def extractArray(self, path, targetShape):
X_direct = []
y = []
l = len(glob(path + '/*'))
numbact = 0
printProgressBar(0,
l,
prefix='Progress:',
suffix='Complete',
length=50)
for i, im_path in enumerate(glob(path + '/*')):
printProgressBar(i + 1,
l,
prefix='Progress:',
suffix='Complete',
length=50)
init = np.float32(cv2.imread(im_path, 0))
resized = cv2.resize(init,
targetShape,
interpolation=cv2.INTER_LINEAR)
X_direct.append(resized)
if self.labeled:
if 'NORMAL' in im_path:
y.append(0)
elif 'bacteria' in im_path:
y.append(1)
numbact += 1
else:
y.append(2)
percentBact = numbact / len(X_direct)
print("Percent Bact", percentBact)
X_direct = np.stack(X_direct, axis=0) / 255
return X_direct, np.asarray(y)
def compute_motion(cls, time_subsampling=5, with_ProgressBar=False):
"""
"""
frames = np.arange(cls.nframes)[::time_subsampling]
motion = np.zeros(len(frames) - 1)
if with_ProgressBar:
printProgressBar(0, cls.nframes)
for i, frame in enumerate(frames[:-1]):
imgs = load_ROI_data(cls, frame, frame + 2, flatten=True)
motion[i] = np.mean(np.diff(imgs, axis=0)**2)
if with_ProgressBar and (i % 20 == 0):
printProgressBar(frame, cls.nframes)
return frames[1:], motion
def perform_loop(parent,
subsampling=1000,
shape='ellipse',
gaussian_smoothing=0,
saturation=100,
with_ProgressBar=False):
temp = {} # temporary data in case of subsampling
for key in [
'frame', 'cx', 'cy', 'sx', 'sy', 'diameter', 'residual', 'angle'
]:
temp[key] = []
if with_ProgressBar:
printProgressBar(0, parent.nframes)
for parent.cframe in list(
range(parent.nframes - 1)[::subsampling]) + [parent.nframes - 1]:
# preprocess image
img = preprocess(parent,
gaussian_smoothing=gaussian_smoothing,
saturation=saturation,
with_reinit=False)
coords, _, res = perform_fit(parent,
saturation=saturation,
shape=shape)
if shape == 'circle':
coords = list(coords) + [coords[-1]] # form circle to ellipse
temp['frame'].append(parent.cframe)
temp['residual'].append(res)
for key, val in zip(['cx', 'cy', 'sx', 'sy', 'angle'], coords):
temp[key].append(val)
temp['diameter'].append(np.pi * coords[2] * coords[3])
if with_ProgressBar:
printProgressBar(parent.cframe, parent.nframes)
if with_ProgressBar:
printProgressBar(parent.nframes, parent.nframes)
print('Pupil size calculation over !')
for key in temp:
temp[key] = np.array(temp[key])
temp['blinking'] = np.zeros(len(temp['cx']), dtype=np.uint)
return temp