def calculate(self, resource):
""" Append descriptors to DCD h5 table """
(image_uri, mask_uri, gobject_uri) = resource
#image_uri = BQServer().prepare_url(image_uri, remap='gray')
if image_uri and mask_uri and gobject_uri:
raise FeatureExtractionError(
400, 'Can only take either a mask or a gobject not both')
#image_uri = BQServer().prepare_url(image_uri, remap='display')
im = image2numpy(image_uri, remap='gray')
if mask_uri is '' and gobject_uri is '':
#calculating descriptor
descriptor, label = extractHTD(im)
#initalizing rows for the table
return [descriptor], [0]
if mask_uri:
#mask_uri = BQServer().prepare_url(mask_uri, remap='gray')
mask = image2numpy(mask_uri, remap='gray')
if gobject_uri:
#creating a mask from gobject
mask = gobject2mask(gobject_uri, im)
descriptors, labels = extractHTD(im, mask=mask)
#initalizing rows for the table
return descriptors, labels
def calculate(self, resource):
""" Append descriptors to DCD h5 table """
(image_uri, mask_uri, gobject_uri) = resource
if image_uri and mask_uri and gobject_uri:
raise FeatureExtractionError(400, 'Can only take either a mask or a gobject not both')
#image_uri = BQServer().prepare_url(image_uri, remap='display')
im = image2numpy(image_uri, remap='display')
im = np.uint8(im)
if mask_uri is '' and gobject_uri is '':
#calculating descriptor
DCD = extractDCD(im)
#DCD has a potentional to be any length
#the arbitrary decided length to store in the tables is 100
if len(DCD)>self.length:
log.debug('Warning: greater than 100 dimensions')
DCD = DCD[:self.length]
descriptors = np.zeros((self.length))
descriptors[:len(DCD)] = DCD
#initalizing rows for the table
return [descriptors],[0]
if mask_uri:
#mask_uri = BQServer().prepare_url(mask_uri, remap='gray')
mask = image2numpy(mask_uri, remap='gray')
if gobject_uri:
#creating a mask from gobject
mask = gobject2mask(gobject_uri, im)
descritptor_list = []
label_list = []
#calculating descriptor
for label in np.unique(mask):
lmask = np.array((mask==label)*255, dtype='uint8')
DCD = extractDCD(im, mask = lmask)
#DCD has a potentional to be any length
#the arbitrary decided length to store in the tables is 100
if len(DCD)>self.length:
log.debug('Warning: greater than 100 dimensions')
DCD=DCD[:self.length]
descriptors = np.zeros((self.length))
descriptors[:len(DCD)]=DCD
descritptor_list.append(descriptors)
label_list.append(label)
#initalizing rows for the table
return descritptor_list, label_list
def calculate(self, resource):
except_image_only(resource)
im = image2numpy(resource.image, remap='gray')
binary_im = np.uint8(im > 0)
m = cv2.moments(binary_im)
hu = cv2.HuMoments(m)
return [hu.T]
def calculate(self, resource):
except_image_only(resource)
im = image2numpy(resource.image, remap='gray')
feature = hog(im, orientations=4, pixels_per_cell=(8, 8), cells_per_block=(2, 2))
feature = np.reshape(feature, (feature.size/16, 16)) # pylint: disable=no-member
block_count = np.arange(feature.shape[0])
return (feature, block_count)
def calculate(self, resource):
except_image_only(resource)
im = image2numpy(resource.image, remap='gray')
keypoints = corner_peaks(corner_harris(im), min_distance=1)
extractor = BRIEF_()
extractor.extract(im, keypoints)
#initalizing rows for the table
return (extractor.descriptors, keypoints[:,0], keypoints[:,1])
def calculate(self, resource):
""" Append descriptors to h5 table """
except_image_only(resource)
image_uri = resource.image
#image_uri = BQServer().prepare_url(image_uri, remap='display')
im = image2numpy(image_uri, remap='display')
im = np.uint8(im)
descriptors = extractSCD(im, descSize=256) #calculating descriptor
return descriptors
def calculate(self, resource):
#initalizing
except_image_only(resource)
image_uri = resource.image
#image_uri = BQServer().prepare_url(image_uri, remap='gray')
im = image2numpy(image_uri, remap='gray')
descriptors = extractEHD(im)
#initalizing rows for the table
return descriptors
