![]() ![]() Self.sagittal_canvas = widgets.SagittalCanvas(self, plot_points=True, horizontal_nav=True)įile “/data/home/s4333238/sct_4.2.0/spinalcordtoolbox/gui/widgets.py”, line 289, in init fslinfo This returns the following information: datatype INT16 dim1 96 dim2 96 dim3 60 dim4 102 datatype 4 pixdim1 2.500000 pixdim2 2.500000 pixdim3 2.500000 pixdim4 8.700000 calmax 0.000000 calmin 0. Launch_centerline_dialog(im_data, im_mask_viewer, params)įile “/data/home/s4333238/sct_4.2.0/spinalcordtoolbox/gui/centerline.py”, line 260, in launch_centerline_dialogįile “/data/home/s4333238/sct_4.2.0/spinalcordtoolbox/gui/centerline.py”, line 138, in init Im_labels = _call_viewer_centerline(Image(fname_data), interslice_gap=interslice_gap)įile “/data/home/s4333238/sct_4.2.0/spinalcordtoolbox/centerline/core.py”, line 286, in call_viewer_centerline ![]() I then swapped dim using sct_image -i 3890_dwi_ -setorient RPI -o dwi_3890_ as the orientation of the dwi data was set in ASL.įile_type sct_get_centerline -i dwi_3890_ -method viewerįile “/data/home/s4333238/sct_4.2.0/scripts/sct_get_centerline.py”, line 147, inįile “/data/home/s4333238/sct_4.2.0/scripts/sct_get_centerline.py”, line 127, in run_main ![]() I tried to run sct_get_centerline to start but unfortunately ended with the following error (please have a look at the data details, command, output). I would like to use SCT toolbox to analyze them. Whether the layer weights will be updated during training.Thank you very much for your continues help and support. It will be autogenerated if it isn’t provided. Should be unique in a model (do not reuse the same name twice). If you never set it, then it will be “channels_last”.Īn optional name string for the layer. It defaults to the image_data_format value found in your Keras config file at ~/.keras/keras.json. channels_last corresponds to inputs with shape (batch, spatial_dim1, spatial_dim2, spatial_dim3, channels) while channels_first corresponds to inputs with shape (batch, channels, spatial_dim1, spatial_dim2, spatial_dim3). The ordering of the dimensions in the inputs. The upsampling factors for dim1, dim2 and dim3.Ī string, one of channels_last (default) or channels_first. a Tensor, the output tensor from layer_instance(object) is returned. a Sequential model, the model with an additional layer is returned. missing or NULL, the Layer instance is returned. Typically a Sequential model or a Tensor (e.g., as returned by layer_input()). ![]() What to compose the new Layer instance with. Layer_upsampling_3d( object, size = c(2L, 2L, 2L), data_format = NULL, batch_size = NULL, name = NULL, trainable = NULL, weights = NULL ) Arguments Arguments ![]()
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