Update app.py

app.py

@@ -1,4 +1,3 @@
-#working code
 import streamlit as st
 from PIL import Image
 from transformers import pipeline
@@ -134,14 +133,9 @@ if st.button("Generate HeatMap & DataFrame"):
         worksheet = writer.sheets['Sheet1']
 
         # Set the column width and row height
-        worksheet.set_column('A:G', 8)  # Set width for columns A-G
-        worksheet.set_column('H:H', 22)  # Set width for column H (Image Name)   
-        worksheet.set_column('I:I', 14)  # Set width for column I (Image Size)   
-        worksheet.set_column('J:J', 12)  # Set width for column J (Image View)   
-        worksheet.set_column('K:K', 12)  # Set width for column K (Image Num)
-
-
-        
+        worksheet.set_column('A:I', 20)  # Set width for columns A-I
+        worksheet.set_column('J:J', 30)  # Set width for column J (Image View)
+        worksheet.set_column('K:K', 15)  # Set width for column K (Image Num)
         for row_num in range(len(df_emotions) + 1):  # +1 to include the header row
             worksheet.set_row(row_num, 38)  # Set the row height to 38
 
@@ -151,7 +145,18 @@ if st.button("Generate HeatMap & DataFrame"):
             image_stream = io.BytesIO()
             image.save(image_stream, format='PNG')
             image_stream.seek(0)
-            worksheet.insert_image(f'J{idx + 2}', 'image.png', {'image_data': image_stream})
+            # Calculate the scaling factor to fit the image inside the cell
+            cell_width = 64
+            scale_factor = cell_width / image.width
+            # Insert the image into the cell
+            worksheet.insert_image(f'J{idx + 2}', 'image.png', {
+                'image_data': image_stream,
+                'x_scale': scale_factor,
+                'y_scale': scale_factor,
+                'x_offset': 2,
+                'y_offset': 2,
+                'positioning': 1
+            })
 
         # Close the writer object
         writer.close()