Update pages/LIFE_CYCLE_OF_MACHINE_LEARNING.py

pages/LIFE_CYCLE_OF_MACHINE_LEARNING.py

@@ -486,116 +486,127 @@ def Conversion_of_Images_page():
 
 #---------VIDEO CAPTURE AND EXPLANATION OF CV2.WAITKEY-----------
 
+def Video_capture_and_explanation_page():
+    st.header("🎥 Video Capture with `cv2.VideoCapture()`")
 
-
-def  Video_capture_and_explanation_page():
-    st.header("🎥 Video Capture with `cv2.VideoCapture()")
     st.markdown("""
     **Purpose**: Captures live video from a webcam or reads a video file using OpenCV.
 
-### Syntax
-```python
-cap = cv2.VideoCapture(source)
-source:
-0: Refers to the default webcam (if you have one connected).
-'video.mp4': The path to a video file (can be any supported video format like .mp4, .avi).
-Key Methods
-cap.read(): Captures a frame-by-frame video from the source.
+    ### Syntax
+    ```python
+    cap = cv2.VideoCapture(source)
+    source:
+    0: Refers to the default webcam (if you have one connected).
+    'video.mp4': The path to a video file (can be any supported video format like .mp4, .avi).
+    ```
 
-Returns:
-ret: A Boolean indicating whether the frame was read correctly (True if successful).
-frame: The captured frame, represented as a NumPy array (this can be processed or displayed).
-cap.release(): Releases the video source when you are done capturing. It frees up system resources and allows you to safely close the video capture device or file.
+    Key Methods:
+    - cap.read(): Captures a frame-by-frame video from the source.
 
-Example
-Here’s an example that captures video from the default webcam and displays it:
+    Returns:
+    - ret: A Boolean indicating whether the frame was read correctly (True if successful).
+    - frame: The captured frame, represented as a NumPy array (this can be processed or displayed).
+    - cap.release(): Releases the video source when you are done capturing. It frees up system resources and allows you to safely close the video capture device or file.
 
-python
-Copy code
-import cv2
+    Example:
+    Here’s an example that captures video from the default webcam and displays it:
 
-# Open the default webcam (0)
-cap = cv2.VideoCapture(0)
+    ```python
+    import cv2
 
-while cap.isOpened():
-    ret, frame = cap.read()  # Capture frame-by-frame
-    if not ret:
-        break  # Exit if frame not read correctly
+    # Open the default webcam (0)
+    cap = cv2.VideoCapture(0)
 
-    cv2.imshow('Live Video', frame)  # Display the frame
+    while cap.isOpened():
+        ret, frame = cap.read()  # Capture frame-by-frame
+        if not ret:
+            break  # Exit if frame not read correctly
+        cv2.imshow('Live Video', frame)  # Display the frame
 
-    # Wait for 1 ms and exit if 'q' is pressed
-    if cv2.waitKey(1) & 0xFF == ord('q'):
-        break
+        # Wait for 1 ms and exit if 'q' is pressed
+        if cv2.waitKey(1) & 0xFF == ord('q'):
+            break
+
+    cap.release()  # Release the webcam
+    cv2.destroyAllWindows()  # Close all OpenCV windows
+    ```
+
+    How it Works:
+    - cv2.VideoCapture(0): Opens the default webcam (if available).
+    - cap.read(): Reads each frame from the video source.
+    - cv2.imshow('Live Video', frame): Displays each captured frame in a window.
+    - cap.release(): Releases the video capture object when done capturing frames.
+    - cv2.destroyAllWindows(): Closes all OpenCV windows to free up resources.
+    """)
 
-cap.release()  # Release the webcam
-cv2.destroyAllWindows()  # Close all OpenCV windows
-How it Works:
-cv2.VideoCapture(0): Opens the default webcam (if available).
-cap.read(): Reads each frame from the video source.
-cv2.imshow('Live Video', frame): Displays each captured frame in a window.
-cap.release(): Releases the video capture object when done capturing frames.
-cv2.destroyAllWindows(): Closes all OpenCV windows to free up resources.
-     """)
     ##----------##
     
