def dataset_to_xt_data(dataset, crop_roi):
"""Convert dataset to x_data and t_data"""
x_data = []
for raw_path in dataset.filenames:
raw = im_preprocess(imread(raw_path))
if crop_roi:
mask_path = raw_to_mask_path(raw_path)
roi = mask_to_roi(im_preprocess(imread(mask_path)))
raw = raw[roi[0]:roi[2], roi[1]:roi[3]]
raw = resize(raw, (128, 128), preserve_range=True)
x_data.append(im_to_blob(raw))
x_data = np.array(x_data, dtype=np.float32)
t_data = dataset.target.astype(np.int32)
return x_data, t_data
def setUp(self):
self.model = CAEPool()
self.optimizer = O.Adam()
self.optimizer.setup(self.model)
img = doll()
x_data = np.array([im_to_blob(im_preprocess(img))])
self.x = Variable(x_data)
def setUp(self):
cae_ones_h5 = os.path.join(here, 'data/cae_ones.h5')
vgg_h5 = os.path.join(here, 'data/vgg.h5')
self.model = CAEOnesRoiVGG(
initial_roi=[100, 100, 300, 300],
cae_ones_h5=cae_ones_h5, vgg_h5=vgg_h5)
self.optimizer = O.Adam()
self.optimizer.setup(self.model)
img = doll()
x_data = np.array([im_to_blob(im_preprocess(img))])
self.x = Variable(x_data)
t_data = np.array([0], dtype=np.int32)
self.t = Variable(t_data)