Demo effect
Third-party libraries that need to be installed:
pip install pygame # Load music
pip install pillow # Load pictures
pip install mediapipe # Model to determine gestures
pip install opencv # The model is used to process graphics
It is recommended that those with independent graphics and cameras try it!
I’m thinking of upgrading my gameplay. Only by knocking hard can you really accumulate merit! So I found a model that can judge gestures.
Source code (press Q to exit after turning on the camera)
import time
importtkinter
from tkinter import messagebox
import threading
import pygame # pip install pygame
from PIL import Image, ImageTk # pip install pillow
class window(tkinter.Tk):
def __init__(self):
super().__init__()
#Initialize merit
self.gongde=0
# Prepare audio
self.pygame=pygame
self.pygame.mixer.init()
self.pygame.mixer.music.load('knock.mp3')
# Prepare images
self.qiaomuyutupian=ImageTk.PhotoImage(file='KOMUYUTUPIAN.jpg') # Convert to a picture that can be used by tkinter
self.qiaomuyutupian2=ImageTk.PhotoImage(file='KOMUYUTUPIAN2.jpg') # Convert to a picture that can be used by tkinter
# Start interface
self.base_top()
def base_top(self):
self.title('Knocking on wooden fish adds merit')
self.geometry('410x400')
self.configure(bg='black')
# Label
self.label1=tkinter.Label(self,text='Accumulate merit:' + str(self.gongde),font=('华文新伟',15),fg='white',bg ='black',width=18)
self.label1.place(x=100,y=70)
# button
self.button1=tkinter.Button(self,image=self.qiaomuyutupian,relief='ridge',command=self.qiaomuyu)
self.button1.place(x=100,y=100)
# button
self.button2=tkinter.Button(self,text='interaction',width=10,command=self.thread_hudong)
self.button2.place(x=160,y=315)
# information
self.text1=tkinter.Text(self,width=10,height=5,bg='black',bd=0,foreground='white')
self.text1.place(x=125,y=115)
def showplus(self):
# text float
for i in range(4):
self.text1.insert('insert',' \\
')
else:
self.text1.insert('insert',' merit + 1')
for i in range(5):
time.sleep(0.04)
self.text1.delete(1.0, 2.0)
# Merit + 1
self.gongde=self.gongde + 1
self.label1.config(text='Accumulate merit:' + str(self.gongde))
def changetupian(self):
self.button1.config(image=self.qiaomuyutupian2)
time.sleep(0.1)
self.button1.config(image=self.qiaomuyutupian)
def qiaomuyu(self):
# Multi-thread startup solves the delay. Although the delay is small enough, in order to be more effective
th=threading.Thread(target=self.pygame.mixer.music.play)
th.start()
th2=threading.Thread(target=self.showplus)
th2.start()
th3=threading.Thread(target=self.changetupian)
th3.start()
def thread_hudong(self):
th4=threading.Thread(target=self.hudong)
th4.start()
self.frame=tkinter.Frame(self,width=200,height=40,bg='white')
self.frame.place(x=103,y=350)
self.label2=tkinter.Label(self.frame,text='In the camera, please wait...',bg='white')
self.label2.place(x=33,y=10)
def hudong(self):
import cv2
import mediapipe as mp
mp_hands = mp.solutions.hands
hands = mp_hands.Hands()
mp_drawing = mp.solutions.drawing_utils
# coding:utf-8`
cap = cv2.VideoCapture(0) # Turn on the camera
mark_one=0
while True:
self.frame.destroy()
ret, frame = cap.read() # Read video frame
if not ret:
break
image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) # Convert color space
results = hands.process(image) # Gesture recognition
# Process recognition results
if results.multi_hand_landmarks:
for hand_landmarks in results.multi_hand_landmarks:
mp_drawing.draw_landmarks(
frame,
hand_landmarks,
mp_hands.HAND_CONNECTIONS) # Used to specify how landmarks are connected in the graph.
for point in hand_landmarks.landmark:
x = int(point.x * frame.shape[1])
y = int(point.y * frame.shape[0])
if y < 200:
mark_one=1
if y > 400:
if 1 - mark_one == 0:
self.qiaomuyu()
mark_one=0
cv2.circle(frame, (x, y), 5, (0, 255, 0), -1) # Draw key points
cv2.imshow('Gesture Recognition', frame) # Display results
if cv2.waitKey(1) & amp; 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
if __name__ == '__main__':
top=window()
top.mainloop()
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