Initial commit.

.idea/workspace.xml

@@ -2,6 +2,8 @@
 <project version="4">
   <component name="ChangeListManager">
     <list default="true" id="5dd22f22-8223-4d55-99f9-57d1e00622d7" name="Default Changelist" comment="Initial commit.">
+      <change beforePath="$PROJECT_DIR$/.idea/workspace.xml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/workspace.xml" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/app.py" beforeDir="false" afterPath="$PROJECT_DIR$/app.py" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/segmenter_model/utils.py" beforeDir="false" afterPath="$PROJECT_DIR$/segmenter_model/utils.py" afterDir="false" />
     </list>
     <option name="SHOW_DIALOG" value="false" />
@@ -50,7 +52,7 @@
       <option name="number" value="Default" />
       <option name="presentableId" value="Default" />
       <updated>1647350746642</updated>
-      <workItem from="1647350750956" duration="8634000" />
+      <workItem from="1647350750956" duration="8760000" />
     </task>
     <task id="LOCAL-00001" summary="Initial commit.">
       <created>1647352693910</created>
@@ -255,7 +257,14 @@
       <option name="project" value="LOCAL" />
       <updated>1647359422799</updated>
     </task>
-    <option name="localTasksCounter" value="30" />
+    <task id="LOCAL-00030" summary="Initial commit.">
+      <created>1647359586436</created>
+      <option name="number" value="00030" />
+      <option name="presentableId" value="LOCAL-00030" />
+      <option name="project" value="LOCAL" />
+      <updated>1647359586436</updated>
+    </task>
+    <option name="localTasksCounter" value="31" />
     <servers />
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   <component name="TypeScriptGeneratedFilesManager">

app.py

@@ -130,7 +130,7 @@ model, window_size, window_stride = create_model()
 
 def predict(input_img):
     input_img = Image.open(input_img)
-    transform = transforms.Compose([transforms.Resize(256, Image.BICUBIC), transforms.ToTensor()])
+    transform = get_transformations()
     input_img = transform(input_img)
     input_img = torch.unsqueeze(input_img, 0)
 

segmenter_model/utils.py

@@ -389,10 +389,6 @@ def inference(
                 seg_maps[i: i + WB] = model.forward(crops[i: i + WB], decoder_features=decoder_features,
                                                     encoder_features=encoder_features,
                                                     no_upsample=no_upsample)
-                # except:
-                #     print('Input of shape: {}'.format(crops[i:i + WB].shape))
-                #     assert False, "End after error."
-                # torch.cuda.empty_cache()
         windows["seg_maps"] = seg_maps
 
         im_seg_map = merge_windows(windows, window_size, ori_shape, no_softmax=decoder_features,