Working on demo - not finished yet

DeepDeformationMapRegistration/main.py

@@ -338,7 +338,7 @@ def main():
             else:
                 np.savez_compressed(os.path.join(os.path.join(args.outputdir, 'debug'), 'displacement_map.npz'), disp_map)
         
-        LOGGER.info('Predicted image and displacement map saved in: '.format(args.outputdir))
+        LOGGER.info(f'Predicted image and displacement map saved in: '.format(args.outputdir))
         LOGGER.info(f'Displacement map prediction time: {time_disp_map_end - time_disp_map_start} s')
         LOGGER.info(f'Predicted image time: {time_pred_img_end - time_pred_img_start} s')
 

demo/src/compute.py

@@ -1,3 +1,6 @@
-def run_model(input_path):
-    from lungtumormask import mask
-    mask.mask(input_path, "./prediction.nii.gz", lung_filter=True, threshold=0.5, radius=1, batch_size=1)
+import subprocess as sp
+
+
+def run_model(fixed_path, moving_path, output_path):
+    sp.check_call(["ddmr", "--fixed", fixed_path, "--moving", moving_path, \
+                   "-o", output_path, "-a", "B", "--model", "BL-NS", "--original-resolution"])

demo/src/gui.py

@@ -2,7 +2,7 @@ import os
 
 import gradio as gr
 
-from .inference import run_model
+from .compute import run_model
 from .utils import load_ct_to_numpy
 from .utils import load_pred_volume_to_numpy
 from .utils import nifti_to_glb
@@ -16,7 +16,8 @@ class WebUI:
         share: int = 1,
     ):
         # global states
-        self.images = []
+        self.fixed_images = []
+        self.moving_images = []
         self.pred_images = []
 
         # @TODO: This should be dynamically set based on chosen volume size
@@ -26,21 +27,9 @@ class WebUI:
         self.cwd = cwd
         self.share = share
 
-        self.class_name = "meningioma"  # default
         self.class_names = {
-            "meningioma": "MRI_Meningioma",
-            "low-grade": "MRI_LGGlioma",
-            "metastasis": "MRI_Metastasis",
-            "high-grade": "MRI_GBM",
-            "brain": "MRI_Brain",
-        }
-
-        self.result_names = {
-            "meningioma": "Tumor",
-            "low-grade": "Tumor",
-            "metastasis": "Tumor",
-            "high-grade": "Tumor",
-            "brain": "Brain",
+            "B": "Brain",
+            "L": "Liver"
         }
 
         # define widgets not to be rendered immediantly, but later on
@@ -112,8 +101,7 @@ class WebUI:
                 model_selector = gr.Dropdown(
                     list(self.class_names.keys()),
                     label="Task",
-                    info="Which task to perform - one model for"
-                    "each brain tumor type and brain extraction",
+                    info="Which task to perform registration for",
                     multiselect=False,
                     size="sm",
                 )
@@ -135,8 +123,8 @@ class WebUI:
             with gr.Row():
                 gr.Examples(
                     examples=[
-                        os.path.join(self.cwd, "RegLib_C01_1.nii"),
-                        os.path.join(self.cwd, "RegLib_C01_2.nii"),
+                        os.path.join(self.cwd, "ixi_image.nii.gz"),
+                        os.path.join(self.cwd, "ixi_image2.nii.gz"),
                     ],
                     inputs=file_output,
                     outputs=file_output,