def calculate(self, resource):
#initalizing
except_image_only(resource)
image_uri = resource.image
#image_uri = BQServer().prepare_url(image_uri, remap='gray')
im = image2numpy(image_uri, remap='gray')
im = np.uint8(im)
descriptors = extractEHD(im) #calculating descriptor
return descriptors
def calculate(self, resource):
except_image_only(resource)
im = image2numpy(resource.image, remap='gray')
extractor = ORB()
extractor.detect_and_extract(im)
return (extractor.descriptors,
extractor.keypoints[:,0],
extractor.keypoints[:,1],
extractor.responses,
extractor.scales,
extractor.orientations)
def calculate(self, resource):
#initalizing
except_image_only(resource)
image_uri = resource.image
#image_uri = BQServer().prepare_url(image_uri, remap='display')
im = image2numpy(image_uri, remap='display')
im = np.uint8(im)
descriptor = tas(im)
#initalizing rows for the table
return descriptor
def calculate(self, resource):
#initalizing
except_image_only(resource)
image_uri = resource.image
#image_uri = BQServer().prepare_url(image_uri, remap='gray')
im = image2numpy(image_uri, remap='gray')
im = np.uint8(im)
#calculate descriptor
descritptors = np.hstack(haralick(im))
#initalizing rows for the table
return descritptors
def calculate(self, resource):
""" Append descriptors to SURF h5 table """
#initalizing
except_image_only(resource)
image_uri = resource.image
#image_uri = BQServer().prepare_url(image_uri, remap='gray')
im = image2numpy(image_uri, remap='gray')
im = np.uint8(im)
descriptor = pftas(im)
#initalizing rows for the table
return descriptor
def calculate(self, resource):
""" Append descriptors to CSD h5 table """
(image_uri, mask_uri, gobject_uri) = resource
if image_uri and mask_uri and gobject_uri:
raise FeatureExtractionError(400, 'Can only take either a mask or a gobject not both')
#image_uri = BQServer().prepare_url(image_uri, remap='display')
im = image2numpy(image_uri, remap='display')
im = np.uint8(im)
if mask_uri is '' and gobject_uri is '':
#calculating descriptor
RSD = extractRSD(im)
#initalizing rows for the table
return [RSD], [0]
if mask_uri:
#mask_uri = BQServer().prepare_url(mask_uri, remap='gray')
mask = image2numpy(mask_uri, remap='gray')
if gobject_uri:
#creating a mask from gobject
mask = gobject2mask(gobject_uri, im)
descritptor_list = []
label_list = []
#calculating descriptor
for label in np.unique(mask):
lmask = np.array((mask==label)*255,dtype='uint8')
RSD = extractRSD(im, mask=lmask)
label_list.append(label)
descritptor_list.append(RSD)
#initalizing rows for the table
return descritptor_list, label_list
def calculate(self, resource):
#initalizing
except_image_only(resource)
image_uri = resource.image
#image_uri = BQServer().prepare_url(image_uri, remap='gray')
im = image2numpy(image_uri, remap='gray')
im = np.uint8(im)
width, height = im.shape
# if width<128 and height<128:
# raise FeatureExtractionError(resource, 415, 'Image\'s width and height must be greater than 128')
descriptors = extractHTD(im) #calculating descriptor
return descriptors
def calculate(self, resource):
#initalizing
except_image_only(resource)
image_uri = resource.image
#image_uri = BQServer().prepare_url(image_uri, remap='gray')
im = image2numpy(image_uri, remap='gray')
im = np.uint8(im)
radius = 8
degree = 8
descritptor = zernike_moments(im, radius, degree)
#initalizing rows for the table
return descritptor
def calculate(self, resource):
""" Append descriptors to SURF h5 table """
#initalizing
extended = 0
HessianThresh = 400
nOctaves = 3
nOctaveLayers = 4
(image_url, mask_url, gobject_url) = resource
if image_url is '':
raise FeatureExtractionError(resource, 400,
'Image resource is required')
if mask_url is not '':
raise FeatureExtractionError(resource, 400,
'Mask resource is not accepted')
#image_url = BQServer().prepare_url(image_url, remap='display')
im = image2numpy(image_url, remap='display')
im = np.uint8(im)
if gobject_url is '':
