Update pages/LIFE_CYCLE_OF_MACHINE_LEARNING.py

pages/LIFE_CYCLE_OF_MACHINE_LEARNING.py

@@ -477,11 +477,153 @@ def Conversion_of_Images_page():
 
      # Navigation Button
     if st.button("Video capture and explanation"):
-        st.session_state.page = "Video capture and explanation"
+        st.session_state.page = "Video_capture_and_explanation"
 
        # Navigation Button
     if st.button("Back to Data Collection"):
         st.session_state.page = "data_collection"  
+
+
+#---------VIDEO CAPTURE AND EXPLANATION OF CV2.WAITKEY-----------
+
+
+
+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.
+
+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.
+
+Example
+Here’s an example that captures video from the default webcam and displays it:
+
+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('Live Video', 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
+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
+    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 -----###
+
+   st.markdown("""
+
+1. **Video Capture (`cv2.VideoCapture`)**: Opens and reads video either from the webcam or from a video file.
+   - **Method `cap.read()`**: Captures individual frames from the video source.
+   - **Releasing the capture (`cap.release()`)**: Ensures that the resources are freed once done.
+   
+2. **Key Handling (`cv2.waitKey`)**: Waits for user key input and processes it:
+   - **`cv2.waitKey(1)`**: Checks for key presses every 1 millisecond.
+   - **Exiting the loop**: Pressing the `'q'` key exits the video capture loop.
+
+This explanation provides both the purpose and practical use cases of `cv2.VideoCapture()` and `cv2.waitKey()` in video capture scenarios, including how the two work together to display video and handle key events effectively.
+     """)
+
+    # Navigation Button
+    if st.button("Affine Transformation Matrix"):
+        st.session_state.page = "Affine_Transformation_Matrix"
+
+       # Navigation Button
+    if st.button("Back to Data Collection"):
+        st.session_state.page = "data_collection"  
+
+
+
+
+        
 # ----------------- Semi-Structured Data Page -----------------
 def semi_structured_data_page():
     st.title(":orange[Semi-Structured Data]")
@@ -570,8 +712,8 @@ def main():
          operations_using_opencv_page()
     elif page == "Conversion_of_Images":
          Conversion_of_Images_page()
-    elif page == "video_capture_page":
-         video_capture_page
+    elif page == "Video_capture_and_explanation":
+         Video_capture_and_explanation_page()
 
         
 if __name__ == "__main__":