Update pages/3_Life Cycle Of ML Project.py

pages/3_Life Cycle Of ML Project.py

@@ -186,7 +186,7 @@ elif st.session_state.page == "unstructured_data":
         st.session_state.page = "introduction_to_image"
 
 # ----------------- Introduction to Image -----------------
-def introduction_to_image_page():
+elif st.session_state.page == "Introduction_to_image":
     st.header("🖼️ What is Image")
     st.markdown("""
    An image is a two-dimensional visual representation of objects, people, scenes, or concepts. It can be captured using devices like cameras, scanners, or created digitally. Images are composed of individual units called pixels, which contain information about brightness and color.
@@ -260,7 +260,7 @@ Common Color Spaces:
  #       ---------- OPERATIONS USING OPENCV --------------------------------
 
 
-def  operations_using_opencv_page():
+elif st.session_state.page == "operations_using_opencv":
     # Header and description for cv2.imread
     st.header("🗂️ Reading an Image with cv2.imread()")
     st.markdown("""
@@ -344,7 +344,7 @@ def  operations_using_opencv_page():
 ##------------CONVERSION OF IMAGE-----------------
 
 
-def Conversion_of_Images_page():
+elif st.session_state.page == "operations_using_opencv":
     # Header for Image Conversion
     st.header("🔄 Converting Images Between Different Color Spaces")
 
@@ -468,7 +468,7 @@ def Conversion_of_Images_page():
 
 #---------VIDEO CAPTURE AND EXPLANATION OF CV2.WAITKEY-----------
 
-def Video_capture_and_explanation_page():
+elif st.session_state.page == "Video_capture_and_explanation_page":
     st.header("🎥 Video Capture with `cv2.VideoCapture()`")
 
     st.markdown("""
@@ -601,7 +601,7 @@ This explanation provides both the purpose and practical use cases of `cv2.Video
 
 
 
-def affine_transformation_matrix():
+elif st.session_state.page == "affine_transformation_matrix":
     # Header for Affine Transformation Matrix
     st.header("Affine Transformation Matrix")