钓鱼小游戏的py脚本 cv2.matchTemplate

Question

I am trying to make a script for fishing minigame, there is a post with a fishing script for albion online, the problem is that in this game the pointer is very thin and there are many different textures and colors, to the simple grayscale matching works good on one part of the slider (for example on the water texture), sometimes work on others(trees texture) and does not work on the third (ex. sky). If I change to lower threshold it activates often without matching.

screen

import numpy as np
import cv2
from mss.windows import MSS as mss
from PIL import Image
import time
import pyautogui as pg
import cv2
import mss
import numpy

template = cv2.imread("perfect3.png", cv2.IMREAD_GRAYSCALE)
w, h = template.shape[::-1]
fgbg = cv2.createBackgroundSubtractorMOG2(
    history=10,
    varThreshold=2,
    detectShadows=False)

with mss.mss() as sct:
    monitor = {"top": 344, "left": 4419, "width": 150, "height": 666}

    while "Screen capturing":
        last_time = time.time()
        img = numpy.array(sct.grab(monitor))
        gray_frame = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        res = cv2.matchTemplate(gray_frame, template, cv2.TM_CCOEFF_NORMED)
        loc = np.where(res >= 0.85)
        for pt in zip(*loc[::-1]):
            cv2.rectangle(img, pt, (pt[0] + w, pt[1] + h), (0, 255, 0), 3)
            print('click')
        cv2.imshow("OpenCV/Numpy normal", img)

        key = cv2.waitKey(1)
        if cv2.waitKey(25) & 0xFF == ord("q"):
            cv2.destroyAllWindows()
            break

Tried it also with edge detection cv2.canny without luck.

The point is to click the button when the fish is in the smallest green field. The field appears in random parts of a slider.

Any ideas?

================

UPDATE

Tried color matching as Furas said

# import the necessary packages
from collections import deque
from imutils.video import VideoStream
import numpy as np
import argparse
import cv2
import imutils
import time
from mss.linux import MSS as mss
from PIL import Image
import mss
import numpy
import pyautogui
# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video",
    help="path to the (optional) video file")
ap.add_argument("-b", "--buffer", type=int, default=64,
    help="max buffer size")
args = vars(ap.parse_args())
# define the lower and upper boundaries of the "green"
# ball in the HSV color space, then initialize the
# list of tracked points
greenLower = (42, 84, 211)
greenUpper = (69, 130, 255)
blueLower = (88, 76, 255)
blueUpper = (151, 76, 255)
pts = deque(maxlen=args["buffer"])

# grab video from screen(monitor area)
with mss.mss() as sct:
    monitor = {"top": 325, "left": 4423, "width": 136, "height": 662}
    while "Screen capturing":
        #last_time = time.time()
        #vs = numpy.array(sct.grab(monitor))
        #print("fps: {}".format(1 / (time.time() - last_time)))
        vs = sct.grab(monitor)
        # grab the current frame
        #frame = vs
        frame = np.array(vs)
        # resize the frame, blur it, and convert it to the HSV
        # color space
        blurred = cv2.GaussianBlur(frame, (11, 11), 0)
        hsv = cv2.cvtColor(blurred, cv2.COLOR_BGR2HSV)
        # construct a mask for the color "green", then perform
        # a series of dilations and erosions to remove any small
        # blobs left in the mask
        mask = cv2.inRange(hsv, greenLower, greenUpper)
        mask = cv2.erode(mask, None, iterations=2)
        mask = cv2.dilate(mask, None, iterations=2)
        mask2 = cv2.inRange(hsv, blueLower, blueUpper)
        mask2 = cv2.erode(mask2, None, iterations=2)
        mask2 = cv2.dilate(mask2, None, iterations=2)
        # find contours in the mask and initialize the current
        # (x, y) center of the ball
        cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        cnts = imutils.grab_contours(cnts)
        center = None
        cnts2 = cv2.findContours(mask2.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        cnts2 = imutils.grab_contours(cnts2)
        center2 = None
        # only proceed if at least one contour was found
        if len(cnts) > 0:
            # find the largest contour in the mask, then use
            # it to compute the minimum enclosing rectangle and
            # centroid
            c = max(cnts, key=cv2.contourArea)
            (x, y, w, h) = cv2.boundingRect(c)
            M = cv2.moments(c)
            center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))
            c2 = max(cnts2, key=cv2.contourArea)
            (x2, y2, w2, h2) = cv2.boundingRect(c2)
            M2 = cv2.moments(c2)
            center2 = (int(M2["m10"] / M2["m00"]), int(M2["m01"] / M2["m00"]))
            # draw the rectangle and centroid on the frame,
            # then update the list of tracked points
            cv2.rectangle(frame, (int(x), int(y)), (int(x+w), int(y+h)),(0, 255, 255), 2)
            cv2.circle(frame, center, 5, (0, 0, 255), -1)
            cv2.rectangle(frame, (int(x2), int(y2)), (int(x2+w2), int(y2+h2)),(0, 255, 255), 2)
            cv2.circle(frame, center2, 5, (0, 0, 255), -1)
            # update the points queue
            pts.appendleft(center)
            if y-15 < y2 < y+15:
                pyautogui.click(4908, 984)
                time.sleep(2)
                y2 = 0           
        cv2.imshow("frame", frame)
        key = cv2.waitKey(1)
        if cv2.waitKey(25) & 0xFF == ord("q"):
            cv2.destroyAllWindows()
            break

