Update app.py

app.py

@@ -8,7 +8,7 @@ st.set_page_config(
 st.title("Enhancing the Performance of SVM and CNN Models in Detection and Classification of Cervical Cells in Pap Smear Images Using U-Net Architecture for Image Segmentation")
 st.write("A prototype for our U-Net Architecture for Image Segmentation of Cervical Cancer Cells, and SVM and CNN for Classification of Cervical Cancer Cells")
 st.write("Thesis Project by Group DJY of Mapua University")
-st.image("pages/Cervical-Cancer-Cells.jpg", caption='', width=650)
+st.image("pages/Cervical-Cancer-Cells.jpg", caption='', width=700)
 
 
 st.header("How does this app work?")
@@ -40,4 +40,4 @@ However, many of these models face challenges with image segmentation, particula
 This prototype seeks to improve upon existing machine learning models by incorporating the U-Net architecture, designed for precise image segmentation, to enhance the identification of cancerous cells in cervical samples, ultimately facilitating faster and more accurate diagnoses.
 """)
 
-st.sidebar.image("pages/Mapua-logo.png", width=250)
+st.sidebar.image("pages/Mapua-logo.png", width=300)