updated texts

app.py

@@ -113,14 +113,7 @@ def make_user_plot(file_obj, idx: int):
 def demo():
     with gr.Blocks() as demo:
         gr.Markdown(
-            """
-            # deepest
-            **deepest** (short for **deep** learning parameter **est**imator) is a CNN trained to perform signal parameter estimation.
-            The corresponding paper can be found on [arxiv](https://arxiv.org/abs/2211.04846).
-            
-            This applet lets you explore the `deepest` with data from the validationset.
-            You can also upload your own data and see how it works for your signals.
-            """
+            TEXTS.introduction
         )
         
         with gr.Column():
@@ -139,22 +132,7 @@ def demo():
         
         with gr.Column():
             gr.Markdown(
-                """
-                ## Try with your own data.
-                Good news everyone! If you want to try `deepest` with your own data, here is your chance. 
-                Afterall there is no need to believe a paper making vague claims about an algorithms performance.
-                But keep in mind that slight deviations from the training-data distribution might throw off `deepest`.
-                Its a Neural Network after all.  
-                You can upload a `numpy` file (both `*.npy` and `*.npz` work) with your test data.
-                Ensure the data meets the requirements, such that you get good results. 
-                
-                ### Requirements
-                - complex-valued baseband data for the time-variant Channel transfer function $H(f,t)$ (e.g. from a channel-sounding campaign)
-                - array shape must be `batch_size x f_bins x t_bins`
-                - ideally `f_bins`=64 and `t_bins`=64, otherwise the data will be downsampled by the 2D-DFT, which might not be ideal in all scenarios.
-                
-                **Important** This demo runs on Huggingface. You are responsible for the data you upload. Do not upload any data that is confidential or unsuitable in this context.
-                """
+                TEXTS.try_your_own
             )
             
             with gr.Row():
@@ -171,12 +149,7 @@ def demo():
         user_slider.change(make_user_plot, [user_file, user_slider], [user_plot])
         
         gr.Markdown(
-            """
-            ## Acknowledgements
-            The authors acknowledge the financial support by the Federal Ministry of Education and Research of Germany in the project “Open6GHub” (grant number: 16KISK015).
-              
-            The authors give special thanks to Henning Schwanbeck (HPC team leader) of the TU Ilmenau Computer Center for his valuable support.
-            """
+            TEXTS.acknowledgements
         )
         
         gr.Markdown(

texts.toml

@@ -34,8 +34,8 @@ acknowledgements = """
 contact = """
     ## Contact
     If you have technical or scientific questions or encounter any issues in the use of this applet, please let me know.
-    You can either 
-        - write a me an email to [steffen.schieler@tu-ilmenau.de](mailto:steffen.schieler@tu-ilmenau.de)
-        - or start a new discussion in the [Community Tab](https://huggingface.co/spaces/EMS-TU-Ilmenau/deepest-demo/discussions)
+    You can either  
+    - write a me an email to [steffen.schieler@tu-ilmenau.de](mailto:steffen.schieler@tu-ilmenau.de)  
+    - or start a new discussion in the [Community Tab](https://huggingface.co/spaces/EMS-TU-Ilmenau/deepest-demo/discussions)  
 
     """