OpenCV + Python Handling mouse and keyboard events and utilizing the trackbar

 

 

Hello. This is codingwalks.

Event handling is an important element that enables interaction between users and programs. OpenCV also provides this event handling function to allow more intuitive manipulation of images and videos. It is possible to perform certain actions by detecting mouse clicks or keyboard inputs, or to control frames by dynamically changing values ​​through the trackbar. In particular, the ability to move directly to a desired frame using the trackbar during video playback can be useful in video editing programs or analysis tools.

In this article, we will look at how to handle mouse and keyboard events using Python and OpenCV, and how to move video frames using the trackbar.

 

1. Mouse Event Processing

In OpenCV, you can process mouse events that occur in a window using the setMouseCallback() callback function. In addition, if you pass a parameter to param as a parameter of the function, you can use the passed variable to perform additional tasks. There are various events for mouse events, and the frequently used events are as follows.

Frequently Used Events

cv2.EVENT_LBUTTONDOWN	When the left mouse button is pressed
cv2.EVENT_RBUTTONDOWN	When the right mouse button is pressed
cv2.EVENT_MOUSEMOVE	When the mouse cursor moves within the window

Frequently used flags

cv2.EVENT_FLAG_LBUTTON	Left mouse button pressed
cv2.EVENT_FLAG_RBUTTON	Right mouse button pressed
cv2.EVENT_FLAG_MBUTTON	Middle mouse button pressed
cv2.EVENT_FLAG_CTRLKEY	Ctrl key pressed
cv2.EVENT_FLAG_SHIFTKEY	Shift key pressed
cv2.EVENT_FLAG_ALTKEY	Alt key pressed

Keyboard event handling example code

import cv2
import numpy as np

# Mouse event handler function
def mouse_event(event, x, y, flags, param):
    if event == cv2.EVENT_LBUTTONDOWN:
    	print(f"Left button clicked at ({x}, {y})")
    	if flags & cv2.EVENT_FLAG_SHIFTKEY:
        	cv2.rectangle(param, (x-5,y-5), (x+5,y+5), (0,0,255), 2)
        else:
        	cv2.circle(param, (x,y), 5, (0,0,255), 2)
    elif event == cv2.EVENT_RBUTTONDOWN:
        print(f"Right button clicked at ({x}, {y})")
        cv2.circle(param, (x, y), 5, (0, 0, 0), 2)
    elif event == cv2.EVENT_MOUSEMOVE:
        print(f"Mouse moved at ({x}, {y})")
        cv2.circle(param, (x, y), 1, (0, 255, 0), 2)

# Create a blank image
img = 255 * np.ones((300, 300, 3), dtype=np.uint8)
    
# Create an empty window
cv2.namedWindow('Mouse Event Window')

# Setting the mouse callback function
cv2.setMouseCallback('Mouse Event Window', mouse_event, img)

while True:    
    cv2.imshow('Mouse Event Window', img)
    # Exit with ESC key
    if cv2.waitKey(1) & 0xFF == 27:
        break

cv2.destroyAllWindows()

Mouse Event Example

Additional mouse events available

cv2.EVENT_LBUTTONUP	Triggered when the left mouse button is released
cv2.EVENT_RBUTTONUP	Triggered when the right mouse button is released
cv2.EVENT_LBUTTONDBLCLK	Triggered when the left mouse button is double-clicked
cv2.EVENT_RBUTTONDBLCLK	Triggered when the right mouse button is double-clicked
cv2.EVENT_MBUTTONDOWN	Triggered when the middle (wheel) mouse button is pressed
cv2.EVENT_MBUTTONUP	Triggered when the middle mouse button is released
cv2.EVENT_MBUTTONDBLCLK	Triggered when the middle mouse button is double-clicked
cv2.EVENT_MOUSEWHEEL	Triggered when the mouse wheel is rolled up (omnidirectional)
cv2.EVENT_MOUSEHWHEEL	Triggered when the mouse wheel is moved left or right (horizontal)

These additional mouse events allow you to detect and process a wider range of mouse inputs, such as using a double-click to quickly execute a specific function, or implementing zooming with the mouse wheel.

