Update pages/Data Collection.py

pages/Data Collection.py

@@ -704,7 +704,51 @@ elif st.session_state.current_page == "image_operations":
     In this section, we’ll learn how to create different types of images, split them into their color channels, and convert between various color spaces to manipulate images more effectively.
     """)
 
+    # Heading for Creating Black and White Image
+    st.markdown("""
+        <h3 style="color: #9400d3;">Creating a Black and White Image</h3>
+    """, unsafe_allow_html=True)
+    
+    # Explanation
+    st.write("""
+    In OpenCV, black and white images are created by filling a matrix with pixel values:
+    - **Black image**: All pixel values are set to 0.
+    - **White image**: All pixel values are set to 255.
+    """)
+    
+    # Code example
+    st.code("""
+    white_img = np.full((500, 500), 255, dtype=np.uint8)  # Create a white image
+    
+    black_img = np.zeros((500, 500), dtype=np.uint8)    # Create a black image
     
+    # Display the images
+    cv2.imshow("White", white_img)
+    cv2.imshow("Black", black_img)
+    cv2.waitKey(0)  # 0 means infinite delay
+    cv2.destroyAllWindows()
+    """, language="python")
+
+    # Heading for Creating Grayscale Image
+    st.markdown("""
+        <h3 style="color: #9400d3;">Creating a Grayscale Image</h3>
+    """, unsafe_allow_html=True)
+    
+    # Explanation
+    st.write("""
+    In OpenCV, grayscale images are created by filling a matrix with pixel intensity values. The values range from 0 (black) to 255 (white).
+    """)
+    
+    # Code example
+    st.code("""
+    gray_img = np.full((500, 500), 127, dtype=np.uint8)  # Create a grayscale image (127 represents medium gray)
+    
+    # Display the grayscale image
+    cv2.imshow("Grayscale", gray_img)
+    cv2.waitKey(0)  # 0 means infinite delay
+    cv2.destroyAllWindows()
+    """, language="python")
+