class feature:
def __init__(self):
if not detector.GLOBAL_WINDOWS:
self.__term_ = TerminalController()
def extract_features(self, images, algorithm='surf'):
self.__total_ = len(images)
if not detector.GLOBAL_WINDOWS:
self.__progress_ = ProgressBar(self.__term_, 'Extracting features')
self.update_progress(c_int(0))
p_jobs=10
else:
p_jobs=5
if algorithm=='hog':
images = Parallel(n_jobs=-1)(delayed(process_image_hog)(self, i) for i in images)
else:
if algorithm=='surf':
self.__surf_extractor_=surf.surf()
images = self.__surf_extractor_.extract_features(images, 100)
return images
def get_hog_fd(self, image):
fd = hog(image, orientations=8, pixels_per_cell=(10, 10),
cells_per_block=(1, 1), normalise=True)
return fd
def update_progress(self, c):
if detector.GLOBAL_WINDOWS:
print "Working on "+str(c.value)+"/"+str(self.__total_)
else:
self.__progress_.update(float(c.value)/self.__total_, 'working on %i' % c.value)
def process_images(self):
self.print_replace("Starting processing")
if not detector.GLOBAL_WINDOWS:
self.__progress_ = ProgressBar(self.__term_, "Processing images")
p_jobs = 15
else:
p_jobs = 10
images = Parallel(n_jobs=-1)(delayed(process_image2)(self, i) for i in self.__image_paths_)
return images
class preprocess:
def __init__(self, image_paths):
if not detector.GLOBAL_WINDOWS:
self.__term_ = TerminalController()
self.imgIndex = 0
self.__image_paths_ = image_paths
def process_images(self):
self.print_replace("Starting processing")
if not detector.GLOBAL_WINDOWS:
self.__progress_ = ProgressBar(self.__term_, "Processing images")
p_jobs = 15
else:
p_jobs = 10
images = Parallel(n_jobs=-1)(delayed(process_image2)(self, i) for i in self.__image_paths_)
return images
def rgb2singch(self, image):
# return rgb2gray(image) #---Normal grayscale normalisation
return image[:, :, 1] # Green channel
# return image[:,:,0] #Red Channel
# return image[:,:,2] #Blue Channel
def median_filter(self, image):
return skimage.filters.median(image, skimage.morphology.rectangle(3, 3))
def gaussian_filter(self, image):
return skimage.filters.gaussian_filter(image, 2)
def print_replace(self, text):
sys.stdout.write(text)
sys.stdout.flush()
if not detector.GLOBAL_WINDOWS:
sys.stdout.write(self.__term_.BOL + self.__term_.CLEAR_EOL)
def update_progress(self, filename, c):
if detector.GLOBAL_WINDOWS:
print "Working on " + filename + str(c.value) + "/" + str(len(self.__image_paths_))
else:
self.__progress_.update(float(c.value) / len(self.__image_paths_), "working on %s" % filename)
def extract_features(self, images, algorithm='surf'):
self.__total_ = len(images)
if not detector.GLOBAL_WINDOWS:
self.__progress_ = ProgressBar(self.__term_, 'Extracting features')
self.update_progress(c_int(0))
p_jobs=10
else:
p_jobs=5
if algorithm=='hog':
images = Parallel(n_jobs=-1)(delayed(process_image_hog)(self, i) for i in images)
else:
if algorithm=='surf':
self.__surf_extractor_=surf.surf()
images = self.__surf_extractor_.extract_features(images, 100)
return images
