ring_radius = []
for i in range(0, 6):
#find the radius of the ring
ring_radius.append(
int(
math.sqrt((ring_arr[i][0] - center_dartboard[0])**2 +
(ring_arr[i][1] - center_dartboard[1])**2)))
#display the rings
cv.Circle(new_image, center_dartboard, ring_radius[i],
cv.CV_RGB(0, 255, 0), 1, 8)
cv.ShowImage(window_name, new_image)
e.wait()
#destroy calibration window
key.set()
#save valuable calibration data into a structure
calData = CalibrationData()
calData.top = points[0]
calData.bottom = points[1]
calData.left = points[2]
calData.right = points[3]
calData.center_dartboard = center_dartboard
calData.init_point_arr = init_point_arr
calData.ref_angle = ref_angle
calData.ring_radius = ring_radius
#write the calibration data to a file
calFile = open("calibrationData.pkl", "wb")
pickle.dump(calData, calFile, 0)
calFile.close()
calibrationComplete = True
def Calibration():
global image
if from_video:
if from_camera:
capture = cv.CaptureFromCAM(0)
else:
capture = cv.CaptureFromFile(videofile)
## image = 0
cv.SetCaptureProperty(capture, cv.CV_CAP_PROP_FRAME_WIDTH, 640)
cv.SetCaptureProperty(capture, cv.CV_CAP_PROP_FRAME_HEIGHT, 480)
if from_camera:
##we wait for 40 frames...the picture at the very start is always kind of weird,
##wait for the picture to stabalize
for n in range(40):
## RetrieveFrame is just GrabFrame and RetrieveFrame combined into 1
## function call
image = cv.QueryFrame(capture)
## cv.GrabFrame(capture)
## image = cv.CloneImage(cv.RetrieveFrame(capture))
## need to clone this image...otherwise once the capture gets released we won't have access
## to the image anymore
image = cv.CloneImage(cv.QueryFrame(capture))
else:
## if we're capturing from a video file, then just take the first frame
image = cv.QueryFrame(capture)
else:
image = cv.LoadImage(str(r"dartboard_cam1.bmp"),cv.CV_LOAD_IMAGE_COLOR)
#data we need for calibration:
#mapping for a perspective transform
global mapping
#center of the dartboard in x, y form
global center_dartboard
#initial angle of the 20 - 1 points divider
global ref_angle
#the radii of the rings, there are 6 of them
global ring_radius
global calibrationComplete
calibrationComplete = False
#for grabbing the user's clicks
global points
#either grab data from file or user
while calibrationComplete == False:
#Read calibration file, if exists
if os.path.isfile("calibrationData.pkl"):
try:
#for grabbing key presses in the python window showing the image
global keyPressEvent
keyPressEvent = Event()
global keyPress
#for synchronizing the image window thread
global windowReady
windowReady = Event()
#for synchronizing the drawing
global drawingFinished
drawingFinished = Event()
#start a fresh set of points
points = []
calFile = open('calibrationData.pkl', 'rb')
calData = CalibrationData()
calData = pickle.load(calFile)
#load the data into the global variables
points.append(calData.top)
points.append(calData.bottom)
points.append(calData.left)
points.append(calData.right) #index of 3
init_point_arr = calData.init_point_arr
center_dartboard = calData.center_dartboard
ref_angle = calData.ref_angle
ring_radius = []
ring_radius.append(calData.ring_radius[0])
ring_radius.append(calData.ring_radius[1])
ring_radius.append(calData.ring_radius[2])
ring_radius.append(calData.ring_radius[3])
ring_radius.append(calData.ring_radius[4])
ring_radius.append(calData.ring_radius[5]) #append the 6 ring radii
#close the file once we are done reading the data
calFile.close()
#copy image for old calibration data
new_image = cv.CloneImage(image)
#have the image in another window and thread
t = Thread(target=CalibrationWindowThread2,args=(new_image,));
t.start()
#wait for the image window to setup
windowReady.wait()
#now draw them out:
#*******************1. Transform image******************************
newtop = (round(new_image.height/2), round(new_image.height * 0.20))
newbottom = (round(new_image.height/2), round(new_image.height * 0.80))
#Note: the height is smaller than the width
newleft = (round(new_image.height * 0.20), round(new_image.height/2))
newright = (round(new_image.height * 0.80), round(new_image.height/2))
mapping = cv.CreateMat(3, 3, cv.CV_32FC1)
#get a fresh new image
new_image = cv.CloneImage(image)
cv.GetPerspectiveTransform([points[0],points[1],points[2],points[3]],[newtop, newbottom, newleft, newright],mapping)
cv.WarpPerspective(image,new_image,mapping)
cv.ShowImage(prev_calibration_window,new_image)
#*******************************************************************
