Update pages/1_Introduction.py


pages/1_Introduction.py

@@ -4,26 +4,7 @@ import base64
 import io
 
 # Base64 encoded image string (ensure the base64 string is complete)
-encoded_image = "UklGRrICBgBXRUJQVlA4IKrbBABQ9xCdASoABwAEPjEWiUOiISUmJZYbuMAGCWNsiXpgHwljA+sbSoKb/m/ZfJS/8fokeQ9+Mnxx"
 
-# Decode Base64 string to image and convert to PNG format (if necessary)
-def decode_base64_image(encoded_str):
-    try:
-        # Decode the base64 string
-        img_data = base64.b64decode(encoded_str)
-        # Create a BytesIO object from the image data
-        img = Image.open(io.BytesIO(img_data))
-        
-        # If the image is in a WebP format or any other format that PIL struggles with, convert to PNG
-        if img.format not in ['PNG', 'JPEG']:
-            img = img.convert("RGB")  # Convert to RGB if it's not already
-            img = img.convert("P")  # Convert to PNG if necessary
-        
-        return img
-    except Exception as e:
-        # Handle any errors during decoding and show error message
-        st.error(f"Error decoding image: {e}")
-        return None
 
 # Title and introduction
 st.title('Understanding Machine Learning: Teaching Machines Like Children')
@@ -35,9 +16,8 @@ In this app, we'll use the analogy of a father teaching his child to explain the
 """)
 
 # Display the image
-image = decode_base64_image(encoded_image)
-if image:
-    st.image(image, caption='A father teaching his child by showing dog and cat pictures')
+
+    st.image(r"C:\Users\USER\Downloads\WhatsApp Image 2024-12-28 at 14.09.31.jpeg", caption='A father teaching his child by showing dog and cat pictures')
 
 # Supervised Learning Explanation
 st.header('Supervised Learning')