CursorMonitoring_script

import cv2
import numpy as np
import pynput
import time
import pyautogui
from random import randint

# Define the screenshot size
size = (70, 70)

# Set the threshold for movement detection in pixels
threshold = 10000

# Monitor the segmented image for changes
while True:

    # Get the mouse and keyboard controllers
    mouse = pynput.mouse.Controller()
    keyboard = pynput.keyboard.Controller()

    # Get the current mouse position
    x, y = pyautogui.position()

    # Take a screenshot at the mouse position
    screenshot = pyautogui.screenshot(region=(x - size[0] // 2, y - size[1] // 2, size[0], size[1]))

    # Convert the screenshot to grayscale
    gray = cv2.cvtColor(np.array(screenshot), cv2.COLOR_RGB2GRAY)

    # Fine-tune the dark and bright pixels using adaptive thresholding
    thresh = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY_INV, 11, 2)

    # Find the contours in the thresholded image
    contours, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    # If there are any contours, find the largest one
    if len(contours) > 0:
        largest_contour = max(contours, key=cv2.contourArea)

        # Create a mask for the largest contour
        mask = np.zeros_like(thresh)
        cv2.drawContours(mask, [largest_contour], -1, 255, -3)

        # If this is not the first frame, compare the new mask to the previous mask
        if 'prev_mask' in locals():
            # Calculate the absolute difference between the masks
            diff = cv2.absdiff(mask, prev_mask)

            # Count the number of white pixels in the difference image
            count = np.count_nonzero(diff)

            # If enough pixels have moved, print "movement detected"
            if count >= threshold:
                print("Collecting your fish...")
                keyboard.press(pynput.keyboard.Key.shift)
                time.sleep(1)
                mouse.click(pynput.mouse.Button.right, 1)
                keyboard.release(pynput.keyboard.Key.shift)
                delay = randint(2, 5)
                print("Recasting Fishing Line... " + str(delay) + "s")
                time.sleep(delay)


        # Store the current mask for comparison in the next frame
        prev_mask = mask

        time.sleep(0.0001)

        # Display the current screenshot and previous mask images
        cv2.imshow('screenshot', np.array(screenshot))
        cv2.imshow('prev_mask', prev_mask)

        # Wait for a key press to update the images
        cv2.waitKey(1)