Update pages/Data Collection.py

pages/Data Collection.py

@@ -477,9 +477,9 @@ elif st.session_state.current_page == "explore_images_video":
 
     st.write("""
     In the next section, we'll dive into the exciting world of **image processing using OpenCV**. We'll cover how to:
-    - **Load, view, and edit images** using code.
-    - Learn the **basic tools and techniques** used in computer vision.
-    - Discover ways to **transform images and extract useful information**.
+    - **Read, display, and manipulate images** programmatically.
+    - Understand the **core operations** used in computer vision.
+    - Transform images to uncover hidden insights.
     
     Curious to see how?👇Click here to start your journey into OpenCV Basics!🚀
     """)
@@ -491,61 +491,22 @@ elif st.session_state.current_page == "explore_images_video":
     if st.button("Back to previous page"):
         navigate_to("main")
 
-# Navigation for OpenCV Operations Page
 elif st.session_state.current_page == "opencv_operations":
-    # Page Title
+    # Introduction to OpenCV Page
     st.markdown("""
-        <h2 style="color: #BB3385;">Image Operations with OpenCV</h2>
+        <h2 style="color: #BB3385;">Introduction to OpenCV</h2>
     """, unsafe_allow_html=True)
-
-    # Introduction to OpenCV
-    st.write("""
-        OpenCV (Open Source Computer Vision Library) is a powerful library used for image processing and computer vision tasks.
-        It provides various methods for handling images, such as reading, displaying, and modifying them.
-    """)
-
-    # Basic OpenCV Methods
-    st.markdown("""
-        <h3 style="color: #e25822;">Basic Operations:</h3>
-    """, unsafe_allow_html=True)
-
+    
+    # Informative Content
     st.write("""
-        - **`cv2.imread()`**: Reads an image from a file and returns it as a NumPy array.
-        - **`cv2.imshow()`**: Displays an image in a window.
-        - **`cv2.imwrite()`**: Saves an image to a specified file.
-        - **`cv2.resize()`**: Resizes an image to the desired dimensions.
-        - **`cv2.cvtColor()`**: Converts an image from one color space to another.
+    Before diving into OpenCV basics, let's understand a few key points:
+    - In Python, we have several libraries to work with images. One of the most powerful and popular libraries is **OpenCV**.
+    - With **OpenCV**, we can provide machines with **artificial vision**, enabling them to perceive and process visual information.
+    - OpenCV allows us to work with both **images and videos**, making it a versatile tool for various computer vision applications.
     """)
 
-    # Example Code
-    st.markdown("""
-        <h3 style="color: #5b2c6f;">Example Code:</h3>
-    """)
-
-    st.code("""
-import cv2
-
-# Read an image
-image = cv2.imread("path/to/your/image.jpg")
-
-# Display the image
-cv2.imshow("Image", image)
-cv2.waitKey(0)
-cv2.destroyAllWindows()
 
-# Save the image
-cv2.imwrite("output_image.jpg", image)
 
-# Resize the image
-resized_image = cv2.resize(image, (100, 100))
-
-# Convert to grayscale
-gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-    """, language="python")
-
-    # Go Back Button
-    if st.button("Go Back to Home Page"):
-        navigate_to("main")