def segmentImage(*args):
id = args[0]
print "Start id: " + str(id)
image = loadImage(id, "../sampleimages\\")
if not image == None:
segmented, labels = cl.slic(image)
io.imsave("segmented/" + str(id) + ".jpg", image)
io.imsave("segmented/" + str(id) + "_segmented.jpg", segmented)
print "Finish id: " + str(id)
def getTaggedSegments(id, taggedPoints, possibleTags):
li = ['tag1c', 'tag2c', 'tag3c', 'tag4c', 'tag5c', 'tag6c', 'tag7c', 'tag8c', 'tag9c', 'tag10c']
li2 = ['tag1', 'tag2', 'tag3', 'tag4', 'tag5', 'tag6', 'tag7', 'tag8', 'tag9', 'tag10']
possibleTagsDict = {}
possibleTagsDictSobel = {}
for tag in possibleTags:
possibleTagsDict[tag[0]] = []
possibleTagsDictSobel[tag[0]] = []
print "Processing id: " + id
for i in range(len(li)):
newPoints = []
for point in taggedPoints[id][li[i]]:
newPoints.append(point.split(':'))
taggedPoints[id][li[i]] = newPoints
image = loadImage(id, "../sampleimages\\")
sobelImage = filt.sobel(skcol.rgb2gray(image))
if not image == None:
segmented, labels = cl.slic(image)
labelledSegments = labels[0]
labels = labels[1]
n_clusters = labels[2]
for i in range(len(li)):
for point in taggedPoints[id][li[i]]:
for segment in labelledSegments:
#add list of pixels to corresponding tag
try:
if len(point) == 2:
if point[0] != '' and point[1] != '':
if segment[int(point[1])][int(point[0])] and taggedPoints[id][li2[i]] != 'None':
possibleTagsDict[taggedPoints[id][li2[i]].replace('"', '')].append(image[segment])
possibleTagsDictSobel[taggedPoints[id][li2[i]].replace('"', '')].append(np.nanmean(sobelImage[segment]))
except:
continue
return [possibleTagsDict, possibleTagsDictSobel]
def getImageFeatures(imageId, targetDir = "../sampleimages\\"):
image = loadImage(imageId, targetDir)
sobelImage = filt.sobel(skcol.rgb2gray(image))
fig = plt.figure()
ax1 = fig.add_subplot(1,1,1)
ax1.imshow(image)
plt.show()
if not image == None:
segmented, labels = cl.slic(image)
labelledSegments = labels[0]
labels = labels[1]
n_clusters = labels[2]
imageSegments = []
for segment in labelledSegments:
imageSegments.append(image[segment])
sobelSegments = []
for segment in labelledSegments:
sobelSegments.append(np.nanmean(sobelImage[segment]))
return getImageFeatureVectors(imageSegments, sobelSegments)