fs = cv2.SURF().detect(im)
if gobject_url:
(x, y, size) = gobject2keypoint(gobject_url)
fs = [cv2.KeyPoint(x, y, size)] # keypoints
descriptor_extractor = cv2.DescriptorExtractor_create("SURF")
(kpts, descriptors) = descriptor_extractor.compute(im, fs)
if descriptors == None: #taking Nonetype into account
raise FeatureExtractionError(resource, 500,
'No feature was calculated')
x = []
y = []
response = []
size = []
angle = []
octave = []
for k in kpts[:500]:
x.append(k.pt[0])
y.append(k.pt[1])
response.append(k.response)
size.append(k.size)
angle.append(k.angle)
octave.append(k.octave)
return (descriptors, x, y, response, size, angle, octave)
def calculate(self, resource):
except_image_only(resource)
im = image2numpy(resource.image, remap='gray')
m00 = raw_moments(im, 0, 0)
m01 = raw_moments(im, 0, 1)
m10 = raw_moments(im, 1, 0)
m11 = raw_moments(im, 1, 1)
m02 = raw_moments(im, 0, 2)
m20 = raw_moments(im, 2, 0)
m03 = raw_moments(im, 0, 3)
m30 = raw_moments(im, 3, 0)
m21 = raw_moments(im, 2, 1)
m12 = raw_moments(im, 1, 2)
return np.array([m00, m01, m10, m11, m02, m02, m03, m30, m21, m12])
def calculate(self, resource):
except_image_only(resource)
im = image2numpy(resource.image, remap='gray')
u00 = central_moments(im, 0, 0)
u01 = central_moments(im, 0, 1)
u10 = central_moments(im, 1, 0)
u11 = central_moments(im, 1, 1)
u02 = central_moments(im, 0, 2)
u20 = central_moments(im, 2, 0)
u03 = central_moments(im, 0, 3)
u30 = central_moments(im, 3, 0)
u21 = central_moments(im, 2, 1)
u12 = central_moments(im, 1, 2)
return np.array([u00, u01, u10, u11, u02, u02, u03, u30, u21, u12])
def calculate(self, resource):
except_image_only(resource)
im = image2numpy(resource.image, remap='gray')
n00 = scale_invarient_moments(im, 0, 0)
n01 = scale_invarient_moments(im, 0, 1)
n10 = scale_invarient_moments(im, 1, 0)
n11 = scale_invarient_moments(im, 1, 1)
n02 = scale_invarient_moments(im, 0, 2)
n20 = scale_invarient_moments(im, 2, 0)
n03 = scale_invarient_moments(im, 0, 3)
n30 = scale_invarient_moments(im, 3, 0)
n21 = scale_invarient_moments(im, 2, 1)
n12 = scale_invarient_moments(im, 1, 2)
return np.array([n00, n01, n10, n11, n02, n02, n03, n30, n21, n12])
def calculate(self, resource):
#initalizing
except_image_only(resource)
image_uri = resource.image
#image_uri = BQServer().prepare_url(image_uri, remap='gray')
im = image2numpy(image_uri, remap='gray')
im = np.uint8(im)
#calculating descriptor
radius = 5
points = 5
descriptor = lbp(im, radius, points)
#initalizing rows for the table
return descriptor
def calculate(self, resource):
""" Append descriptors to h5 table """
except_image_only(resource)
image_uri = resource.image
feature_info = feature_list[self.name]
tranforms = feature_info[1:3]
#adds the correct delimiter
if image_uri.count('?') < 1:
image_uri += '?'
else:
image_uri += '&'
args = []
if feature_info[4] == True:
#force the image to 3 channels prefered rgb
args.append('remap=display')
else:
#force the image to be 1 channel
args.append('remap=grey')
for t in tranforms:
if t != "Empty Transform":
if t == "Hue Transform":
args.append('depth=8,d')
args.append(
'transform=rgb2hsv'
) #converts rgb to hsv and then selects the hue channel
args.append('remap=1')
else:
args.append('transform=' + t)
args.append('format=tiff') #return tiff format
image_uri += '&'.join(args)
log.debug('WNDCharm uri: %s' % image_uri)
im = image2numpy(image_uri)
extractWNDCharmFeature = feature_info[0]
descriptor = extractWNDCharmFeature(im)
#initalizing rows for the table
return descriptor
def calculate(self, resource):
except_image_only(resource)
im = image2numpy(resource.image, remap='gray')
return rotation_invariant_moments(im)
def calculate(self, resource):
except_image_only(resource)
im = image2numpy(resource.image, remap='gray')
min_length = np.min(im.shape) # pylint: disable=no-member
return hog(im, pixels_per_cell=(min_length, min_length), cells_per_block=(1,1))
