Update app.py

app.py

@@ -16,33 +16,51 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 # Load PathDino model and image transforms
 model, image_transforms = get_pathDino_model("PathDino512.pth")
 
-# Increase the width of the sidebar
-st.write(
-    f"""
-    <style>
-    .sidebar .sidebar-content {{
-        width: 420px;
-    }}
-    </style>
-    """
-)
 
 st.sidebar.markdown("### PathDino")
 st.sidebar.markdown(
-    "PathDino is a lightweight Histopathology transformer consisting of just five small vision transformer blocks. "
+    "PathDino is a lightweight histopathology transformer consisting of just five small vision transformer blocks. "
     "PathDino is a customized ViT architecture, finely tuned to the nuances of histology images. It not only exhibits "
     "superior performance but also effectively reduces susceptibility to overfitting, a common challenge in histology "
     "image analysis.\n\n"
 )
 
+
 default_image_url_compare = "images/HistRotate.png"
-st.sidebar.image(default_image_url_compare, caption='A 360 rotation augmentation for training models on histopathology images. Unlike training on natural images where the rotation may change the context of the visual data, rotating a histopathology patch does not change the context and it improves the learning process for better reliable embedding learning.', width=300)
+st.sidebar.image(default_image_url_compare, caption='A 360 rotation augmentation for training models on histopathology images. Unlike training on natural images where the rotation may change the context of the visual data, rotating a histopathology patch does not change the context and it improves the learning process for better reliable embedding learning.', width=500)
 
 default_image_url_compare = "images/FigPathDino_parameters_FLOPs_compare.png"
-st.sidebar.image(default_image_url_compare, caption='PathDino Vs its counterparts. Number of Parameters (Millions) vs the patch-level retrieval with macro avg F-score of majority vote (MV@5) on CAMELYON16 dataset. The bubble size represents the FLOPs.', width=300)
+st.sidebar.image(default_image_url_compare, caption='PathDino Vs its counterparts. Number of Parameters (Millions) vs the patch-level retrieval with macro avg F-score of majority vote (MV@5) on CAMELYON16 dataset. The bubble size represents the FLOPs.', width=500)
 
 default_image_url_compare = "images/ActivationMap.png"
-st.sidebar.image(default_image_url_compare, caption='Attention Visualization. When visualizing attention patterns, our PathDino transformer outperforms HIPT-small and DinoSSLPath, despite being trained on a smaller dataset of 6 million TCGA patches. In contrast, DinoSSLPath and HIPT were trained on much larger datasets, with 19 million and 104 million TCGA patches, respectively.', width=300)
+st.sidebar.image(default_image_url_compare, caption='Attention Visualization. When visualizing attention patterns, our PathDino transformer outperforms HIPT-small and DinoSSLPath, despite being trained on a smaller dataset of 6 million TCGA patches. In contrast, DinoSSLPath and HIPT were trained on much larger datasets, with 19 million and 104 million TCGA patches, respectively.', width=500)
+
+
+st.sidebar.markdown("### Citation")
+# Create a code block for citations
+st.sidebar.markdown("""
+```markdown
+@article{alfasly2023PathDino,
+  title={Rotation-Agnostic Representation Learning for Histopathological Image Analysis},
+  author={Saghir, Alfasly and Abubakr, Shafique and Peyman, Nejat and Jibran, Khan and Areej, Alsaafin and  Ghazal, Alabtah and H.R.Tizhoosh},
+  journal={arXiv preprint arXiv:xxxx.xxxxx},
+  year={2023}""")
+
+# Rhazes Lab and Mayo Clinic Logos
+st.sidebar.markdown("\n\n")
+# Create a two-column layout for logos and text
+col1, col2 = st.sidebar.columns(2)
+
+# Logo and text for My Logo Lab
+url_logo_lab = "images/rhazes_lab_logo.png"
+with col1:
+    st.image(url_logo_lab, width=150)
+# Logo and text for My Logo Company
+url_logo_company = "images/Mayo_Clinic_logo.png"
+with col2:
+    st.image(url_logo_company, width=150)
+st.sidebar.markdown("Rhazes Lab, \n Department of Artificial Intelligence and Informatics, \n Mayo Clinic, \n Rochester, MN, USA")
+
 
 
 
@@ -77,7 +95,7 @@ def generate_activation_maps(image):
     return attention_list
 
 # Streamlit UI
-st.title("PathDino - Compact ViT for Histopathology Image Analysis")
+st.title("PathDino - Compact ViT for histopathology Image Analysis")
 st.write("Upload a histology image to view the activation maps.")
 
 # uploaded_image = st.file_uploader("Upload an image", type=["jpg", "png", "jpeg"])