__author__ = "Hannes Hoettinger"
import numpy as np
import cv2
import time
import cv2.cv as cv
import math
import pickle
from Classes import *
from MathFunctions import *
from DartsMapping import *
from Draw import *
DEBUG = False
winName = "test2"
def cam2gray(cam):
success, image = cam.read()
img_g = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
return success, img_g
def getThreshold(cam, t):
success, t_plus = cam2gray(cam)
dimg = cv2.absdiff(t, t_plus)
blur = cv2.GaussianBlur(dimg, (5, 5), 0)
blur = cv2.bilateralFilter(blur, 9, 75, 75)
_, thresh = cv2.threshold(blur, 60, 255, 0)
return thresh
def diff2blur(cam, t):
_, t_plus = cam2gray(cam)
dimg = cv2.absdiff(t, t_plus)
## kernel size important -> make accessible
# filter noise from image distortions
kernel = np.ones((5, 5), np.float32) / 25
blur = cv2.filter2D(dimg, -1, kernel)
return t_plus, blur
def getCorners(img_in):
# number of features to track is a distinctive feature
## FeaturesToTrack important -> make accessible
edges = cv2.goodFeaturesToTrack(img_in, 640, 0.0008, 1, mask=None, blockSize=3, useHarrisDetector=1, k=0.06) # k=0.08
corners = np.int0(edges)
return corners
def filterCorners(corners):
cornerdata = []
tt = 0
mean_corners = np.mean(corners, axis=0)
for i in corners:
xl, yl = i.ravel()
# filter noise to only get dart arrow
## threshold important -> make accessible
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
return corners_new
def filterCornersLine(corners, rows, cols):
[vx, vy, x, y] = cv2.fitLine(corners, 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:
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
cornerdata.append(tt)
tt += 1
corners_final = np.delete(corners, [cornerdata], axis=0) # delete corners to form new array
return corners_final
def getRealLocation(corners_final, mount):
if mount == "right":
loc = np.argmax(corners_final, axis=0)
else:
loc = np.argmin(corners_final, axis=0)
locationofdart = corners_final[loc]
# 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
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!"
return locationofdart
def getDarts(cam_R, cam_L, calData_R, calData_L, playerObj, GUI):
finalScore = 0
count = 0
breaker = 0
## threshold important -> make accessible
minThres = 2000/2
maxThres = 15000/2
# save score if score is below 1...
old_score = playerObj.score
# Read first image twice (issue somewhere) to start loop:
_, _ = cam2gray(cam_R)
_, _ = cam2gray(cam_L)
# wait for camera
time.sleep(0.1)
success, t_R = cam2gray(cam_R)
_, t_L = cam2gray(cam_L)
while success:
# wait for camera
time.sleep(0.1)
# check if dart hit the board
thresh_R = getThreshold(cam_R, t_R)
thresh_L = getThreshold(cam_L, t_L)
print cv2.countNonZero(thresh_R)
## threshold important
if (cv2.countNonZero(thresh_R) > minThres and cv2.countNonZero(thresh_R) < maxThres) \
or (cv2.countNonZero(thresh_L) > minThres and cv2.countNonZero(thresh_L) < maxThres):
# wait for camera vibrations
time.sleep(0.2)
# filter noise
t_plus_R, blur_R = diff2blur(cam_R, t_R)
t_plus_L, blur_L = diff2blur(cam_L, t_L)
# get corners
corners_R = getCorners(blur_R)
corners_L = getCorners(blur_L)
testimg = blur_R.copy()
# dart outside?
if corners_R.size < 40 and corners_L.size < 40:
print "### dart not detected"
continue
# filter corners
corners_f_R = filterCorners(corners_R)
corners_f_L = filterCorners(corners_L)