#********************2.Draw points dividers*************************
#find initial angle of the 20-1 divider
tempX_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
#correct the point with respect to the center
cv.mSet( tempX_mat, 0, 0, init_point_arr[0] - center_dartboard[0] )
tempY_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
#adjust the origin of y
cv.mSet( tempY_mat, 0, 0, init_point_arr[1] - (new_image.height - center_dartboard[1]) )
init_mag_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
init_angle_reversed_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
#each point region is 360/12 = 18 degrees large
cv.CartToPolar(tempX_mat, tempY_mat, init_mag_mat, init_angle_reversed_mat, angleInDegrees=True)
#display dividers
current_point = (int(round(init_point_arr[0])), int(round(init_point_arr[1])))
next_angle = cv.CreateMat(1, 1, cv.CV_32FC1)
cv.mSet( next_angle, 0, 0, 360 - ref_angle )
temp_angle = 360.0 - ref_angle
#draw point dividers counterclockwise, just like how angle is calculated, arctan(y/x)
for i in range(0, 20):
cv.Line(new_image, center_dartboard, current_point, cv.CV_RGB(0, 0, 255), 1, 8)
#calculate the cartesian coordinate of the next point divider
temp_angle = 360.0 - temp_angle
temp_angle += 18.0
if temp_angle >= 360.0:
temp_angle -= 360.0
#make temp_angle reversed
temp_angle = 360.0 - temp_angle
#print temp_angle
cv.mSet( next_angle, 0, 0, temp_angle )
cv.PolarToCart(init_mag_mat, next_angle, tempX_mat, tempY_mat, angleInDegrees=True)
#current_point = []
#adjust the cartesian points
current_point = ( int(round( cv.mGet( tempX_mat, 0, 0) + center_dartboard[0] )), int(round( cv.mGet( tempY_mat, 0, 0) + (new_image.height - center_dartboard[1]) ) ))
#print current_point
cv.ShowImage(prev_calibration_window,new_image)
#*************************************************************************
#**********************3. Draw rings**************************************
for i in range(0,6):
#display the rings
cv.Circle(new_image, center_dartboard, ring_radius[i], cv.CV_RGB(0, 255, 0), 1, 8)
cv.ShowImage(prev_calibration_window,new_image)
#*************************************************************************
#we are finished drawing, signal
drawingFinished.set()
#wait for key press
print "Previous calibration data detected. Would you like to keep this calibration data? Press 'y' for yes"
#wait indefinitely for a key press
keyPressEvent.wait()
#ASCII 121 is character 'y'
if keyPress == 121:
#we are good with the previous calibration data
calibrationComplete = True
else:
calibrationComplete = False
#delete the calibration file and start over
os.remove("calibrationData.pkl")
#corrupted file
except EOFError as err:
print err
#Manual calibration
else:
#use two events to emulate wait for mouse click event
global e
global key
e = Event()
key = Event()
#start a fresh set of points
points = []
#copy image for manual calibration
new_image = cv.CloneImage(image)
t = Thread(target=CalibrationWindowThread,args=(new_image,));
t.start()
print "Please select the center of the 20 points outermost rim."
e.wait()
e.clear()
cv.Circle(new_image, points[0], 3,cv.CV_RGB(255, 0, 0),2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the center of the 3 points outermost rim."
e.wait()
e.clear()
cv.Circle(new_image, points[1], 3,cv.CV_RGB(255, 0, 0),2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the center of the 11 points outermost rim."
e.wait()
e.clear()
cv.Circle(new_image, points[2], 3,cv.CV_RGB(255, 0, 0),2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the center of the 6 points outermost rim."
e.wait()
e.clear()
cv.Circle(new_image, points[3], 3,cv.CV_RGB(255, 0, 0),2, 8)
cv.ShowImage(window_name, new_image)
#calculate the desired circle dimensions
newtop = (round(new_image.height/2), round(new_image.height * 0.20))
newbottom = (round(new_image.height/2), round(new_image.height * 0.80))
#Note: the height is smaller than the width
newleft = (round(new_image.height * 0.20), round(new_image.height/2))
newright = (round(new_image.height * 0.80), round(new_image.height/2))
mapping = cv.CreateMat(3, 3, cv.CV_32FC1)
#get a fresh new image
new_image = cv.CloneImage(image)
cv.GetPerspectiveTransform([points[0],points[1],points[2],points[3]],[newtop, newbottom, newleft, newright],mapping)
cv.WarpPerspective(image,new_image,mapping)
cv.ShowImage(window_name,new_image)
print "The dartboard image has now been normalized."
