Linted code

demo/app.py

@@ -16,8 +16,7 @@ def main():
         "--share",
         type=int,
         default=0,
-        help="Whether to enable the app to be accessible online"
-        "-> setups a public link which requires internet access.",
+        help="Whether to enable the app to be accessible online" "-> setups a public link which requires internet access.",
     )
     args = parser.parse_args()
 

demo/src/convert.py

@@ -28,8 +28,4 @@ def nifti_to_obj(path, output="prediction.obj"):
             thefile.write("vn {0} {1} {2}\n".format(item[0], item[1], item[2]))
 
         for item in faces:
-            thefile.write(
-                "f {0}//{0} {1}//{1} {2}//{2}\n".format(
-                    item[0], item[1], item[2]
-                )
-            )
+            thefile.write("f {0}//{0} {1}//{1} {2}//{2}\n".format(item[0], item[1], item[2]))

demo/src/gui.py

@@ -141,17 +141,11 @@ class WebUI:
                                 [sidebar_left, sidebar_state],
                             )
 
-                            btn_clear_logs = gr.Button(
-                                "Clear logs", elem_id="logs-button"
-                            )
+                            btn_clear_logs = gr.Button("Clear logs", elem_id="logs-button")
                             btn_clear_logs.click(flush_logs, [], [])
 
-                        file_output = gr.File(
-                            file_count="single", elem_id="upload"
-                        )
-                        file_output.upload(
-                            self.upload_file, file_output, file_output
-                        )
+                        file_output = gr.File(file_count="single", elem_id="upload")
+                        file_output.upload(self.upload_file, file_output, file_output)
 
                         model_selector = gr.Dropdown(
                             list(self.class_names.keys()),
@@ -203,9 +197,7 @@ class WebUI:
                         with gr.Box():
                             with gr.Column():
                                 # create dummy image to be replaced by loaded images
-                                t = gr.AnnotatedImage(
-                                    visible=True, elem_id="model-2d"
-                                ).style(
+                                t = gr.AnnotatedImage(visible=True, elem_id="model-2d").style(
                                     color_map={self.class_name: "#ffae00"},
                                     height=512,
                                     width=512,
@@ -226,6 +218,4 @@ class WebUI:
         # https://gradio.app/sharing-your-app/
         # inference times > 60 seconds -> need queue():
         # https://github.com/tloen/alpaca-lora/issues/60#issuecomment-1510006062
-        demo.queue().launch(
-            server_name="0.0.0.0", server_port=7860, share=self.share
-        )
+        demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=self.share)

demo/src/inference.py

@@ -61,9 +61,7 @@ def run_model(
             os.path.join(model_path, task, "pipeline.json"),
         )
         rads_config.add_section("Runtime")
-        rads_config.set(
-            "Runtime", "reconstruction_method", "thresholding"
-        )  # thresholding, probabilities
+        rads_config.set("Runtime", "reconstruction_method", "thresholding")  # thresholding, probabilities
         rads_config.set("Runtime", "reconstruction_order", "resample_first")
         rads_config.set("Runtime", "use_preprocessed_data", "False")
 
@@ -77,13 +75,7 @@ def run_model(
 
         # rename and move final result
         os.rename(
-            "./result/prediction-"
-            + splits[0]
-            + "/T0/"
-            + splits[0]
-            + "-t1gd_annotation-"
-            + name
-            + ".nii.gz",
+            "./result/prediction-" + splits[0] + "/T0/" + splits[0] + "-t1gd_annotation-" + name + ".nii.gz",
             "./prediction.nii.gz",
         )
         # Clean-up