def __init__(self, boardsize):
self.boardsize = boardsize
self.mask = dict()
self.config = dict()
self.boardRecognizer = BoardRecognizer()
self.pieceRecognizer = PieceRecognizer(self.boardsize)
class Recognizer:
def __init__(self, boardsize):
self.boardsize = boardsize
self.mask = dict()
self.config = dict()
self.boardRecognizer = BoardRecognizer()
self.pieceRecognizer = PieceRecognizer(self.boardsize)
def initcapture(self, n):
cap = cv2.VideoCapture(n)
# This settings are to always set webcam resolution to maximum
cap.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH, 2000)
cap.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, 2000)
print "Capturing from: {}".format(n)
print "Frame Size: ", cap.get(3), "x", cap.get(4)
self.cap = cap
return cap.isOpened()
def initrefdata(self, path):
file = open(path, 'r')
refdata = yaml.load(file.read())
self.refBoard = refdata['board']
print "Ref data:"
print refdata
def endcapture(self):
self.cap.release()
def setconfig(self, config):
self.config = config
self.boardRecognizer.setmask(config['mask'])
def getconfig(self):
return self.config
def getframe(self):
_, frame = self.cap.read()
return frame
def getboardstate(self, frame):
self.frame = frame
boardfound, self.board = self.boardRecognizer.processframe(frame)
if boardfound:
self.pieceRecognizer.findpiecesonboard(self.board)
return self.pieceRecognizer.board_representation
def __init__(self, n):
print "Initializing board recognizer"
self.initCapture(n)
self.piecerecognizer = PieceRecognizer()
class BoardRecognizer:
def __init__(self, n):
print "Initializing board recognizer"
self.initCapture(n)
self.piecerecognizer = PieceRecognizer()
def initCapture(self, n):
#initialize cap
cap = cv2.VideoCapture(n)
cap.set(cv2.cv.CV_CAP_PROP_FPS, 1)
cap.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH, 2000)
cap.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, 2000)
print "Using Camera{}".format(n)
print "Frame Size: ", cap.get(3), "x", cap.get(4)
self.cap = cap
return cap.isOpened()
def endProgram(self):
#when everyting is done release the frame
self.cap.release()
cv2.destroyAllWindows()
def getBoardState(self):
pieces = "!"
cap = self.cap
#capture frame by frame
_, frame = cap.read()
# Smoothing
frame = cv2.bilateralFilter(frame, 12, 50, 50)
# Color space conversions
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# Color filtering
# 50 50 50
lower_green = np.array([30, 30, 20])
upper_green = np.array([85, 255, 255])
mask = cv2.inRange(hsv, lower_green, upper_green)
#copy the mask because findContours destroys the image
thresh = mask.copy()
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
#Board vertexes
points = []
# Contour filter
for contour in contours:
area = cv2.contourArea(contour)
if area > 500:
M = cv2.moments(contour)
cx = int(M['m10']/M['m00'])
cy = int(M['m01']/M['m00'])
points.append((cx, cy))
#If the board is found we can try and recognize the pieces
if len(points) == 4:
gray = frame[:,:,2]
points1 = np.float32(points)
points2 = np.float32([[0,0],[400,0],[0,400],[400,400]])
M = cv2.getPerspectiveTransform(points1,points2)
board = cv2.warpPerspective(gray, M, (400,400))
pieces = self.piecerecognizer.findPiecesOnBoard(board)
#display the resulting frame
cv2.namedWindow('frame', cv2.WINDOW_AUTOSIZE)
cv2.imshow('frame', frame)
#and the mask
cv2.namedWindow('mask', cv2.WINDOW_AUTOSIZE)
cv2.imshow('mask', mask)
return pieces
