app.py CHANGED
@@ -296,8 +296,17 @@ with col2:
296
  img_nii = None
297
  if st.session_state.preds_3D_ori is not None and st.session_state.data_item is not None:
298
  meta_dict = st.session_state.data_item['meta']
299
- pred_array = st.session_state.preds_3D_ori.transpose(2, 1, 0)
300
- img_nii = nib.Nifti1Image(pred_array, affine=meta_dict['affine'])
 
 
 
 
 
 
 
 
 
301
 
302
  with tempfile.NamedTemporaryFile(suffix=".nii.gz") as tmpfile:
303
  nib.save(img_nii, tmpfile.name)
@@ -323,9 +332,6 @@ with col3:
323
  st.session_state.running = True
324
  st.rerun()
325
 
326
- # if len(st.session_state.points) > 0:
327
- # st.write(st.session_state.points)
328
-
329
  if st.session_state.running:
330
  st.session_state.running = False
331
  with st.status("Running...", expanded=False) as status:
 
296
  img_nii = None
297
  if st.session_state.preds_3D_ori is not None and st.session_state.data_item is not None:
298
  meta_dict = st.session_state.data_item['meta']
299
+ foreground_start_coord = st.session_state.data_item['foreground_start_coord']
300
+ foreground_end_coord = st.session_state.data_item['foreground_end_coord']
301
+ original_shape = st.session_state.data_item['ori_shape']
302
+ pred_array = st.session_state.preds_3D_ori
303
+ original_array = np.zeros(original_shape)
304
+ original_array[foreground_start_coord[0]:foreground_end_coord[0],
305
+ foreground_start_coord[1]:foreground_end_coord[1],
306
+ foreground_start_coord[2]:foreground_end_coord[2]] = pred_array
307
+
308
+ original_array = original_array.transpose(2, 1, 0)
309
+ img_nii = nib.Nifti1Image(original_array, affine=meta_dict['affine'])
310
 
311
  with tempfile.NamedTemporaryFile(suffix=".nii.gz") as tmpfile:
312
  nib.save(img_nii, tmpfile.name)
 
332
  st.session_state.running = True
333
  st.rerun()
334
 
 
 
 
335
  if st.session_state.running:
336
  st.session_state.running = False
337
  with st.status("Running...", expanded=False) as status:
model/data_process/__pycache__/demo_data_process.cpython-39.pyc CHANGED
Binary files a/model/data_process/__pycache__/demo_data_process.cpython-39.pyc and b/model/data_process/__pycache__/demo_data_process.cpython-39.pyc differ
 
model/data_process/demo_data_process.py CHANGED
@@ -60,7 +60,7 @@ def process_ct_gt(case_path, spatial_size=(32,256,256)):
60
  DimTranspose(keys=["image"]),
61
  MinMaxNormalization(),
62
  transforms.SpatialPadd(keys=["image"], spatial_size=spatial_size, mode='constant'),
63
- # transforms.CropForegroundd(keys=["image"], source_key="image"),
64
  transforms.ToTensord(keys=["image"]),
65
  ]
66
  )
@@ -81,12 +81,14 @@ def process_ct_gt(case_path, spatial_size=(32,256,256)):
81
  ct_voxel_ndarray = np.array(ct_voxel_ndarray).squeeze()
82
  ct_voxel_ndarray = np.expand_dims(ct_voxel_ndarray, axis=0)
83
  item['image'] = ct_voxel_ndarray
 
84
 
85
  # transform
86
  item = transform(item)
87
  item_zoom_out = zoom_out_transform(item)
88
  item['zoom_out_image'] = item_zoom_out['image']
89
-
 
90
  item_z = z_transform(item)
91
  item['z_image'] = item_z['image']
92
  item['meta'] = meta_tensor_dict
 
60
  DimTranspose(keys=["image"]),
61
  MinMaxNormalization(),
62
  transforms.SpatialPadd(keys=["image"], spatial_size=spatial_size, mode='constant'),
63
+ transforms.CropForegroundd(keys=["image"], source_key="image"),
64
  transforms.ToTensord(keys=["image"]),
65
  ]
66
  )
 
81
  ct_voxel_ndarray = np.array(ct_voxel_ndarray).squeeze()
82
  ct_voxel_ndarray = np.expand_dims(ct_voxel_ndarray, axis=0)
83
  item['image'] = ct_voxel_ndarray
84
+ ori_shape = np.swapaxes(ct_voxel_ndarray, -1, -3).shape[1:]
85
 
86
  # transform
87
  item = transform(item)
88
  item_zoom_out = zoom_out_transform(item)
89
  item['zoom_out_image'] = item_zoom_out['image']
90
+ item['ori_shape'] = ori_shape
91
+
92
  item_z = z_transform(item)
93
  item['z_image'] = item_z['image']
94
  item['meta'] = meta_tensor_dict