Initial Commit

##More Basic testing for fishing.py

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+##More Basic testing for fishing
+import pyautogui as pag
+from random import randint, uniform
+import cv2
+import numpy
+import math
+import time
+import sys 
+
+class FishBot(object):
+    def __init__(self):
+        pass
+
+    def random_coordinate(self, location):
+            #Moves cursor to random locaction still above the object to be clicked
+            x = randint(location[0], location[0]+location[2])
+            y = randint(location[1], location[1]+location[3])
+            time = self.travel_time(x, y)
+
+            return pag.moveTo(x, y, time)
+
+    
+    def fishLoop(self):
+        #check if inventory is full
+        pag.screenshot('Images/shrimp.png', region=(1575, 1689, 305, 411))
+        screen = cv2.imread('Images/shrimp.png')
+        template = cv2.imread('Images/fullinv.png')
+        res = cv2.matchTemplate(screen, template, cv2.TM_CCOEFF_NORMED)
+        threshold = .80
+        loc = numpy.where(res >= threshold)
+        if len(loc[0]) > 0:
+            invResult = True
+    
+        else:
+            invResult = False
+            #Move to Random Coordinate where shrimps are 
+            ##need to add some variance, misses clicks, doesn't move in a
+            ###straight line too fast
+            #Shrimp location
+            location1 = (580, 1954, 60, 60)
+
+            #Now add a little variance to the x and y coordinates
+            ##The location is in a tuple, these are immutable so it must be converted into a list to be changed
+            ###Then converted back
+            locationList = list(location1)
+            modifiedx = randint(0,35)
+            modifiedy = randint(0,35)
+            locationList[0] = locationList[0] + modifiedx
+            print (locationList)
+            locationList[1] = locationList[1] + modifiedy
+            modifiedLocation = tuple(locationList)
+            pag.moveTo(modifiedLocation, 2)
+            pag.click()
+            self.random_wait(0.05, 0.1)

#Image Recognition Testing.py

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+import cv2
+import numpy as np
+import pyautogui as pag
+
+##Inventory Count
+
+# Take a screenshot and store it in a numpy array
+screenshot = np.array(pag.screenshot(region = (0, 1079, 1920, 1080)))
+
+screenshot = cv2.cvtColor(screenshot, cv2.COLOR_BGR2GRAY)
+
+# Load the image to be searched for in grayscale
+image_to_search = cv2.imread('Images/shrimp.png', 0)
+
+# Get the dimensions of the image to be searched for
+h, w = image_to_search.shape[::-1]
+
+# Use cv2.matchTemplate() to find the template image within the screenshot
+result = cv2.matchTemplate(screenshot, image_to_search, cv2.TM_CCOEFF_NORMED)
+
+# Set a threshold value to count only those template images that have a high enough correlation
+threshold = 0.9
+counter = 0
+
+loc = np.where(result >= threshold)
+for pt in zip(*loc[::-1]):
+    cv2.rectangle(screenshot, pt, (pt[0] + w, pt[1] + h), (0, 0, 255), 2)
+    counter += 1
+    
+print(counter)
+
+if counter == 27:
+    print('Inventory full, time to drop')
+else:
+    print('Inventory not full, keep fishing')

Testing file.py

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+##Testing file
+import pyautogui as pag
+from random import randint, uniform
+import cv2
+import numpy
+import math
+import time
+import sys 
+
+#Build a list of acceptable x and y locations and pass them to the moveto function
+##how to do this without having to pass a sequence, because for some reason the library does not like them
+
+location1x = 580
+location1y = 1954
+
+#Now add a little variance to the x and y coordinates
+modifiedx = randint(0,35) + location1x
+modifiedy = randint(0,35) + location1y
+
+#Also add the chance to misclick
+misclick = randint(0,10)
+
+#20% Chance to misclick
+if misclick <= 2:
+    location1x = location1x + 50
+    location1y = location1y + 50
+    print('Misclick calculated')
+else:
+    print('Clicking Normally')
+
+pag.moveTo(location1x, location1y, 0.70)
+pag.click()

fishing.py

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+import pyautogui as pag
+from random import randint, uniform
+import cv2
+import numpy as np
+import math
+import time
+import sys 
+
+#For Fishing
+##https://zaxrosenberg.com/how-to-write-a-runescape-autoclicker-with-python-part-ii/
+
+def inventoryCount():
+
+    ##Inventory Count
+
+    # Take a screenshot and store it in a numpy array
+    screenshot = np.array(pag.screenshot(region = (0, 1079, 1920, 1080)))
+
+    screenshot = cv2.cvtColor(screenshot, cv2.COLOR_BGR2GRAY)
+
+    # Load the image to be searched for in grayscale
+    image_to_search = cv2.imread('Images/shrimp.png', 0)
+
+    # Get the dimensions of the image to be searched for
+    h, w = image_to_search.shape[::-1]
+
+    # Use cv2.matchTemplate() to find the template image within the screenshot
+    result = cv2.matchTemplate(screenshot, image_to_search, cv2.TM_CCOEFF_NORMED)
+
+    # Set a threshold value to count only those template images that have a high enough correlation
+    threshold = 0.9
+    counter = 0
+
+    loc = np.where(result >= threshold)
+    for pt in zip(*loc[::-1]):
+        cv2.rectangle(screenshot, pt, (pt[0] + w, pt[1] + h), (0, 0, 255), 2)
+        counter += 1
+        
+    print(counter)
+
+    if counter == 27:
+        print('Inventory full, time to drop')
+    else:
+        print('Inventory not full, keep fishing')
+
+#Function to check if we are currently fishing
+def checkIfFishing():
+    # Take a screenshot and store it in a numpy array
+    screenshot = np.array(pag.screenshot(region = (0, 1079, 1920, 1080)))
+
+    screenshot = cv2.cvtColor(screenshot, cv2.COLOR_BGR2GRAY)
+
+    # Load the image to be searched for in grayscale
+    image_to_search = cv2.imread('Images/fishing.png', 0)
+
+    # Get the dimensions of the image to be searched for
+    h, w = image_to_search.shape[::-1]
+
+    # Use cv2.matchTemplate() to find the template image within the screenshot
+    #This checks if the green Fishing icon is being displayed in the top left
+    result = cv2.matchTemplate(screenshot, image_to_search, cv2.TM_CCOEFF_NORMED)
+
+    # Set a threshold value to count only those template images that have a high enough correlation
+    threshold = 0.8
+    #Assume we are not fishing until proven otherwise
+    Fishing = False
+
+
+    loc = np.where(result >= threshold)
+    for pt in zip(*loc[::-1]):
+        cv2.rectangle(screenshot, pt, (pt[0] + w, pt[1] + h), (0, 0, 255), 2)
+        Fishing = True
+        
+    print(Fishing)
+
+    if Fishing:
+        print('Currently Fishing')
+    else:
+        print('Not Fishing')
+
+#Function for finding the fishing spots
+def fishingSpots():
+    print('Searching for fishing spot')

main.py

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+import pyautogui
+import random
+
+###Try locating depending on color instead, doing specific images doesn't seem to work.
+
+
+
+

mouseLocation.py

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+#! python3
+
+#This displays the location of the mouse in a loop
+import pyautogui, sys
+print('Press Ctrl-C to quit.')
+try:
+    while True:
+        x, y = pyautogui.position()
+        positionStr = 'X: ' + str(x).rjust(4) + ' Y: ' + str(y).rjust(4)
+        print(positionStr, end='')
+        print('\b' * len(positionStr), end='', flush=True)
+except KeyboardInterrupt:
+    print('\n')