def setUp(self):
np.random.seed(1234)
self.data3D = np.zeros((2, 64, 56, 48))
self.data3D[:, 21:41, 12:32, 13:33] = 1
self.seg3D = self.data3D
self.zoom_factors = 2
self.d3D, self.s3D = augment_zoom(self.data3D, self.seg3D, zoom_factors=self.zoom_factors, order=0, order_seg=0)
self.data2D = np.zeros((2, 64, 56))
self.data2D[:, 21:41, 12:32] = 1
self.seg2D = self.data2D
self.d2D, self.s2D = augment_zoom(self.data2D, self.seg2D, zoom_factors=self.zoom_factors, order=0, order_seg=0)
def zoom_augment(data):
'''
zoom变换增广
:param data:
:return:
'''
data_result, seg_result = augment_zoom(data, (0.5, 0.8))
return data_result, seg_result
def _zoom_x_and_y(self, x, y, zoom_factor):
# Very slow
x_new = []
y_new = []
for b in range(x.shape[0]):
x_tmp, y_tmp = augment_zoom(x[b], y[b], zoom_factor, order=3, order_seg=1, cval_seg=0)
x_new.append(x_tmp)
y_new.append(y_tmp)
return np.array(x_new), np.array(y_new)
def __call__(self, **data_dict):
data = data_dict.get(self.data_key)
seg = data_dict.get(self.label_key)
ret_val = augment_zoom(data=data, seg=seg, zoom_factors=self.zoom_factors, order=self.order)
data_dict[self.data_key] = ret_val[0]
if seg is not None:
data_dict[self.label_key] = ret_val[1]
return data_dict
def __call__(self, **data_dict):
data = data_dict.get(self.data_key)
seg = data_dict.get(self.label_key)
ret_val = augment_zoom(data=data, seg=seg, zoom_factors=self.zoom_factors, order=self.order, order_seg=self.order_seg, cval_seg=self.cval_seg)
data_dict[self.data_key] = ret_val[0]
if seg is not None:
data_dict[self.label_key] = ret_val[1]
return data_dict
def __call__(self, **data_dict):
data = data_dict.get(self.data_key)
seg = data_dict.get(self.label_key)
if isinstance(data, np.ndarray):
concatenate = True
else:
concatenate = self.concatenate_list
if seg is not None:
if isinstance(seg, np.ndarray):
concatenate_seg = True
else:
concatenate_seg = self.concatenate_list
else:
concatenate_seg = None
results = []
for b in range(len(data)):
sample_seg = None
if seg is not None:
sample_seg = seg[b]
res_data, res_seg = augment_zoom(data[b], sample_seg,
self.zoom_factors, self.order,
self.order_seg, self.cval_seg)
results.append((res_data, res_seg))
if concatenate:
data = np.vstack([i[0][None] for i in results])
if concatenate_seg is not None and concatenate_seg:
seg = np.vstack([i[1][None] for i in results])
data_dict[self.data_key] = data
if seg is not None:
data_dict[self.label_key] = seg
return data_dict
