add output name setting, hide advanced options

predict-gui.py

@@ -30,7 +30,10 @@ parser.add_argument(
 )
 args = parser.parse_args()
 
-def process_file(input_file, config_file, weights_file, input_spectrometer_frequency=None,reference_spectrum=None, scale=None):
+def default_out_filename_from_input_filename(input_file):
+    return f"{Path(input_file.name).stem}_processed{Path(input_file.name).suffix}"
+
+def process_file(input_file, config_file, weights_file, input_spectrometer_frequency=None,reference_spectrum=None, scale=None, output_filename=None):
     if input_spectrometer_frequency == 0:
         input_spectrometer_frequency = None
     # Load configuration and initialize predictor
@@ -65,7 +68,10 @@ def process_file(input_file, config_file, weights_file, input_spectrometer_frequ
 
     # Prepare output data for download
     output_data = np.column_stack((input_freqs_input_ppm, output_prediction))
-    output_file = f"{Path(input_file).stem}_processed{Path(input_file).suffix}"
+    if output_filename is None or output_filename.strip() == "":
+        output_file = default_out_filename_from_input_filename(input_file)
+    else:
+        output_file = output_filename
     np.savetxt(output_file, output_data)
 
     # Create Plotly figure
@@ -128,11 +134,13 @@ def process_file(input_file, config_file, weights_file, input_spectrometer_frequ
     
     return fig, output_file
 
+
 # Gradio app
 with gr.Blocks() as app:
     gr.Markdown("# ShimNet Spectra Correction")
-    gr.Markdown("[ShimNet: A neural network for post-acquisition improvement of NMR spectra distorted by magnetic-field inhomogeneity](https://chemrxiv.org/engage/chemrxiv/article-details/67ef86686dde43c90860d315)")
-    gr.Markdown("Upload your input file, configuration, and weights to process the NMR spectrum.")
+    gr.Markdown("[ShimNet: A neural network for post-acquisition improvement of NMR spectra distorted by magnetic-field inhomogeneity](https://doi.org/10.1021/acs.jpcb.5c02632)")
+    gr.Markdown("Upload your input file and select the model to process the NMR spectrum. Select 'Custom' to provide your own configuration and weights files.")
+    gr.Markdown("Sample input files: https://huggingface.co/spaces/NMR-CeNT-UW/ShimNet/tree/main/sample_data")
 
     with gr.Row():
         with gr.Column():
@@ -144,12 +152,14 @@ with gr.Blocks() as app:
             config_file = gr.File(label="Custom Config File (.yaml)", visible=False, height=120)
             weights_file = gr.File(label="Custom Weights File (.pt)", visible=False, height=120)
 
-            scale_input = gr.Number(
-                label="Scale (Intensity Normalization)",
-                value=Defaults.SCALE,
-                info="Adjust the scaling factor for intensity normalization. Default is 16.",
-            )
-        
+            with gr.Accordion("Custom output file name / advanced options", open=False):
+                output_filename = gr.Textbox(label="Output File Name", placeholder="set automatically after input file upload", interactive=True)
+                scale_input = gr.Number(
+                    label="Scale (Intensity Normalization)",
+                    value=Defaults.SCALE,
+                    info="Adjust the scaling factor for intensity normalization. Default is 16.",
+                )
+
         with gr.Column():
             input_file = gr.File(label="Input File (.txt | .csv)", height=120)
             input_spectrometer_frequency = gr.Number(label="Input Spectrometer Frequency (MHz) (0 or empty if the same as in the loaded model)", value=None)
@@ -174,8 +184,23 @@ with gr.Blocks() as app:
         outputs=[config_file, weights_file]
     )
 
+    # Auto-populate output filename when input file is uploaded
+    def generate_output_filename(input_file, output_filename):
+        # do not overwrite if user has provided a filename
+        if output_filename is not None and output_filename.strip() != "":
+            return output_filename
+        if input_file is None:
+            return ""
+        return default_out_filename_from_input_filename(input_file)
+    
+    input_file.change(
+        generate_output_filename,
+        inputs=[input_file, output_filename],
+        outputs=[output_filename]
+    )
+
     # Process button click logic
-    def process_file_with_model(input_file, model_selection, config_file, weights_file, input_spectrometer_frequency, reference_spectrum_file, scale):
+    def process_file_with_model(input_file, output_filename, model_selection, config_file, weights_file, input_spectrometer_frequency, reference_spectrum_file, scale):
         if model_selection == "600 MHz":
             config_file = "configs/shimnet_600.yaml"
             weights_file = "weights/shimnet_600MHz.pt"
@@ -192,24 +217,14 @@ with gr.Blocks() as app:
             weights_file,
             input_spectrometer_frequency,
             reference_spectrum_file.name if reference_spectrum_file else None,
-            scale
+            scale,
+            output_filename
         )
 
     process_button.click(
         process_file_with_model,
-        inputs=[input_file, model_selection, config_file, weights_file, input_spectrometer_frequency, reference_spectrum_file, scale_input],
+        inputs=[input_file, output_filename, model_selection, config_file, weights_file, input_spectrometer_frequency, reference_spectrum_file, scale_input],
         outputs=[plot_output, download_button]
     )
 
 app.launch(share=args.share, server_name=args.server_name)
-
-# '#636efa',
-#  '#EF553B',
-#  '#00cc96',
-#  '#ab63fa',
-#  '#FFA15A',
-#  '#19d3f3',
-#  '#FF6692',
-#  '#B6E880',
-#  '#FF97FF',
-#  '#FECB52'