contours3d = []

for cnt in contours:

cnt3d = np.zeros( (cnt.shape[0], 1, cnt.shape[1]), dtype=int )

for ii in xrange(cnt.shape[0]):

cnt3d[ii] = cnt[ii]

contours3d.append(cnt3d)

result = []

global g_mser

global THRESHOLD_FRACTION

if g_mser == None:

g_mser = cv2.MSER( _delta = 10, _min_area=100, _max_area=300*50*2 )

gray = cv2.cvtColor( frame, cv2.COLOR_BGR2GRAY )

if g_mser:

contours = g_mser.detect(gray, None)

if cv2.__version__ == "2.4.2":

contours = arrayTo3d( contours ) # Jakub's workaround for 2.4.2 on linux

else:

histogram = cv2.calcHist([gray],[0],None,[256],[0,256])

s = 0

for i, h in enumerate(histogram):

s += h

if s > THRESHOLD_FRACTION * 640 * 360:

break

ret, binary = cv2.threshold( gray, i, 255, cv2.THRESH_BINARY )

# ret, binary = cv2.threshold( gray, 0, 255, cv2.THRESH_OTSU )

contours, hierarchy = cv2.findContours( binary, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE )

for cnt in contours:

if g_mser == None:

area = cv2.contourArea(cnt, oriented=True)

if g_mser != None or (area > 100 and area < 100000):

rect = cv2.minAreaRect(cnt)

if g_mser == None or len(cnt)/float(rect[1][0]*rect[1][1]) > 0.70:

result.append( rect )

if g_mser != None:

result = removeDuplicities( result )

if debug:

if g_mser == None:

cv2.drawContours(frame, contours, -1, (0,255,0), 3)

for rect in result:

box = cv2.cv.BoxPoints(rect)

box = np.int0(box)

cv2.drawContours( frame,[box],0,(255,0,0),2)

result = filterRectangles([((int(x),int(y)),(int(w),int(h)),int(a)) for ((x,y),(w,h),a) in result], minWidth=150/2)

if debug:

for rect in result:

box = cv2.cv.BoxPoints(rect)

box = np.int0(box)

cv2.drawContours( frame,[box],0,(0,0,255),2)

cv2.imshow('image', frame)

# save image for simpler results review, angle is used as hash for search sub-sequence

if g_filename:

cv2.imwrite( g_filename, frame )

ret = []

for (x,y),(w,h),a in rects:

if w < h:

w,h,a = h,w,a+90

if w > 3*h and w >= minWidth and w <= maxWidth:

ret.append( ((x,y,),(w,h),a) )

"return relative pose of image rectangle"

(x,y),(w,h),a = rect

assert w > 3*h, (w,h) # 30cm long, 5cm wide ... i.e. should be 6 times

a = -a-90

if a > 90:

a -= 180

if a < -90:

a += 180

if scale == None:

if w >= 5*h: # it should be 6x, but width is more precise

scale = 0.3/float(w)

else:

scale = 0.05/float(h)

if highResolution:

return Pose( scale*(720/2-y), scale*(1280/2-x), math.radians( a ) )

else:

# return Pose( scale*(360/2-y), scale*(640/2-x), math.radians( a ) )

# expected low resolution 640x390

if len(rects) == 1:

# keep the old behavior

return [stripPose( rects[0], highResolution=highResolution )]

maxWidth = None

for (x,y),(w,h),a in rects:

width = max(w,h)

if maxWidth == None or width > maxWidth:

maxWidth = width

"for MSER remove multiple detections of the same strip"

radius = 30

ret = []

for (x,y),(w,h),a in rectangles:

for (x2,y2),(w2,h2),a2 in ret:

if abs(x-x2) < radius and abs(y-y2) < radius:

ratio = max(h,w)/float(min(h,w))

ratio2 = max(h2,w2)/float(min(h2,w2))

if abs(ratio-desiredRatio) < abs(ratio2-desiredRatio):

# use the bigger one

ret.remove( ((x2,y2),(w2,h2),a2) )

ret.append( ((x,y),(w,h),a) )

break

else:

ret.append( ((x,y),(w,h),a) )

cap = cv2.VideoCapture( filename )

while(cap.isOpened()):

ret, frame = cap.read()

if ret:

processFrame( frame, debug=True )

else:

break

if cv2.waitKey(1) & 0xFF == ord('q'):

break

f = open( filename, "rb" )

data = f.read(10000)

pave = PaVE()

cap = None

total = 0

while len(data) > 0:

pave.append( data )

header,payload = pave.extract()

while payload:

if isIFrame( header ) and (onlyFrameNumber == None or onlyFrameNumber==frameNumber( header )/FRAMES_PER_INDEX):

tmpFile = open( "tmp.bin", "wb" )

tmpFile.write( payload )

tmpFile.flush()

tmpFile.close()

cap = cv2.VideoCapture( "tmp.bin" )

ret, frame = cap.read()

assert ret

if ret:

global g_filename

g_filename = "tmp_%04d.jpg" % (frameNumber( header )/FRAMES_PER_INDEX)

result = processFrame( frame, debug=True )

if refLog != None:

print refLog.readline().strip()

(oldFrameNumber, oldTimestamp), oldResult = eval(refLog.readline().strip())

assert oldFrameNumber == frameNumber(header), (oldFrameNumber, frameNumber(header))

assert oldTimestamp == timestamp(header), (oldTimestamp, timestamp(header))

print ((frameNumber(header), timestamp(header)), result)

# assert oldResult == result, oldResult # potential difference linux/windows

else:

print frameNumber( header )/FRAMES_PER_INDEX, result

if onlyFrameNumber:

cv2.waitKey(0)

return

header,payload = pave.extract()

if cv2.waitKey(1) & 0xFF == ord('q'):

break

data = f.read(10000)

if refLog != None: # complete termination line

if imgFce != None:

global processFrame

processFrame = imgFce

if len(argv) < 2:

print __doc__

sys.exit(2)

filename = argv[1]

if filename.endswith(".jpg"):

testFrame( filename )

else:

if isParrotVideo( filename ):

if len(argv) > 2:

if "src_cv2_" in argv[2]:

testPaVEVideo( filename, refLog=open(argv[2]) )

else:

testPaVEVideo( filename, onlyFrameNumber=int(eval(argv[2])) )

else:

testPaVEVideo( filename )

else:

testVideo( filename )