def SegmentImage(image, filledImage, contours):
#Create a list for all the segments found in the image
segments = list()
#Create a collective image that has all segments
imagecollective = np.zeros((image.shape[0], image.shape[1]))
imagecollective[:, :] = 0.5
#Segment every contour
for contour in contours:
#Create new segment
segment = Segment()
#Get aspect ratio
segment.BoundingBox = BoundingBox(np.min(contour[:, 1]),
np.max(contour[:, 1]),
np.min(contour[:, 0]),
np.max(contour[:, 0]))
segment.BoundingBox.ToInt()
#Create the segment image (will be replaced with segment class)
segment.CreateImage()
#Copy the segment from the contour we have to the segment
rr, cc = polygon(contour[:, 0], contour[:, 1], image.shape)
rr = rr.astype(int)
cc = cc.astype(int)
segment.Image[rr - segment.BoundingBox.miny,
cc - segment.BoundingBox.minx] = image[rr, cc]
segment.FilledImage[rr - segment.BoundingBox.miny,
cc - segment.BoundingBox.minx] = filledImage[rr,
cc]
imagecollective[rr, cc] = image[rr, cc]
segments.append(segment)
return imagecollective, segments
def MergeHalfCircles(circles):
newCirclesList = list()
merged = np.zeros(len(circles))
for i in range(len(circles)):
if (merged[i] == 1):
continue
c1 = circles[i]
c2 = None
for j in range(len(circles)):
if (i == j or merged[j]):
continue
if (abs(c1.BoundingBox.miny - circles[j].BoundingBox.miny) <
circlesMergeThreshold
and abs(c1.BoundingBox.maxy - circles[j].BoundingBox.maxy)
< circlesMergeThreshold and
(abs(c1.BoundingBox.minx - circles[j].BoundingBox.maxx) <
circlesMergeThreshold * 10
or abs(c1.BoundingBox.maxx - circles[j].BoundingBox.minx) <
circlesMergeThreshold * 10)):
c2 = circles[j]
merged[j] = 1
break
if (c2 != None and c1.BoundingBox.minx > c2.BoundingBox.minx):
c1, c2 = c2, c1
width = c1.Image.shape[1]
height = c1.Image.shape[0]
if (c2 != None):
width = max(width, c2.Image.shape[1])
height = max(height, c2.Image.shape[0])
#Resize img1
tmp = np.copy(c1.Image)
c1.Image = np.zeros((height, width))
c1.Image[:tmp.shape[0], :tmp.shape[1]] = tmp[:, :]
if (c2 != None):
#Resize img2
tmp = np.copy(c2.Image)
c2.Image = np.zeros((height, width))
c2.Image[:tmp.shape[0], :tmp.shape[1]] = tmp[:, :]
newCircle = np.concatenate((c1.Image, c2.Image), axis=1)
segment = Segment()
segment.BoundingBox = c1.BoundingBox
segment.Image = newCircle
newCirclesList.append(segment)
merged[i] = 1
else:
newCirclesList.append(c1)
connectCircles(newCirclesList)
for circle in newCirclesList:
contours = find_contours(circle.Image, 0.9)
circle.FilledImage = FillPolygon(circle.Image, contours)
return newCirclesList
def DetectNoteheads(notesAndConnectedSegments):
newList = list()
newSegmentsList = list()
for seg in notesAndConnectedSegments:
image = np.copy(seg.Image)
tmpImg = np.copy(image[1:-2, 1:-2])
ones = np.sum(image[5:-5, 5:-5] == 1)
zeros = np.sum(image[5:-5, 5:-5] == 0)
if (ones > 0 and zeros / ones > 1.2):
image = ndimage.binary_fill_holes(image).astype(int)
image = binary_erosion(image, selement)
image = binary_erosion(image, selement)
image = binary_erosion(image, selement2)
newSeg = Segment(seg)
newSeg.Image = image
newSeg.BoundingBox = seg.BoundingBox
newList.append(image)
newSegmentsList.append(newSeg)
return newSegmentsList, newList
