311 lines
9.4 KiB
Python
311 lines
9.4 KiB
Python
from __future__ import division
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import os, cv2, sys, ctypes, sqlite3
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import numpy as np
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import pyautogui as pag
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import pytesseract as pt
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from tkinter import *
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from PIL import Image
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from tkinter.filedialog import askopenfilename
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cascade = cv2.CascadeClassifier('cascades/data/haarcascade_frontalface_alt2.xml')
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recognizer = cv2.face.LBPHFaceRecognizer_create()
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BASE_DIR = os.path.dirname(os.path.abspath(__file__))
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with sqlite3.connect("database.db") as db:
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cursor = db.cursor()
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cursor.execute('''
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CREATE TABLE IF NOT EXISTS users(
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user_id INTEGER PRIMARY KEY AUTOINCREMENT,
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username VARCHAR(35) NOT NULL UNIQUE,
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password VARCHAR(35) NOT NULL
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);
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''')
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cursor.execute('SELECT * FROM users;')
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print("Na start:",cursor.fetchall())
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def start_window():
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global window
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window = Tk()
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window.geometry('300x200')
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window.title('Login')
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Label(text = 'Login', font = ('Calibri', 12)).pack()
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Button(text = 'Login', command = login).pack()
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Button(text='Register', command = register).pack()
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window.mainloop()
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def register():
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global reg_window
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reg_window = Toplevel(window)
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reg_window.title('Register')
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reg_window.geometry('300x200')
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global reg_username
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global reg_password
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reg_username = StringVar()
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reg_password = StringVar()
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Label(reg_window, text='Username:', font=('Calibri', 12)).pack()
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Entry(reg_window, textvariable = reg_username).pack()
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Label(reg_window, text='Password:', font=('Calibri', 12)).pack()
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Entry(reg_window, textvariable = reg_password, show='*').pack()
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Button(reg_window, text='Register', command = reg_conf).pack()
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def reg_conf():
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new_username = reg_username.get()
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new_password = reg_password.get()
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cursor.execute('SELECT * FROM users WHERE username like "'''+new_username+'''";''')
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user_test = cursor.fetchone()
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if len(new_username) >= 3 and len(new_password) >= 3:
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if user_test == None:
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reg_cam()
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cursor.execute('''
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INSERT INTO users(username, password)
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VALUES ("''' + new_username + '''", "''' + new_password + '''");
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''')
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ctypes.windll.user32.MessageBoxW(0, "Successfully registered!", "Success!", 0)
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reg_window.destroy()
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else:
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ctypes.windll.user32.MessageBoxW(0, "User exists!", "Error", 0)
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else:
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ctypes.windll.user32.MessageBoxW(0, "Username or password should be longer! (at least 3 characters)", "Error", 0)
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db.commit()
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def login():
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global cam_ver
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global log_window
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log_window = Toplevel(window)
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log_window.title('Login')
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log_window.geometry('300x200')
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global log_username
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global log_password
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log_username = StringVar()
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log_password = StringVar()
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Label(log_window, text='Username:', font=('Calibri', 12)).pack()
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Entry(log_window, textvariable=log_username).pack()
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Label(log_window, text='Password:', font=('Calibri', 12)).pack()
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Entry(log_window, textvariable=log_password, show='*').pack()
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Button(log_window, text='Login', command=log_conf).pack()
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def log_conf():
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global cam_ver
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cam_ver = False
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username = log_username.get()
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password = log_password.get()
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cursor.execute('SELECT * FROM users WHERE username like "'''+username+'''" AND password like "'''+password+'''";''')
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user_test = cursor.fetchone()
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print(user_test)
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if user_test != None:
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log_cam()
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if cam_ver == True:
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log_window.destroy()
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window.destroy()
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main_window()
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else:
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ctypes.windll.user32.MessageBoxW(0, "Incorrect login or password!", "Error", 0)
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db.commit()
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def main_window():
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window = Tk()
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window.geometry('300x200')
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window.title('Main')
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Button(text='Cursor control', command=cursor_control).pack()
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Button(text='OCR', command=ocr).pack()
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def reg_cam():
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capture = cv2.VideoCapture(0)
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i=0
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os.mkdir('images/' + reg_username.get(), 777)
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while (True):
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ret, frame = capture.read()
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frameGray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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faces = cascade.detectMultiScale(frameGray, scaleFactor=1.5, minNeighbors=5)
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for (x, y, w,h) in faces:
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cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
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roi_gray = frameGray[y:y + h, x:x + w]
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image = 'images/'+reg_username.get()+'/image'+str(i)+'.png'
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cv2.imwrite(image, roi_gray)
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i=i+1
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cv2.imshow('Move your head sideways, up and down (no more than 30 degrees)', frame)