print ""
center_dartboard = []
print "Please select the middle of the dartboard. i.e. the middle of the double bull's eye"
e.wait()
e.clear()
center_dartboard = points[4]
center_dartboard = (int(round(center_dartboard[0])), int(round(center_dartboard[1])))
cv.Circle(new_image, center_dartboard, 3,cv.CV_RGB(255, 0, 0),2, 8)
cv.ShowImage(window_name, new_image)
init_point_arr = []
print "Please select the outermost intersection of the 20 points and 1 ponit line."
e.wait()
e.clear()
init_point_arr = points[5]
cv.Circle(new_image, init_point_arr, 3,cv.CV_RGB(255, 0, 0),2, 8)
cv.ShowImage(window_name, new_image)
#find initial angle of the 20-1 divider
tempX_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
#correct the point with respect to the center
cv.mSet( tempX_mat, 0, 0, init_point_arr[0] - center_dartboard[0] )
tempY_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
#adjust the origin of y
cv.mSet( tempY_mat, 0, 0, init_point_arr[1] - (new_image.height - center_dartboard[1]) )
init_mag_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
init_angle_reversed_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
#each point region is 360/12 = 18 degrees large
cv.CartToPolar(tempX_mat, tempY_mat, init_mag_mat, init_angle_reversed_mat, angleInDegrees=True)
ref_angle = 360.0 - cv.mGet(init_angle_reversed_mat, 0, 0)
global ref_mag
ref_mag = cv.mGet(init_mag_mat, 0, 0)
#print cv.mGet(init_mag_mat, 0, 0)
#print "Initial angle"
#print init_angle_val
#display dividers
current_point = (int(round(init_point_arr[0])), int(round(init_point_arr[1])))
next_angle = cv.CreateMat(1, 1, cv.CV_32FC1)
cv.mSet( next_angle, 0, 0, 360 - ref_angle )
temp_angle = 360.0 - ref_angle
#draw point dividers counterclockwise, just like how angle is calculated, arctan(y/x)
for i in range(0, 20):
cv.Line(new_image, center_dartboard, current_point, cv.CV_RGB(0, 0, 255), 1, 8)
#calculate the cartesian coordinate of the next point divider
temp_angle = 360.0 - temp_angle
temp_angle += 18.0
if temp_angle >= 360.0:
temp_angle -= 360.0
#make temp_angle reversed
temp_angle = 360.0 - temp_angle
#print temp_angle
cv.mSet( next_angle, 0, 0, temp_angle )
cv.PolarToCart(init_mag_mat, next_angle, tempX_mat, tempY_mat, angleInDegrees=True)
#current_point = []
#adjust the cartesian points
current_point = ( int(round( cv.mGet( tempX_mat, 0, 0) + center_dartboard[0] )), int(round( cv.mGet( tempY_mat, 0, 0) + (new_image.height - center_dartboard[1]) ) ))
#print current_point
cv.ShowImage(window_name,new_image)
ring_arr = []
print "Please select the first ring (any point). i.e. the ring that encloses the double bull's eye."
e.wait()
e.clear()
ring_arr.append(points[6])
cv.Circle(new_image, points[6], 3,cv.CV_RGB(255, 0, 0),2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the second ring (any point). i.e. the ring that encloses the bull's eye."
e.wait()
e.clear()
ring_arr.append(points[7])
cv.Circle(new_image, points[7], 3,cv.CV_RGB(255, 0, 0),2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the third ring (any point). i.e. the closer ring that encloses the triple score region."
e.wait()
e.clear()
ring_arr.append(points[8])
cv.Circle(new_image, points[8], 3,cv.CV_RGB(255, 0, 0),2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the fourth ring (any point). i.e. the further ring that encloses the triple score region."
e.wait()
e.clear()
ring_arr.append(points[9])
cv.Circle(new_image, points[9], 3,cv.CV_RGB(255, 0, 0),2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the fifth ring (any point). i.e. the closer ring that encloses the double score region."
e.wait()
e.clear()
ring_arr.append(points[10])
cv.Circle(new_image, points[10], 3,cv.CV_RGB(255, 0, 0),2, 8)
cv.ShowImage(window_name, new_image)
print "Please select the sixth ring (any point). i.e. the further ring that encloses the double score region."