-   st.header("⏱️ cv2.waitKey() for Key Event Handling")
-   st.markdown(""" Purpose:
-cv2.waitKey() is a key function used to handle keyboard events in OpenCV. It is commonly used to display images or video frames and wait for a user input.
-
-Syntax
-python
-Copy code
-cv2.waitKey(delay)
-delay:
-0: Waits indefinitely until a key is pressed. This is useful when displaying images or video and you want to hold the display open until a key is pressed.
-1: Waits for 1 millisecond. This is commonly used in real-time video streaming where the program keeps checking for user input every 1 millisecond.
-How it Works:
-cv2.waitKey(1): This line waits for a key press for 1 millisecond before checking if the user has pressed any key. If no key is pressed within that time, it proceeds to the next frame.
-Key Event: The function returns an integer value representing the ASCII code of the key pressed.
-For example, pressing the 'q' key returns 113 (the ASCII value for 'q').
-Example
-Here’s an example using cv2.waitKey() to exit the video capture loop when the 'q' key is pressed:
-
-python
-Copy code
-if cv2.waitKey(1) & 0xFF == ord('q'):
-    break
-ord('q'): Converts the 'q' character to its ASCII value (113).
-& 0xFF: Masks the higher bits of the returned value to only check for the lower 8 bits, ensuring correct handling of the key press.
-Why is cv2.waitKey() Important?
-It helps manage user input while displaying images or videos.
-Without cv2.waitKey(), the OpenCV window would immediately close after displaying the image/video, and you would not be able to interact with it.
-It enables frame-by-frame processing in real-time video processing (such as live video capture or webcam feeds).
-Example in Context:
-python
-Copy code
-import cv2
-
-# Open the default webcam (0)
-cap = cv2.VideoCapture(0)
-
-while cap.isOpened():
-    ret, frame = cap.read()  # Capture frame-by-frame
-    if not ret:
-        break  # Exit if frame not read correctly
-
-    cv2.imshow('Webcam Feed', frame)  # Display the frame
-
-    # Wait for 1 ms and exit if 'q' is pressed
+    st.header("⏱️ cv2.waitKey() for Key Event Handling")
+    st.markdown(""" 
+    Purpose:
+    cv2.waitKey() is a key function used to handle keyboard events in OpenCV. It is commonly used to display images or video frames and wait for a user input.
+
+    Syntax:
+    ```python
+    cv2.waitKey(delay)
+    ```
+
+    delay:
+    - 0: Waits indefinitely until a key is pressed. This is useful when displaying images or video and you want to hold the display open until a key is pressed.
+    - 1: Waits for 1 millisecond. This is commonly used in real-time video streaming where the program keeps checking for user input every 1 millisecond.
+
+    How it Works:
+    - cv2.waitKey(1): This line waits for a key press for 1 millisecond before checking if the user has pressed any key. If no key is pressed within that time, it proceeds to the next frame.
+    - Key Event: The function returns an integer value representing the ASCII code of the key pressed. For example, pressing the 'q' key returns 113 (the ASCII value for 'q').
+
+    Example:
+    Here’s an example using cv2.waitKey() to exit the video capture loop when the 'q' key is pressed:
+
+    ```python
     if cv2.waitKey(1) & 0xFF == ord('q'):
         break
+    ```
 
-cap.release()  # Release the webcam
-cv2.destroyAllWindows()  # Close all OpenCV windows
-Explanation:
-cv2.VideoCapture(0): Initializes the webcam.
-cap.read(): Captures each frame from the webcam.
-cv2.imshow('Webcam Feed', frame): Displays the captured frame.
-cv2.waitKey(1): Checks for key press every 1 millisecond. If the 'q' key is pressed, the loop breaks, and the webcam feed stops.
-cap.release(): Releases the webcam when done.
-cv2.destroyAllWindows(): Closes the OpenCV windows and cleans up resources.
-     """)
+    Explanation:
+    - ord('q'): Converts the 'q' character to its ASCII value (113).
+    - & 0xFF: Masks the higher bits of the returned value to only check for the lower 8 bits, ensuring correct handling of the key press.
+
+    Why is cv2.waitKey() Important?
+    - It helps manage user input while displaying images or videos.
+    - Without cv2.waitKey(), the OpenCV window would immediately close after displaying the image/video, and you would not be able to interact with it.
+    - It enables frame-by-frame processing in real-time video processing (such as live video capture or webcam feeds).
+
+    Example in Context:
+
+    ```python
+    import cv2
+
+    # Open the default webcam (0)
+    cap = cv2.VideoCapture(0)
+
+    while cap.isOpened():
+        ret, frame = cap.read()  # Capture frame-by-frame
+        if not ret:
+            break  # Exit if frame not read correctly
+
+        cv2.imshow('Webcam Feed', frame)  # Display the frame
+
+        # Wait for 1 ms and exit if 'q' is pressed
+        if cv2.waitKey(1) & 0xFF == ord('q'):
+            break
+
+    cap.release()  # Release the webcam
+    cv2.destroyAllWindows()  # Close all OpenCV windows
+    ```
+
+    Explanation:
+    - cv2.VideoCapture(0): Initializes the webcam.
+    - cap.read(): Captures each frame from the webcam.
+    - cv2.imshow('Webcam Feed', frame): Displays the captured frame.
+    - cv2.waitKey(1): Checks for key press every 1 millisecond. If the 'q' key is pressed, the loop breaks, and the webcam feed stops.
+    - cap.release(): Releases the webcam when done.
+    - cv2.destroyAllWindows(): Closes the OpenCV windows and cleans up resources.
+    """)
 
 ###------KEY POINTS -----###