The below-mentioned Python 3 code-snippet allows you to skip/block Youtube ads. I’ve also used OpenCV and PyAutoGUI libraries to implement this project.
At first, you must install PyAutoGUI and OpenCV Python libraries. To do so, simply execute the below commands in the command line.
pip install pyautogui
pip install opencv-python
code.py
import cv2
import numpy as np
import pyautogui
import time
# faster version
# lopping over the template matching
# reading the templates
template3 = cv2.imread('template3.png', 0)
template4 = cv2.imread('template4.png', 0)
template5 = cv2.imread('template5.png', 0)
template6 = cv2.imread('template6.png', 0)
# setting the threshold for confidence in template matching
threshold = 0.7
# alert box for stopping criteria
pyautogui.alert(text = 'Keep the mouse pointer on the top left corner of screen to stop the program', title= 'Stopping Criteria')
# continuous loop to check for youtube ad
while True:
time.sleep(1)
im1 = pyautogui.screenshot()
im1 = np.asarray(im1.convert(mode = 'L'))
# im1.save('im1.png')
# im1 = cv2.imread('im1.png', 0)
# checking for template3
res = cv2.matchTemplate(im1, template3, cv2.TM_CCOEFF_NORMED)
loc = np.where(res >= threshold)
# checking if template is matched
if loc[0].size != 0:
# clicking on the first match
pyautogui.click(list(zip(*loc[::-1]))[0])
continue # continue loop from start without further execution of the loop
# checking for template4
res = cv2.matchTemplate(im1, template4, cv2.TM_CCOEFF_NORMED)
loc = np.where(res >= threshold)
# checking if template is matched
if loc[0].size != 0:
# clicking on the first match
pyautogui.click(list(zip(*loc[::-1]))[0])
continue # continue loop from start without further execution of the loop
# checking for template5
res = cv2.matchTemplate(im1, template5, cv2.TM_CCOEFF_NORMED)
loc = np.where(res >= threshold)
# checking if template is matched
if loc[0].size != 0:
# clicking on the first match
pyautogui.click(list(zip(*loc[::-1]))[0])
continue # continue loop from start without further execution of the loop
# checking for template6
res = cv2.matchTemplate(im1, template6, cv2.TM_CCOEFF_NORMED)
loc = np.where(res >= threshold)
# checking if template is matched
if loc[0].size != 0:
# clicking on the first match
pyautogui.click(list(zip(*loc[::-1]))[0])
# Stopping criteria
if pyautogui.position() == (0,0):
pyautogui.alert(text = 'Adskipper is Closed', title = 'Adskipper Closed')
break