Update pages/LIFE_CYCLE_OF_MACHINE_LEARNING.py

pages/LIFE_CYCLE_OF_MACHINE_LEARNING.py

@@ -329,6 +329,158 @@ def  operations_using_opencv_page():
     if st.button("Back to Data Collection"):
         st.session_state.page = "data_collection"  
 
+##------------CONVERSION OF IMAGE-----------------
+import streamlit as st
+
+def Conversion_of_Images_page():
+    # Header for Image Conversion
+    st.header("🔄 Converting Images Between Different Color Spaces")
+
+    st.markdown("""
+    **OpenCV supports many color spaces for image processing.**
+
+    **Common Conversions:**
+    
+    - **BGR to Grayscale:** Converts a color image to grayscale.
+    - **BGR to RGB:** Converts from OpenCV's default BGR format to the standard RGB format.
+    - **BGR to HSV:** Converts the image to the HSV (Hue, Saturation, Value) color space.
+
+    **Examples of Conversions:**
+
+    ```python
+    import cv2
+
+    # Load the image
+    image = cv2.imread('image.jpg')
+
+    # Convert BGR to Grayscale
+    gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+    # Convert BGR to RGB
+    rgb_image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+
+    # Convert BGR to HSV
+    hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
+    ```
+
+    **Why Convert Color Spaces?**
+    - **Grayscale:** Useful for reducing image complexity in tasks like edge detection.
+    - **RGB:** Standard format for visualization in libraries like `matplotlib`.
+    - **HSV:** Useful for color-based segmentation, as it separates color information from brightness.
+    """)
+
+    # Header for Splitting Channels
+    st.header("🔹 Splitting Color Channels in an Image")
+
+    st.markdown("""
+    **Splitting an image into its individual color channels (B, G, R) allows you to analyze or modify each channel independently.**
+
+    **Syntax:**
+    ```python
+    b, g, r = cv2.split(image)
+    ```
+
+    **Example:**
+    ```python
+    import cv2
+
+    # Load the image
+    image = cv2.imread('image.jpg')
+
+    # Split the image into Blue, Green, and Red channels
+    blue_channel, green_channel, red_channel = cv2.split(image)
+
+    # Display the channels separately (Optional)
+    cv2.imshow('Blue Channel', blue_channel)
+    cv2.imshow('Green Channel', green_channel)
+    cv2.imshow('Red Channel', red_channel)
+    cv2.waitKey(0)
+    cv2.destroyAllWindows()
+    ```
+
+    **Explanation:**
+    - The `cv2.split()` function returns the Blue, Green, and Red channels as separate images (grayscale format).
+    """)
+
+    # Header for Merging Channels
+    st.header("🔹 Merging Color Channels in an Image")
+
+    st.markdown("""
+    **You can merge the individual channels back into a color image using `cv2.merge()`.**
+
+    **Syntax:**
+    ```python
+    merged_image = cv2.merge((b, g, r))
+    ```
+
+    **Example:**
+    ```python
+    import cv2
+
+    # Load the image
+    image = cv2.imread('image.jpg')
+
+    # Split the image into channels
+    b, g, r = cv2.split(image)
+
+    # Merge the channels back into a color image
+    merged_image = cv2.merge((b, g, r))
+
+    # Display the merged image
+    cv2.imshow('Merged Image', merged_image)
+    cv2.waitKey(0)
+    cv2.destroyAllWindows()
+    ```
+
+    **Explanation:**
+    - The `cv2.merge()` function takes a tuple of channels `(b, g, r)` and combines them back into a single color image.
+    - You can manipulate the individual channels before merging to achieve different effects.
+    """)
+
+    # Header for Combining with Modifications
+    st.header("🎨 Modifying Channels Before Merging")
+
+    st.markdown("""
+    **You can modify each channel (e.g., increase brightness in the red channel) before merging them back together.**
+
+    **Example:**
+    ```python
+    import cv2
+
+    # Load the image
+    image = cv2.imread('image.jpg')
+
+    # Split channels
+    b, g, r = cv2.split(image)
+
+    # Increase the intensity of the red channel
+    r = cv2.add(r, 50)
+
+    # Merge the modified channels
+    modified_image = cv2.merge((b, g, r))
+
+    # Display the modified image                            
+    cv2.imshow('Modified Image', modified_image)
+    cv2.waitKey(0)
+    cv2.destroyAllWindows()
+    ```
+
+    **Explanation:**
+    - In this example, `cv2.add(r, 50)` increases the intensity of the red channel by 50.
+    - After modification, the channels are merged back to create the final image.
+    """)
+
+
+     # Navigation Button
+    if st.button("Video capture and explanation of cv2.waitKey"):
+        st.session_state.page = "Video capture and explanation of cv2.waitKey"
+
+    # Navigation Button
+    if st.button("Back to Data Collection"):
+        st.session_state.page = "data_collection"
+
+
+
 
 
 
@@ -418,6 +570,9 @@ def main():
         introduction_to_image_page()
     elif page == "operations_using_opencv":
          operations_using_opencv_page()
-    
+    elif page == "Conversion_of_Images_page"
+         Conversion_of_Images_page()
+    elif page == "video_capture_cv2.waitKey()_page"
+         video_capture_cv2.waitKey()_page
 if __name__ == "__main__":
     main()