first simple version of the text on the landing page.

dianna/dashboard/Home.py

@@ -38,31 +38,38 @@
 
 # Display the content of the selected page
 if selected == "Home":
-    st.image(str(data_directory / 'logo_smaller.png'))
+    st.image(str(data_directory / 'logo.png'), width = 360)
 
     st.markdown("""
     DIANNA (Deep Insight And Neural Network Analysis) is a Python package that brings explainable AI (XAI)
     to your research project.
+
     It wraps carefully selected XAI methods (explainers) in a simple, uniform interface.
     It's built by, with and for (academic) researchers and research software engineers
     working on machine learning projects.
+
     DIANNA supports the de-facto standard of neural network models - ONNX.
+
     ### Dashboard
     The DIANNA dashboard can be used for explanation of the behaviour of several ONNX models trained for the tasks
     and datasets presented
     in the [DIANNA Tutorials](https://github.com/dianna-ai/dianna/tree/main/tutorials#datasets-and-tasks).
+
     The dashboard shows the visual explanation of a models' decision on a selected data item
     by a selected XAI method (explainer).
     It allows you to compare the results of different explainers, as well as explanations
     of the top ranked predicted labels.
     The dashboard was created using [streamlit](https://streamlit.io/).
-    This dashboard has separate interfaces to the different data modalities supported by DIANNA:
+
+    There are separate interfaces to the different data modalities supported by DIANNA:
     Image, Text, Tabular, and Time series data.
+
     It primarily illustrates the examples from the DIANNA tutorials.
     It is also possible to upload own trained (onnx) model, a data item for which you would like
     the model's decision explanation and other data required by the specific explainer.
     You can then select the explainer you want to use and set its hyperparameters.
-    ### More information
+
+     ### More information
 
     - [Source code](https://github.com/dianna-ai/dianna)
     - [Documentation](https://dianna.readthedocs.io/)