Update pages/Data Collection.py

pages/Data Collection.py

@@ -1270,7 +1270,7 @@ elif st.session_state.current_page == "image_transformations":
 
     # Heading
     st.markdown("""
-        <h2 style="color: #9400d3;">What is Image Augmentation?</h2>
+        <h3 style="color: #9400d3;">What is Image Augmentation?</h3>
     """, unsafe_allow_html=True)
     
     # Definition
@@ -1278,7 +1278,7 @@ elif st.session_state.current_page == "image_transformations":
     Image augmentation is a method used to enhance the size and variety of an image dataset by applying transformations to existing images. 
     These transformations introduce variations while preserving the core features of the image, making it useful for training machine learning models to handle diverse inputs. 
     
-    ### How It Works
+    **How It Works**
     Image augmentation applies transformations like resizing, rotation, flipping, and more to the original image. These changes simulate real-world variations, ensuring that machine learning models can identify patterns even with differences in perspective, scale, or lighting conditions.
     
     The key idea is to preserve the original features of the image while introducing diversity. For example, if we take an image and apply five different transformations, we generate five new variations of that image. This provides the model with more data to learn from, improving its performance and ability to generalize.
@@ -1328,7 +1328,9 @@ elif st.session_state.current_page == "image_transformations":
     These transformations are linear, meaning the relationships between points in the image remain consistent.
     """)
 
-
+    st.image(
+        "https://huggingface.co/spaces/LakshmiHarika/MachineLearning/resolve/main/Images/affine_transformations.png",
+        use_container_width=True)