Example code to handle all mouse events

import cv2
import numpy as np

# A function that handles all mouse events
def mouse_event(event, x, y, flags, param):
    if event == cv2.EVENT_LBUTTONDOWN:
        print(f"Left button down at ({x}, {y})")
    elif event == cv2.EVENT_LBUTTONUP:
        print(f"Left button released at ({x}, {y})")
    elif event == cv2.EVENT_RBUTTONDOWN:
        print(f"Right button down at ({x}, {y})")
    elif event == cv2.EVENT_RBUTTONUP:
        print(f"Right button released at ({x}, {y})")
    elif event == cv2.EVENT_LBUTTONDBLCLK:
        print(f"Left button double clicked at ({x}, {y})")
    elif event == cv2.EVENT_RBUTTONDBLCLK:
        print(f"Right button double clicked at ({x}, {y})")
    elif event == cv2.EVENT_MBUTTONDOWN:
        print(f"Middle button down at ({x}, {y})")
    elif event == cv2.EVENT_MBUTTONUP:
        print(f"Middle button released at ({x}, {y})")
    elif event == cv2.EVENT_MBUTTONDBLCLK:
        print(f"Middle button double clicked at ({x}, {y})")
    elif event == cv2.EVENT_MOUSEMOVE:
        print(f"Mouse moved to ({x}, {y})")
    elif event == cv2.EVENT_MOUSEWHEEL:
        print(f"Mouse wheel scrolled vertically at ({x}, {y})")
    elif event == cv2.EVENT_MOUSEHWHEEL:
        print(f"Mouse horizontal wheel scrolled at ({x}, {y})")

# Create an empty window
cv2.namedWindow('Mouse Event Window')

# Setting the mouse callback function
cv2.setMouseCallback('Mouse Event Window', mouse_event)

while True:
    # Display a blank image in the window
    img = 255 * np.ones((300, 300, 3), dtype=np.uint8)
    cv2.imshow('Mouse Event Window', img)

    # Exit with ESC key
    if cv2.waitKey(1) & 0xFF == 27:
        break

cv2.destroyAllWindows()

 

2. Handling Keyboard Events

OpenCV can handle keyboard events using the waitKey() function. You can specify the action that occurs when a specific key is pressed. Typically, the ord() function is used to compare the ASCII values ​​of specific characters.

Example code for handling keyboard events

import cv2
import numpy as np

cv2.namedWindow('Keyboard Event Window')

while True:
    img = 255 * np.ones((300, 300, 3), dtype=np.uint8)
    cv2.imshow('Keyboard Event Window', img)

    key = cv2.waitKey(1) & 0xFF
    if key == ord('q'):
        print("Key 'q' pressed - Exiting")
        break
    elif key == ord('s'):
        print("Key 's' pressed - Saving image")
        cv2.imwrite('saved_image.jpg', img)
        
cv2.destroyAllWindows()

 

3. Using the Trackbar

Trackbar is a tool that allows you to create a slider in OpenCV and dynamically adjust variable values ​​through it. Trackbar is created using the createTrackbar() function. This allows you to change variable values ​​in real time based on user input.

Important arguments when creating a trackbar:

Trackbar name
Window name to which the trackbar belongs
Set minimum and maximum values
Callback function to be called when the trackbar position changes

 

Trackbar Example Code (Simple Slider)

import cv2
import numpy as np

# Trackbar callback function
def on_trackbar(val):
    print(f"Trackbar value: {val}")

cv2.namedWindow('Trackbar Window')

# Create trackbar (name, window name, initial value, maximum value, callback function)
cv2.createTrackbar('Slider', 'Trackbar Window', 0, 100, on_trackbar)

while True:
    img = 255 * np.ones((300, 300, 3), dtype=np.uint8)
    cv2.imshow('Trackbar Window', img)

    if cv2.waitKey(1) & 0xFF == 27:
        break

cv2.destroyAllWindows()

 

4. Controlling video frame movement with the trackbar

You can implement the ability to move to a specific frame in a video file using the trackbar. This makes it easier to control video playback.

Example code for controlling a video file with the trackbar

import cv2

# Trackbar callback function (frame change)
def on_trackbar(val):
    global cap
    cap.set(cv2.CAP_PROP_POS_FRAMES, val)

# Load video file
cap = cv2.VideoCapture('resources/TownCentreXVID.mp4')

# Check if the video file is opened
if not cap.isOpened():
    print("Error: Unable to open video file")
    exit()

# Total number of frames
total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))

# Create a window and set up the trackbar
cv2.namedWindow('Video Control')
cv2.createTrackbar('Frame', 'Video Control', 0, total_frames - 1, on_trackbar)

while True:
    ret, frame = cap.read()
    
    # End when end of video file is reached
    if not ret:
        break
    
    # Set current trackbar position
    current_frame = int(cap.get(cv2.CAP_PROP_POS_FRAMES))
    cv2.setTrackbarPos('Frame', 'Video Control', current_frame)

    # Frame display
    cv2.imshow('Video Control', frame)
    
    # Exit with ESC key
    if cv2.waitKey(1) & 0xFF == 27:
        break

cap.release()
cv2.destroyAllWindows()

Video Frame Trackbar

 

5. Conclusion

We have learned how to utilize mouse events, keyboard events, and trackbars in OpenCV. These event handling and interfaces allow us to control images and videos in a more interactive way. In particular, the ability to control video frames through trackbars is practical and can be applied to a variety of applications. We hope that this example will help you understand event handling and user interface implementation in OpenCV.

 

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★ All contents are referenced from the link below. ★

OpenCV: OpenCV-Python Tutorials