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if cv2.waitKey(27) & 0xFF == ord('\x1b'):
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print("stop")
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if i == 100:
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break
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capture.release()
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cv2.destroyAllWindows()
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current_id = 0
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name_ids = {}
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y_names = []
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x_train = []
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for root, dirs, files in os.walk(os.path.join(BASE_DIR, 'images/'+reg_username.get()+'/')):
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for file in files:
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if file.endswith('png'):
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path = os.path.join(root, file)
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name = os.path.basename(root)
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print(name, path)
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if name in name_ids:
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pass
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else:
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name_ids[name] = current_id
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current_id += 1
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id_ = name_ids[name]
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print(name_ids)
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pil_image = Image.open(path)
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image_array = np.array(pil_image, 'uint8')
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faces = cascade.detectMultiScale(image_array, minNeighbors=5)
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for (x, y, w, h) in faces:
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roi = image_array[y:y + h, x:x + w]
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x_train.append(roi)
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y_names.append(id_)
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recognizer.train(x_train, np.array(y_names))
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recognizer.save('train/'+reg_username.get()+'.yml')
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def log_cam():
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capture = cv2.VideoCapture(0)
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global cam_ver
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recognizer.read('train/'+log_username.get()+'.yml')
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i = 0
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while (True):
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ret, frame = capture.read()
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frameGray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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faces = cascade.detectMultiScale(frameGray, scaleFactor=1.5, minNeighbors=5)
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for (x, y, w, h) in faces:
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cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
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cv2.rectangle(frameGray, (x, y), (x + w, y + h), (0, 255, 0), 2)
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roi_gray = frameGray[y:y + h, x:x + w]
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id_, conf = recognizer.predict(roi_gray)
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if conf >= 50:
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i += 1
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cv2.imshow('Login', frame)
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if cv2.waitKey(27) & 0xFF == ord('\x1b'):
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print("stop")
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if i >= 3:
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cam_ver = True
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print(cam_ver)
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break
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capture.release()
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cv2.destroyAllWindows()
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def cursor_control():
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capture = cv2.VideoCapture(0)
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pag.FAILSAFE = FALSE
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old_cx, old_cy = pag.position()
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while (True):
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ret, frame = capture.read()
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frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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image_blur = cv2.GaussianBlur(frame, (7, 7), 0)
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image_blur_hsv = cv2.cvtColor(image_blur, cv2.COLOR_RGB2HSV)
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min_red = np.array([0,100,80])
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max_red = np.array([10,256,256])
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mask1 = cv2.inRange(image_blur_hsv, min_red, max_red)
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min_red2 = np.array([170,100,80])
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max_red2 = np.array([180, 256, 256])
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mask2 = cv2.inRange(image_blur_hsv, min_red2, max_red2)
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mask = mask1 + mask2
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min_blue = np.array([110, 50, 50])
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max_blue = np.array([130, 255, 255])
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click_mask = cv2.inRange(image_blur_hsv, min_blue, max_blue)
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contour = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (15, 15))
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mask_closed = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, contour)
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mask_clean = cv2.morphologyEx(mask_closed, cv2.MORPH_OPEN, contour)
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contours, hierarchy = cv2.findContours(mask_clean, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
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contour_blue = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (15, 15))
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blue_closed = cv2.morphologyEx(click_mask, cv2.MORPH_CLOSE, contour_blue)
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blue_clean = cv2.morphologyEx(blue_closed, cv2.MORPH_OPEN, contour_blue)
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click_contours, click_hierarchy = cv2.findContours(blue_clean, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
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contour_sizes = [(cv2.contourArea(contour), contour) for contour in contours]
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if contour_sizes != []:
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marker = max(contour_sizes, key=lambda x: x[0])[1]
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M = cv2.moments(marker)
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cx = int(M['m10'] / M['m00'])
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cy = int(M['m01'] / M['m00'])
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pag.move((cx-old_cx)*5, (cy-old_cy)*5, duration=0.5)
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old_cx = cx
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old_cy = cy
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click_contour_sizes = [(cv2.contourArea(click_contour), click_contour) for click_contour in click_contours]
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if click_contour_sizes != []:
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pag.click()
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if pag.position() == (0,0):
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break
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capture.release()
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cv2.destroyAllWindows()
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def ocr():
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Tk().withdraw()
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filename = askopenfilename(filetypes=[("PNG files", "*.png")])
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pt.pytesseract.tesseract_cmd = r'C:\Users\Kuba\AppData\Local\Tesseract-OCR\tesseract.exe'
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image = cv2.imread(filename)
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image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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kernel = np.ones((1, 1), np.uint8)
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image = cv2.dilate(image, kernel)
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image = cv2.erode(image, kernel)
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image = cv2.adaptiveThreshold(image, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 65, 105)
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text = pt.image_to_string(image)
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file = open(filename+'.txt', 'w+')
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file.write(text)
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file.close()
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print(text)
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print(filename)
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start_window() |