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GetDart.py
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GetDart.py
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__author__ = "Hannes Hoettinger"
import numpy as np
import cv2
import time
import cv2.cv as cv
import math
import pickle
img = cv2.imread("D:\Projekte\PycharmProjects\DartsScorer\Darts\Dartboard_2.png")
img2 = cv2.imread("D:\Projekte\PycharmProjects\DartsScorer\Darts\Dartboard_3.png")
vidcap = cv2.VideoCapture("C:\Users\hanne\OneDrive\Projekte\GitHub\darts\Darts\Darts_Testvideo_9_1.mp4")
from_video = True
DEBUG = True
winName = "test2"
center_dartboard = []
ring_radius = []
transformation_matrix = []
class dartThrow:
def __init__(self):
self.base = -1
self.multiplier = -1
self.magnitude = -1
self.angle = -1
#For file IO
class CalibrationData:
def __init__(self):
#for perspective transform
self.top = []
self.bottom = []
self.left = []
self.right = []
#for calculating the first angle
self.init_point_arr = []
self.center_dartboard = []
#initial angle of the 20 / 1 points divider
self.ref_angle = []
#radii of the rings, there are 6 in total
self.ring_radius = []
self.transformationMatrix = []
## improve and make circle radius accessible
def drawBoard():
raw_loc_mat = np.zeros((800, 800, 3))
# draw board
cv2.circle(raw_loc_mat, (400, 400), 170 * 2, (255, 255, 255), 1) # outside double
cv2.circle(raw_loc_mat, (400, 400), 160 * 2, (255, 255, 255), 1) # inside double
cv2.circle(raw_loc_mat, (400, 400), 107 * 2, (255, 255, 255), 1) # outside treble
cv2.circle(raw_loc_mat, (400, 400), 97 * 2, (255, 255, 255), 1) # inside treble
cv2.circle(raw_loc_mat, (400, 400), 16 * 2, (255, 255, 255), 1) # 25
cv2.circle(raw_loc_mat, (400, 400), 7 * 2, (255, 255, 255), 1) # Bulls eye
# 20 sectors...
sectorangle = 2 * math.pi / 20
i = 0
while (i < 20):
cv2.line(raw_loc_mat, (400, 400), (
int(400 + 170 * 2 * math.cos((0.5 + i) * sectorangle)),
int(400 + 170 * 2 * math.sin((0.5 + i) * sectorangle))), (255, 255, 255), 1)
i = i + 1
return raw_loc_mat
def dist(x1,y1, x2,y2, x3,y3): # x3,y3 is the point
px = x2-x1
py = y2-y1
something = px*px + py*py
u = ((x3 - x1) * px + (y3 - y1) * py) / float(something)
if u > 1:
u = 1
elif u < 0:
u = 0
x = x1 + u * px
y = y1 + u * py
dx = x - x3
dy = y - y3
# Note: If the actual distance does not matter,
# if you only want to compare what this function
# returns to other results of this function, you
# can just return the squared distance instead
# (i.e. remove the sqrt) to gain a little performance
dist = math.sqrt(dx*dx + dy*dy)
return dist
def DartLocation(x_coord,y_coord):
try:
#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
global transformation_matrix
transformation_matrix = calData.transformationMatrix
global 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
global center_dartboard
center_dartboard = calData.center_dartboard
#close the file once we are done reading the data
calFile.close()
#print "Raw dart location:"
#print x_coord,y_coord
# transform only the hit point with the saved transformation matrix
dart_loc_temp = np.array([[x_coord, y_coord]], dtype="float32")
dart_loc_temp = np.array([dart_loc_temp])
dart_loc = cv2.perspectiveTransform(dart_loc_temp, transformation_matrix)
new_dart_loc = tuple(dart_loc.reshape(1, -1)[0])
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)
#Returns dartThrow (score, multiplier, angle, magnitude) based on x,y location
def DartRegion(dart_loc):
try:
height = 800
width = 800
global dartInfo
dartInfo = dartThrow()
#find the magnitude and angle of the dart
vx = (dart_loc[0] - center_dartboard[0])
vy = (center_dartboard[1] - dart_loc[1])
# reference angle for atan2 conversion
ref_angle = 81
dart_magnitude = math.sqrt(math.pow(vx, 2) + math.pow(vy, 2))
dart_angle = math.fmod(((math.atan2(vy,vx) * 180/math.pi) + 360 - ref_angle), 360)
