Update pages/7_Unstructured_data.py

pages/7_Unstructured_data.py

@@ -644,16 +644,11 @@ if file_type == "VIDEO":
     - **`release()`**: Releases the video capture object and closes the video stream.
     - **`cv2.namedWindow()`**:It actually creates a pop-up window and all the features of pop-up window will be created
     - **`cv2.imshow()`**: As it is not creating pop-up window ,it internally calls the namedWindow() where we can create our own pop-up window
-    - **`cv2.waitKey()`**: It internally creates a po-up window and for that window it is going to add delay 
-        
-    - Waits for a key event for a specified amount of time (in milliseconds). It returns the ASCII value of the key pressed.
-            
-    -If 0 is passed, it waits indefinitely until a key is pressed.
+    - **`cv2.waitKey()`**: It internally creates a po-up window and for that window it is going to add delay.Waits for a key event for a specified amount of time (in milliseconds). It returns the ASCII value of the key pressed.If 0 is passed, it waits indefinitely until a key is pressed.
     - **`cv2.destroyAllWindows()`**: Closes all OpenCV windows that were opened during the program's execution.
     - **`cv2.MouseCallBack()`**: It is a technique where we can make lot of things automated
     - **`cv2.SetMouseCallBack()`**:It will be automatically activated when we hover the mouse inside pop-up window.
-
-    -It is going to call user-defined function which tracks the events of mouse 
+    - It is going to call user-defined function which tracks the events of mouse 
     - It contains 5 parameters
     - **5 parameters:**
     - def fun(event,x,yflags,param):
@@ -665,5 +660,147 @@ if file_type == "VIDEO":
     These methods are useful in forming the foundation of real-time video processing in OpenCV, 
     and also essential for handling the display and closing of images in OpenCV applications. 
     """)
+    
+    st.subheader("**Reading and Displaying a Video**")
+    st.code("""
+    import cv2
+    # Open the video file
+    video = cv2.VideoCapture("path_to_video.mp4")
+    # Loop to read and display frames
+    while True:
+        success, frame = video.read()  # Read a frame
+        if not success:
+            print("Video Ended")
+            break
+        cv2.imshow("Video Playback", frame)  # Display the frame
+    # Break loop on 'q' key press
+        if cv2.waitKey(1) & 255 == ord('q'):
+            break
+    video.release()  # Release the video file
+    cv2.destroyAllWindows()  # Close all OpenCV windows
+    """, language="python")
+
+    st.markdown("---")
+    st.subheader("**Understanding `cv2.waitKey()` and Key Input**")
+    st.write("""
+    The line `if cv2.waitKey(1) & 255 == ord('q'):` is used in OpenCV to handle keyboard input while processing video frames. Here’s a breakdown:
+    - **`cv2.waitKey(1)`**:
+      - Waits for a key press for `1` millisecond.
+      - Returns the ASCII value of the key pressed, or `-1` if no key is pressed.
+    - **`& 255`**:
+      - Extracts only the last 8 bits (ASCII value).
+    - **`ord('q')`**:
+      - Provides the ASCII value of the character `'q'`.
+      - The condition checks if the user pressed the `'q'` key to quit the program.
+    """)
+
+    st.header("**Capturing and Saving a Specific Frame**")
+    st.markdown("""
+    - Use OpenCV to capture a specific frame from a video and save it as an image file.
+    """)
+
+    st.subheader("Example: Saving a Frame")
+    st.code("""
+    import cv2
+    video = cv2.VideoCapture("path_to_video.mp4")  # Replace with 0 for webcam
+    while True:
+        success, frame = video.read()
+        if not success:
+        break
+        cv2.imshow("Video", frame)
+    # Save frame on 's' key press
+        if cv2.waitKey(1) & 255 == ord('s'):
+            cv2.imwrite("captured_frame.jpg", frame)
+            print("Frame saved as captured_frame.jpg")
+    # Break loop on 'q' key press
+        if cv2.waitKey(1) & 255 == ord('q'):
+            break
+    video.release()
+    cv2.destroyAllWindows()
+    """, language="python")
+
+
+    st.header("**Capturing Video from Webcam**")
+    st.markdown("""
+    - The `cv2.VideoCapture()` function can also be used to capture live video from your webcam or connected camera devices.
+    """)
+
+    st.subheader("**Example of Capturing Video from Webcam**")
+    st.code("""
+    import cv2
+    # Open video capture (0 for primary webcam)
+    video = cv2.VideoCapture(0)
+    # Loop to read frames
+    while True:
+        success, frame = video.read()  # Read a frame
+        if not success:
+            break
+        cv2.imshow("Webcam", frame)  # Display the frame
+    # Break loop on 'q' key press
+        if cv2.waitKey(1) & 255 == ord('q'):
+            break
+    video.release()  # Release the video capture object
+    cv2.destroyAllWindows()  # Close all OpenCV windows
+    """, language="python")
+
+    st.header("**Processing Video: Converting to Grayscale**")
+    st.markdown("""
+    You can process each frame of the video in real-time.By following steps:
+    - Convert each frame of a video to grayscale.
+    - Display the processed video.
+    """)
+
+    st.subheader("**Example of Converting Video to Grayscale**")
+    st.code("""
+    import cv2
+    # Open the video file
+    video = cv2.VideoCapture("path_to_video.mp4")
+    # Loop to read and process frames
+    while True:
+        success, frame = video.read()  # Read a frame
+        if not suc:
+            break
+        gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)  # Convert frame to grayscale
+        cv2.imshow("Grayscale Video", gray_frame)  # Display the processed frame
+    # Break loop on 'q' key press
+        if cv2.waitKey(30) & 255 == ord('q'):
+            break
+    video.release()  # Release the video file
+    cv2.destroyAllWindows()  # Close all OpenCV windows
+    """, language="python")
+
+    st.header("**Splitting Channels in a Video Frame**")
+    st.markdown("""
+    - You can split the three color channels (Blue, Green, and Red) from a video frame and process them individually.
+    """)
+
+    st.subheader("Example: Splitting Video Frame Channels")
+    st.code("""
+    import cv2
+    # Open video capture
+    video = cv2.VideoCapture("path_to_video.mp4")  # Replace with 0 for webcam
+    while True:
+        success, frame = video.read()
+        if not success:
+            break
+    # Split the frame into channels
+        b, g, r = cv2.split(frame)
+    # Merge and display individual channels
+        blue_img = cv2.merge([b, g*0, r*0])
+        green_img = cv2.merge([b*0, g, r*0])
+        red_img = cv2.merge([b*0, g*0, r])
+        cv2.imshow("Original Frame", frame)
+        cv2.imshow("Blue Channel", blue_img)
+        cv2.imshow("Green Channel", green_img)
+        cv2.imshow("Red Channel", red_img)
+    # Break loop on 'q' key press
+        if cv2.waitKey(1) & 255 == ord('q'):
+            break
+    video.release()
+    cv2.destroyAllWindows()
+    """, language="python")
+
+    
+