OpenCV dreadnautilus fishing script

main.py

import time
import subprocess
from subprocess import Popen, PIPE

import cv2
import scanf
import numpy as np
import pytesseract
from mss import mss

# Install maim, slop, and xdotool before using this script

# Frame delay
WAIT = 0.0333

# Pick screen region (need maim/slop installed)
process = Popen(['slop'], stdout=PIPE, stderr=PIPE)
geom_str,_ = process.communicate()
geom = scanf.scanf("%dx%d+%d+%d",str(geom_str)[:-1])
print(geom)
mon = {'top': geom[3], 'left': geom[2], 'width': geom[0], 'height': geom[1]}

def to_hsv(image): 
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
    return hsv

# Other potentially useful min/max HSV ranges

#    lower = np.array([0, 39, 0])
#    upper = np.array([179, 255, 255])

#    lower = np.array([54, 0, 144])
#    upper = np.array([128, 255, 255])

def create_mask(hsv):
    lower = np.array([168,0,159])
    upper = np.array([179,179,255])
    mask = cv2.inRange(hsv, lower, upper)
    return mask

def imgOptimize(mask):
    # Create horizontal kernel and dilate to connect text characters
    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5,3))
    dilate = cv2.dilate(mask, kernel, iterations=5)

    # Find contours and filter using aspect ratio
    # Remove non-text contours by filling in the contour
    cnts = cv2.findContours(dilate, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    cnts = cnts[0] if len(cnts) == 2 else cnts[1]
    for c in cnts:
        x,y,w,h = cv2.boundingRect(c)
        ar = w / float(h)
        if ar < 5:
            cv2.drawContours(dilate, [c], -1, (0,0,0), -1)

    # Bitwise dilated image with mask, invert, then OCR
    result = 255 - cv2.bitwise_and(dilate, mask)
    return result

def textProcess(image):
    data = pytesseract.image_to_string(image,lang='eng',config='--psm 6')
    return data

cnt = 0
active = True

# Remember to buff first and cast out line for the first time before launching the script.

with mss() as sct:
    while True:
 
        if cv2.waitKey(25) & 0xFF == ord('q'):
            cv2.destroyAllWindows()
            break

        last_time = time.time()
        mss_img = sct.grab(mon)
        img = np.array(mss_img)
        mask = create_mask(to_hsv(img))
        cv2.imshow('Screen View', mask)
        
        text = textProcess(mask)
        print(f"Text found: {text}")

        # Other blood moon fishing enemies:
        #  or "blood" in text.lower() or "hemo" in text.lower() or "wander" in text.lower()
        if ("dread" in text.lower() or "naut" in text.lower()):
            # Reel in fishing line. Wait until text is empty again
            print("DREADNAUTILUS DETECTED!!!")
            if active:
                subprocess.run(["xdotool","keydown","l","sleep","0.05","keyup","l"])
                print("Attempting to reel in..")
                active = False
        if (not active and text.strip() == ""):
                # Text is empty. We can cast the line again
                time.sleep(2)
                subprocess.run(["xdotool","keydown","l","sleep","0.05","keyup","l"])
                print("Attempting to cast out..")
                active = True
        
        if (cnt == 200):
            subprocess.run(["xdotool","keydown","b","sleep","0.05","keyup","b"])
            cnt = 0

        
        time.sleep(WAIT)
        cnt += 1

requirements.txt

numpy
opencv-python
pytesseract
mss
scanf