dartInfo.magnitude = dart_magnitude
dartInfo.angle = dart_angle
angleDiffMul = int((dart_angle) / 18.0)
print vx, vy, dart_angle
#starting from the 20 points
if angleDiffMul == 19:
dartInfo.base = 20
elif angleDiffMul == 0:
dartInfo.base = 5
elif angleDiffMul == 1:
dartInfo.base = 12
elif angleDiffMul == 2:
dartInfo.base = 9
elif angleDiffMul == 3:
dartInfo.base = 14
elif angleDiffMul == 4:
dartInfo.base = 11
elif angleDiffMul == 5:
dartInfo.base = 8
elif angleDiffMul == 6:
dartInfo.base = 16
elif angleDiffMul == 7:
dartInfo.base = 7
elif angleDiffMul == 8:
dartInfo.base = 19
elif angleDiffMul == 9:
dartInfo.base = 3
elif angleDiffMul == 10:
dartInfo.base = 17
elif angleDiffMul == 11:
dartInfo.base = 2
elif angleDiffMul == 12:
dartInfo.base = 15
elif angleDiffMul == 13:
dartInfo.base = 10
elif angleDiffMul == 14:
dartInfo.base = 6
elif angleDiffMul == 15:
dartInfo.base = 13
elif angleDiffMul == 16:
dartInfo.base = 4
elif angleDiffMul == 17:
dartInfo.base = 18
elif angleDiffMul == 18:
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(ring_radius)):
#Find the ring that encloses the dart
if dartInfo.magnitude <= 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 > ring_radius[5]:
dartInfo.base = 0
dartInfo.multiplier = 0
return dartInfo
#system not calibrated
except AttributeError as err1:
print err1
dartInfo = dartThrow()
return dartInfo
except NameError as err2:
#not calibrated error
print err2
dartInfo = dartThrow()
return dartInfo
#if breaker == 3:
# break
def getDart():
global finalScore
global transformation_matrix
debug_img = drawBoard()
finalScore = 0
count = 0
breaker = 0
success = 1
## threshold important -> make accessible
x = 3000
# Read first image twice (issue somewhere) to start loop:
t = cv2.cvtColor(vidcap.read()[1], cv2.COLOR_RGB2GRAY)
# wait for camera
time.sleep(0.1)
t = cv2.cvtColor(vidcap.read()[1], cv2.COLOR_RGB2GRAY)
while success:
time.sleep(0.1)
success,image = vidcap.read()
t_plus = cv2.cvtColor(vidcap.read()[1], cv2.COLOR_RGB2GRAY)
dimg = cv2.absdiff(t, t_plus)
# cv2.imshow(winName, edges(t_minus, t, t_plus))
blur = cv2.GaussianBlur(dimg,(5,5),0)
blur = cv2.bilateralFilter(blur,9,75,75)
ret, thresh = cv2.threshold(blur, 60, 255, 0)
if cv2.countNonZero(thresh) > x and cv2.countNonZero(thresh) < 15000: ## threshold important -> make accessible
if from_video:
t_plus = cv2.cvtColor(vidcap.read()[1], cv2.COLOR_RGB2GRAY)
t_plus = cv2.cvtColor(vidcap.read()[1], cv2.COLOR_RGB2GRAY)
t_plus = cv2.cvtColor(vidcap.read()[1], cv2.COLOR_RGB2GRAY)
t_plus = cv2.cvtColor(vidcap.read()[1], cv2.COLOR_RGB2GRAY)
t_plus = cv2.cvtColor(vidcap.read()[1], cv2.COLOR_RGB2GRAY)
else:
time.sleep(0.2)
t_plus = cv2.cvtColor(vidcap.read()[1], cv2.COLOR_RGB2GRAY)
cv2.imshow(winName, t_plus)
dimg = cv2.absdiff(t, t_plus)
## kernel size important -> make accessible
# filter noise from image distortions
kernel = np.ones((8, 8), np.float32) / 40
blur = cv2.filter2D(dimg, -1, kernel)
#blur = cv2.GaussianBlur(dimg,(3,3),1)
#blur = cv2.bilateralFilter(blur,3,10,70) # 10,70
# remove image distortions
#kernel = np.ones((1, 1), np.uint8)
#blur = cv2.morphologyEx(blur, cv2.MORPH_OPEN, kernel)
#kernel = np.ones((1, 1), np.uint8)
# blur = cv2.dilate(blur, kernel, iterations=2)
#blur = cv2.erode(blur, kernel, iterations=1)
# number of features to track is a distinctive feature
#edges = cv2.goodFeaturesToTrack(blur,200,0.01,0,mask=None, blockSize=2, useHarrisDetector=1, k=0.001)
## FeaturesToTrack important -> make accessible
edges = cv2.goodFeaturesToTrack(blur,640,0.0008,3,mask=None, blockSize=3, useHarrisDetector=1, k=0.06) # k=0.08
corners = np.int0(edges)
testimg = blur.copy()
t_plus_copy = t_plus.copy()
# filter corners
cornerdata = []
tt = 0
mean_corners = np.mean(corners, axis=0)
for i in corners:
xl, yl = i.ravel()
## threshold important -> make accessible
# filter noise to only get dart arrow
if abs(mean_corners[0][0] - xl) > 180:
cornerdata.append(tt)
if abs(mean_corners[0][1] - yl) > 120:
cornerdata.append(tt)
tt += 1
corners_new = np.delete(corners, [cornerdata], axis=0) # delete corners to form new array
# find left and rightmost corners
rows,cols = dimg.shape[:2]
[vx,vy,x,y] = cv2.fitLine(corners_new,cv.CV_DIST_HUBER, 0,0.1,0.1)
lefty = int((-x*vy/vx) + y)
righty = int(((cols-x)*vy/vx)+y)
cornerdata = []
tt = 0
for i in corners_new:
xl,yl = i.ravel()
# check distance to fitted line, only draw corners within certain range
distance = dist(0,lefty, cols-1,righty, xl,yl)
if distance < 40: ## threshold important -> make accessible
cv2.circle(testimg,(xl,yl),3,255,-1)
else: # only save corners within certain range
cornerdata.append(tt)
tt += 1
corners_final = np.delete(corners_new, [cornerdata], axis=0) # delete corners to form new array
ret, thresh = cv2.threshold(blur, 60, 255, 0)
## threshold important -> make accessible
if cv2.countNonZero(thresh) > 15000:
continue
x,y,w,h = cv2.boundingRect(corners_final)
cv2.rectangle(t_plus_copy,(x,y),(x+w,y+h),(0,255,0),1)
breaker += 1
# find maximum x distance to dart tip, if camera is mounted on top
maxloc = np.argmax(corners_final, axis=0) # check max pos!!!, write image with circle??!!!
locationofdart = corners_final[maxloc]
try:
# check if dart location has neighbouring corners (if not -> continue)
cornerdata = []
tt = 0
for i in corners_final:
xl, yl = i.ravel()
distance = abs(locationofdart.item(0) - xl) + abs(locationofdart.item(1) - yl)
if distance < 40: ## threshold important -> make accessible
tt += 1
else:
cornerdata.append(tt)
if tt < 3:
corners_temp = cornerdata
maxloc = np.argmax(corners_temp, axis=0)
locationofdart = corners_temp[maxloc]
print "### used different location due to noise!"
cv2.circle(t_plus_copy, (locationofdart.item(0),locationofdart.item(1)), 10,(0, 0, 0),2, 8)
cv2.circle(t_plus_copy, (locationofdart.item(0), locationofdart.item(1)), 2, (0, 0, 0), 2, 8)
# check for the location of the dart with the calibration
dartloc = DartLocation(locationofdart.item(0), locationofdart.item(1))
dartInfo = DartRegion(dartloc) #cal_image
except:
print "Something went wrong in finding the darts location!"
continue
# check for the location of the dart with the calibration
print dartInfo.base, dartInfo.multiplier
if breaker == 1:
cv2.imwrite("frame2.jpg", testimg) # save dart1 frame
elif breaker == 2:
cv2.imwrite("frame3.jpg", testimg) # save dart2 frame
elif breaker == 3:
cv2.imwrite("frame4.jpg", testimg) # save dart3 frame
# save new diff img for next dart
t = t_plus
finalScore += (dartInfo.base * dartInfo.multiplier)
if DEBUG:
loc_x = dartloc[0] #400 + dartInfo.magnitude * math.tan(dartInfo.angle * math.pi/180)
loc_y = dartloc[1] #400 + dartInfo.magnitude * math.tan(dartInfo.angle * math.pi/180)
cv2.circle(debug_img, (int(loc_x), int(loc_y)), 2, (0, 255, 0), 2, 8)
cv2.circle(debug_img, (int(loc_x), int(loc_y)), 6, (0, 255, 0), 1, 8)
string = "" + str(dartInfo.base) + "x" + str(dartInfo.multiplier)
# add text (before clear with rectangle)
cv2.rectangle(debug_img, (600, 700), (800, 800), (0, 0, 0), -1)
cv2.putText(debug_img, string, (600, 750), cv2.FONT_HERSHEY_SIMPLEX, 2, (255, 255, 255), 2, 8)
cv2.namedWindow(winName, cv2.WINDOW_NORMAL)
cv2.namedWindow("raw", cv2.WINDOW_NORMAL)
cv2.namedWindow("test", cv2.WINDOW_NORMAL)
cv2.imshow(winName, debug_img)
cv2.imshow("raw", t_plus_copy)
cv2.imshow("test", testimg)
else:
cv2.imshow(winName, testimg)
#if breaker == 3:
# break
# missed dart
elif cv2.countNonZero(thresh) < 35000:
continue
# if player enters zone - break loop
elif cv2.countNonZero(thresh) > 35000:
break
key = cv2.waitKey(10)
if key == 27:
cv2.destroyWindow(winName)
break
count += 1
dartInfo = dartThrow()
if __name__ == '__main__':
print "Welcome to darts!"
getDart()
#getTransformation()