# dart outside?
if corners_f_R.size < 30 and corners_f_L.size < 30:
print "### dart not detected"
continue
# find left and rightmost corners#
rows, cols = blur_R.shape[:2]
corners_final_R = filterCornersLine(corners_f_R, rows, cols)
corners_final_L = filterCornersLine(corners_f_L, rows, cols)
_, thresh_R = cv2.threshold(blur_R, 60, 255, 0)
_, thresh_L = cv2.threshold(blur_L, 60, 255, 0)
# check if it was really a dart
print cv2.countNonZero(thresh_R)
if cv2.countNonZero(thresh_R) > maxThres*2 or cv2.countNonZero(thresh_L) > maxThres*2:
continue
print "Dart detected"
# dart was found -> increase counter
breaker += 1
dartInfo = DartDef()
# get final darts location
try:
dartInfo_R = DartDef()
dartInfo_L = DartDef()
dartInfo_R.corners = corners_final_R.size
dartInfo_L.corners = corners_final_L.size
locationofdart_R = getRealLocation(corners_final_R, "right")
locationofdart_L = getRealLocation(corners_final_L, "left")
# check for the location of the dart with the calibration
dartloc_R = getTransformedLocation(locationofdart_R.item(0), locationofdart_R.item(1), calData_R)
dartloc_L = getTransformedLocation(locationofdart_L.item(0), locationofdart_L.item(1), calData_L)
# detect region and score
dartInfo_R = getDartRegion(dartloc_R, calData_R)
dartInfo_L = getDartRegion(dartloc_L, calData_L)
cv2.circle(testimg, (locationofdart_R.item(0), locationofdart_R.item(1)), 10, (255, 255, 255), 2, 8)
cv2.circle(testimg, (locationofdart_R.item(0), locationofdart_R.item(1)), 2, (0, 255, 0), 2, 8)
except:
print "Something went wrong in finding the darts location!"
breaker -= 1
continue
# "merge" scores
if dartInfo_R.base == dartInfo_L.base and dartInfo_R.multiplier == dartInfo_L.multiplier:
dartInfo = dartInfo_R
# use the score of the image with more corners
else:
if dartInfo_R.corners > dartInfo_L.corners:
dartInfo = dartInfo_R
else:
dartInfo = dartInfo_L
print dartInfo.base, dartInfo.multiplier
if breaker == 1:
GUI.dart1entry.insert(10,str(dartInfo.base * dartInfo.multiplier))
dart = int(GUI.dart1entry.get())
cv2.imwrite("frame2.jpg", testimg) # save dart1 frame
elif breaker == 2:
GUI.dart2entry.insert(10,str(dartInfo.base * dartInfo.multiplier))
dart = int(GUI.dart2entry.get())
cv2.imwrite("frame3.jpg", testimg) # save dart2 frame
elif breaker == 3:
GUI.dart3entry.insert(10,str(dartInfo.base * dartInfo.multiplier))
dart = int(GUI.dart3entry.get())
cv2.imwrite("frame4.jpg", testimg) # save dart3 frame
playerObj.score -= dart
if playerObj.score == 0 and dartInfo.multiplier == 2:
playerObj.score = 0
breaker = 3
elif playerObj.score <= 1:
playerObj.score = old_score
breaker = 3
# save new diff img for next dart
t_R = t_plus_R
t_L = t_plus_L
if playerObj.player == 1:
GUI.e1.delete(0,'end')
GUI.e1.insert(10,playerObj.score)
else:
GUI.e2.delete(0,'end')
GUI.e2.insert(10,playerObj.score)
finalScore += (dartInfo.base * dartInfo.multiplier)
if breaker == 3:
break
#cv2.imshow(winName, tnow)
# missed dart
elif cv2.countNonZero(thresh_R) < maxThres/2 or cv2.countNonZero(thresh_L) < maxThres/2:
continue
# if player enters zone - break loop
elif cv2.countNonZero(thresh_R) > maxThres/2 or cv2.countNonZero(thresh_L) > maxThres/2:
break
key = cv2.waitKey(10)
if key == 27:
cv2.destroyWindow(winName)
break
count += 1
GUI.finalentry.delete(0, 'end')
GUI.finalentry.insert(10,finalScore)
print finalScore
if __name__ == '__main__':
print "Welcome to darts!"
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
# 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)