But before the round or between rounds i get error

Traceback (most recent call last):
  File "C:\Users\Game\Desktop\Py\Fish.py", line 74, in <module>
    c2 = max(cnts2, key=cv2.contourArea)
ValueError: max() arg is an empty sequence

How can it be solved?

Going to change the two masks in one as Furas adviced

mask = cv2.bitwise_or(mask1, mask2)

But what can i use to find both max for green field and fish? till now it was 2 masks, 2 cnts and 2 max values.

With mss sct.grab i have not so great FPS (average 25fps) any other better capturing methods?

Thanks a lot!

Answer 1

Ok, after some workaround i got it working and tested, with a colour detection it works on the firs "day map". Not always get "perfect" hit, but at least "good", guess it is becouse of FPS procession, maybee if I find the way to reise FPS, than it would be better.

    # import the necessary packages
from collections import deque
from imutils.video import VideoStream
import numpy as np
import argparse
import cv2
import imutils
import time
from mss.linux import MSS as mss
from PIL import Image
import mss
import pyautogui
from win32 import win32gui
from pythonwin import win32ui
from win32.lib import win32con
from win32 import win32api

# define the lower and upper boundaries in the HSV color space, then initialize the
# list of tracked points
# Green "perfect" field
greenLower = (42, 79, 211)
greenUpper = (69, 130, 255)
# Blue fish
blueLower = (88, 76, 255)
blueUpper = (151, 76, 255)
# Purple field
blue2Lower = (114, 139, 218)
blue2Upper = (123, 165, 255)
# Gray field "Status" (after fish is caught)
grayLower = (0, 0, 114)
grayUpper = (0, 0, 132)
# Purple miss
purpleLower = (123, 148, 239)
purpleUpper = (125, 165, 243)
# Define Vars
y2 = 0
a = 0
b = 0
startTime = time.time()
startTime2 = time.time()
# grab video from screen(monitor area)
with mss.mss() as sct:
    #grab picture of slider and fish
    monitor = {"top": 846, "left": 4726, "width": 162, "height": 398}
    #grab picture of gray field "Status" when the fish is caught
    monitor2 = {"top": 1017, "left": 4366, "width": 11, "height": 23}
    #grab picture of purple pixels if fish is lost
    monitor3 = {"top": 1013, "left": 4484, "width": 5, "height": 6}
    while "Screen capturing":
        vs = sct.grab(monitor)
        vs2 = sct.grab(monitor2)
        vs3 = sct.grab(monitor3) 
        # grab the current frame
        frame = np.array(vs)
        frame2 = np.array(vs2)
        frame3 = np.array(vs3)
        # resize the frame, blur it, and convert it to the HSV
        # color space
        blurred = cv2.GaussianBlur(frame, (11, 11), 0)
        hsv = cv2.cvtColor(blurred, cv2.COLOR_BGR2HSV)
        blurred2 = cv2.GaussianBlur(frame2, (11, 11), 0)
        hsv2 = cv2.cvtColor(blurred2, cv2.COLOR_BGR2HSV)
        blurred3 = cv2.GaussianBlur(frame3, (11, 11), 0)
        hsv3 = cv2.cvtColor(blurred3, cv2.COLOR_BGR2HSV)
        # construct a mask for the color, then perform
        # a series of dilations and erosions to remove any small
        # blobs left in the mask
        # Mask for green 'perfect' field
        mask = cv2.inRange(hsv, greenLower, greenUpper)
        mask = cv2.erode(mask, None, iterations=2)
        mask = cv2.dilate(mask, None, iterations=2)
        # Mask for Fish
        mask2 = cv2.inRange(hsv, blueLower, blueUpper)
        mask2 = cv2.erode(mask2, None, iterations=2)
        mask2 = cv2.dilate(mask2, None, iterations=2)
        # Mask for purple Start slider
        mask3 = cv2.inRange(hsv, blue2Lower, blue2Upper)
        mask3 = cv2.erode(mask3, None, iterations=2)
        mask3 = cv2.dilate(mask3, None, iterations=2)
