# Python筆記

from pynput.keyboard import Key
from pynput.keyboard import Listener
import time

class Pair:
    def __init__(self, key, time_stamp, type):
        self.key = key
        self.time_stamp = time_stamp
        self.type = type

his_list = []

def on_press(key):
    his_list.append(Pair(key=key, time_stamp=time.time(), type=0))
    # print('{0} pressed'.format(key))

def on_release(key):
    his_list.append(Pair(key=key, time_stamp=time.time(), type=1))
    # print('{0} release'.format(key))
    if key == Key.esc:
        # Stop listener
        return False

# Collect events until released
with Listener(
        on_press=on_press,
        on_release=on_release) as listener:
    listener.join()

his_dict = dict()
log_list = []

for item in his_list:
    print(vars(item))

    if item.type == 0:
        if not(item.key in his_dict):
            his_dict[item.key] = 1
            log_list.append(item)
    else:
        if not(item.key in his_dict):
            print(f"{item.key} not found")
        else:
            his_dict.pop(item.key)
            log_list.append(item)

print("===================")

for item in log_list:
    print(vars(item))

import cv2
import matplotlib.pyplot as plt
import numpy as np

def calculateDHash(img):
    flatten = np.reshape(img, (-1))
    dhash = np.zeros((flatten.shape[0]-1))

    for i in range(flatten.shape[0]-1):
        if flatten[i+1] >= flatten[i]:
            dhash[i] = 1
    
    return dhash

def calculateHamingDistance(d1, d2):
    return (d1.shape[0] - np.logical_xor(d1, d2).sum())/d1.shape[0]

img1 = cv2.imread("test.png", cv2.IMREAD_GRAYSCALE)
img2 = cv2.imread("test1.png", cv2.IMREAD_GRAYSCALE)

d1 = calculateDHash(img1)
d2 = calculateDHash(img2)

hd = calculateHamingDistance(d1, d2)

print(hd)

# cv2.imshow("123", img)
# cv2.waitKey(0)
# cv2.destroyAllWindows()

import mss
import cv2
import numpy as np
import matplotlib.pyplot as plt

with mss.mss() as sct:
    
    # Get information of monitor 2
    monitor_number = 1
    mon = sct.monitors[monitor_number]

    print(mon)

    # The screen part to capture
    monitor = {
        "top": mon["top"],
        "left": mon["left"],
        "width": mon["width"],
        "height": mon["height"],
        "mon": monitor_number,
    }
    # output = "sct-mon{mon}_{top}x{left}_{width}x{height}.png".format(**monitor)

    # Grab the data
    img = np.array(sct.grab(monitor))    
    plt.imshow(img)

import cv2
import matplotlib.pyplot as plt
import numpy as np
import mss
import time

def calculateDHash(img):
    flatten = np.reshape(img, (-1))
    dhash = np.zeros((flatten.shape[0]-1))

    for i in range(flatten.shape[0]-1):
        if flatten[i+1] >= flatten[i]:
            dhash[i] = 1
    
    return dhash

def calculateHamingDistance(d1, d2):
    return (d1.shape[0] - np.logical_xor(d1, d2).sum())/d1.shape[0]

def getScreenShot():
    with mss.mss() as sct:
    
        # Get information of monitor 2
        monitor_number = 2
        mon = sct.monitors[monitor_number]
        
        # The screen part to capture
        monitor = {
            "top": mon["top"],
            "left": mon["left"],
            "width": mon["width"],
            "height": mon["height"],
            "mon": monitor_number,
        }
        # output = "sct-mon{mon}_{top}x{left}_{width}x{height}.png".format(**monitor)

        # Grab the data
        return cv2.cvtColor(np.array(sct.grab(monitor)), cv2.COLOR_BGR2GRAY)

# img1 = cv2.imread("test.png", cv2.IMREAD_GRAYSCALE)
# img2 = cv2.imread("test1.png", cv2.IMREAD_GRAYSCALE)

for i in range(10):
    ts1 = time.time()

    img1 = getScreenShot()[800:, 1600:]
    img2 = getScreenShot()[800:, 1600:]

    d1 = calculateDHash(img1)
    d2 = calculateDHash(img2)

    hd = calculateHamingDistance(d1, d2)

    ts2 = time.time()

    print(ts2-ts1)

    time.sleep(3)
    
# cv2.imshow("123", img)
# cv2.waitKey(0)
# cv2.destroyAllWindows()