Update pages/Data Collection.py

pages/Data Collection.py

@@ -526,8 +526,7 @@ def image_details_page():
 
         st.write("""
         - Represents only two colors: **Black (0)** and **White (255)**.
-        - Used for simple image processing tasks where color isn't essential.
-        - **Disadvantage**: It only preserves black and white, so other colors (like red, green, or brown) are completely lost.
+        - **Limitation**: It only preserves black and white.
         - For example, by using the image's width and height (rows and columns), we can create a **2D array** where each pixel is represented by either 0 (black) or 255 (white). 
         """)
         
@@ -535,29 +534,21 @@ def image_details_page():
         st.markdown("<h3 style='text-align:; color: #4169E1;'>2. Grayscale</h3>", unsafe_allow_html=True)
 
         st.write("""
-        - Extends black and white to include **256 shades of gray**.
-        - Preserves brightness details but loses color information.
-        - **Disadvantage**: If the image has colors like red, green, or brown, it cannot preserve those since grayscale only represents shades of gray.
-        - After converting an image to grayscale, each pixel can take values from 0 (black) to 255 (white), with every intermediate value representing a shade of gray.
+        - 0 means **black** 1 means **white**
+        - Values between 1-254 represent various shades of gray.
+        - **Limitation**:
+        - Gray Scale images cannot preserve coloured images as it is having only gray shades
         """)
         
         # Subheading for RGB color space
-        st.markdown("<h3 style='text-align:; color: #483D8B;'>3. RGB (Red, Green, Blue)</h3>", unsafe_allow_html=True)
+        st.markdown("<h3 style='text-align:; color: #483D8B;'>3. RGB </h3>", unsafe_allow_html=True)
 
         st.write("""
-        - Combines three color channels: **Red**, **Green**, and **Blue**.
-        - Each channel can represent **256 shades** (0-255).
-        - By mixing different intensities of red, green, and blue, you can create over **16 million possible colors**.
-        - This is the most commonly used color space for colored images and is widely used in digital displays, cameras, and image processing tasks.
-        - In RGB color space, each pixel is represented by three values, one for each channel (Red, Green, Blue). The image is represented as a **3D array** where each pixel has three values (R, G, B).
+        - To represent coloured image we have to convert image in 3D array , Mixture of three 2D arrays is **RGB**.
+        - The value in each array ranges from R(0,255) ,G(0,255) ,B(0,255) 
+        - By mixing different intensities of red, green, and blue,we can create over **16 million possible colors**.
         """)
         
-        # Connecting the concepts
-        st.subheader("Key Differences Between 2D and 3D Arrays in Color Spaces")
-        st.write("""
-        - **2D Arrays**: Used in Black and White or Grayscale color spaces. Each pixel is represented by a single value (black/white or a shade of gray).
-        - **3D Arrays**: Used in RGB color space, where each pixel is represented by three values (Red, Green, Blue), forming a 3D structure of the image.
-        """)
         
     # Basic Operations Section
     elif page =="Basic Operations":