        # Mask for gray field "Status" when the fish is caught
        mask4 = cv2.inRange(hsv2, grayLower, grayUpper)
        mask4 = cv2.erode(mask4, None, iterations=2)
        mask4 = cv2.dilate(mask4, None, iterations=2)
        # Mask for purple fish miss
        mask5 = cv2.inRange(hsv3, purpleLower, purpleUpper)
        mask5 = cv2.erode(mask5, None, iterations=2)
        mask5 = cv2.dilate(mask5, None, iterations=2)
        # find contours in the mask and initialize the current
        # (x, y) center of the rectangle
        cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        cnts = imutils.grab_contours(cnts)
        cnts2 = cv2.findContours(mask2.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        cnts2 = imutils.grab_contours(cnts2)
        cnts3 = cv2.findContours(mask3.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        cnts3 = imutils.grab_contours(cnts3)
        cnts4 = cv2.findContours(mask4.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        cnts4 = imutils.grab_contours(cnts4)
        cnts5 = cv2.findContours(mask5.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        cnts5 = imutils.grab_contours(cnts5)
        # only proceed if at least one contour was found
        if len(cnts3) > 0:
            print ("start")
            startTime2 = time.time()
            time.sleep(0.1)
            pyautogui.click(4978, 1239)
            time.sleep(1)
            startTime2 = time.time()
        elif len(cnts) > 0 and len(cnts2) > 0:
            startTime2 = time.time()
            # find the largest contour in the mask, then use
            # it to compute the minimum enclosing rectangle and
            # centroid
            c = max(cnts, key=cv2.contourArea)
            M = cv2.moments(c)
            center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))
            (x, y) = center
            c2 = max(cnts2, key=cv2.contourArea)
            M2 = cv2.moments(c2)
            center2 = (int(M2["m10"] / M2["m00"]), int(M2["m01"] / M2["m00"]))
            (x2, y2) = center2
            if y-65 < y2 < y+65:
                print ("catch")
                pyautogui.click(4978, 1239)
                time.sleep(1)
                y2 = 0
                startTime2 = time.time()
        elif len(cnts4) > 0:
            time.sleep(1)
            a +=1
            endTime = time.time()
            timer = endTime-startTime
            hour = timer // 3600
            timer %= 3600
            minutes = timer // 60
            timer %= 60
            seconds = timer
            print (a, "fishes and", b, "misses in %d:%d:%d" % (hour, minutes, seconds))
            print ("start over")
            time.sleep(1)
            pyautogui.click(4741, 913)
            pyautogui.click(4741, 913)
            time.sleep(1)
            pyautogui.click(4978, 1239)
            pyautogui.click(4978, 1239)
            time.sleep(1)
            startTime2 = time.time()
        elif len(cnts5) > 0:
            b +=1
            print ("Miss")
            time.sleep(2)
            pyautogui.click(4978, 1239)
            startTime2 = time.time()
        else:
            endTime2 = time.time()
            if (endTime2 - startTime2 > 40):
                print("Longer than 40 seconds")
                startTime2 = time.time()
                print ("restart")
                pyautogui.click(4741, 913)
                time.sleep(1)
                pyautogui.click(4978, 1239)
                time.sleep(1) 
        key = cv2.waitKey(1)
        if cv2.waitKey(25) & 0xFF == ord("q"):
            cv2.destroyAllWindows()
            break