e.wait()
e.clear()
ring_arr.append(points[11])
cv.Circle(new_image, points[11], 3,cv.CV_RGB(255, 0, 0),2, 8)
cv.ShowImage(window_name, new_image)
ring_radius = []
for i in range(0,6):
#find the radius of the ring
ring_radius.append(int(math.sqrt(( ring_arr[i][0] - center_dartboard[0] )** 2 + (ring_arr[i][1] - center_dartboard[1] )** 2)))
#display the rings
cv.Circle(new_image, center_dartboard, ring_radius[i], cv.CV_RGB(0, 255, 0), 1, 8)
cv.ShowImage(window_name,new_image)
e.wait()
#destroy calibration window
key.set()
#save valuable calibration data into a structure
calData = CalibrationData()
calData.top = points[0]
calData.bottom = points[1]
calData.left = points[2]
calData.right = points[3]
calData.center_dartboard = center_dartboard
calData.init_point_arr = init_point_arr
calData.ref_angle = ref_angle
calData.ring_radius = ring_radius
#write the calibration data to a file
calFile = open("calibrationData.pkl", "wb")
pickle.dump(calData, calFile, 0)
calFile.close()
calibrationComplete = True
def DartRegion(dart_loc):
try:
if calibration.calibrationComplete:
print "Finding dart throw information"
dartInfo = GameEngine.dartThrow()
#find the magnitude and angle of the dart
tempX_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
cv.mSet( tempX_mat, 0, 0, dart_loc[0] - calibration.center_dartboard[0] )
tempY_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
#adjust the origin of y to fit a Cartesian plane
cv.mSet( tempY_mat, 0, 0, dart_loc[1] - (calibration.image.height - calibration.center_dartboard[1]) )
dart_mag_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
dart_angle_reversed_mat = cv.CreateMat(1, 1, cv.CV_32FC1)
#each point region is 360/12 = 18 degrees large
cv.CartToPolar(tempX_mat, tempY_mat, dart_mag_mat, dart_angle_reversed_mat, angleInDegrees=True)
dart_angle_val = 360.0 - cv.mGet(dart_angle_reversed_mat, 0, 0)
dartInfo.magnitude = cv.mGet(dart_mag_mat, 0, 0)
dartInfo.angle = dart_angle_val
#Calculating score:
#Find base point
if dart_angle_val < calibration.ref_angle: #make sure dart's angle is always greater
dart_angle_val += 360.0
angleDiffMul = int((dart_angle_val - calibration.ref_angle) / 18.0)
#starting from the 20 points
if angleDiffMul == 0:
dartInfo.base = 20
elif angleDiffMul == 1:
dartInfo.base = 5
elif angleDiffMul == 2:
dartInfo.base = 12
elif angleDiffMul == 3:
dartInfo.base = 9
elif angleDiffMul == 4:
dartInfo.base = 14
elif angleDiffMul == 5:
dartInfo.base = 11
elif angleDiffMul == 6:
dartInfo.base = 8
elif angleDiffMul == 7:
dartInfo.base = 16
elif angleDiffMul == 8:
dartInfo.base = 7
elif angleDiffMul == 9:
dartInfo.base = 19
elif angleDiffMul == 10:
dartInfo.base = 3
elif angleDiffMul == 11:
dartInfo.base = 17
elif angleDiffMul == 12:
dartInfo.base = 2
elif angleDiffMul == 13:
dartInfo.base = 15
elif angleDiffMul == 14:
dartInfo.base = 10
elif angleDiffMul == 15:
dartInfo.base = 6
elif angleDiffMul == 16:
dartInfo.base = 13
elif angleDiffMul == 17:
dartInfo.base = 4
elif angleDiffMul == 18:
dartInfo.base = 18
elif angleDiffMul == 19:
dartInfo.base = 1
else:
#something went wrong
dartInfo.base = -300
#Calculating multiplier (and special cases for Bull's Eye):
for i in range(0, len(calibration.ring_radius)):
print calibration.ring_radius[i]
#Find the ring that encloses the dart
if dartInfo.magnitude <= calibration.ring_radius[i]:
#Bull's eye, adjust base score
if i == 0:
dartInfo.base = 25
dartInfo.multiplier = 2
elif i == 1:
dartInfo.base = 25
dartInfo.multiplier = 1
#triple ring
elif i == 3:
dartInfo.multiplier = 3
#double ring
elif i == 5:
dartInfo.multiplier = 2
#single
elif i == 2 or i == 4:
dartInfo.multiplier = 1
#finished calculation
break
#miss
if dartInfo.magnitude > calibration.ring_radius[5]:
dartInfo.base = 0
dartInfo.multiplier = 0
return dartInfo
#system not calibrated
except AttributeError as err1:
print err1
dartInfo = GameEngine.dartThrow()
return dartInfo
except NameError as err2:
#not calibrated error
print err2
dartInfo = GameEngine.dartThrow()
return dartInfo
