运行效果
基于Mediapipe的手势识别,完成的手势识别游戏。运行效果图如下:
首先是初始的界面效果图:


游戏规则:屏幕上会出现蚊子和蜜蜂,当手蜷曲握起时,表示抓的动作。如果抓到右边移动的蚊子,则会增加分数,如果抓到右边的蜜蜂,则会出现被蛰到的声音 :)
代码介绍
调用Mediapipe,定义与手势识别有关的类:
这里完成了对图片镜像的翻转,在图上画出手势线条,并对手势的握起状态逻辑进行判断。
import cv2
import mediapipe as mp
from settings import *
import numpy as np
mp_drawing = mp.solutions.drawing_utils
mp_drawing_styles = mp.solutions.drawing_styles
mp_hands = mp.solutions.hands
class HandTracking:
def __init__(self):
self.hand_tracking = mp_hands.Hands(min_detection_confidence=0.5, min_tracking_confidence=0.5)
self.hand_x = 0
self.hand_y = 0
self.results = None
self.hand_closed = False
def scan_hands(self, image):
rows, cols, _ = image.shape
# Flip the image horizontally for a later selfie-view display, and convert
# the BGR image to RGB.
image = cv2.cvtColor(cv2.flip(image, 1), cv2.COLOR_BGR2RGB)
# To improve performance, optionally mark the image as not writeable to
# pass by reference.
image.flags.writeable = False
self.results = self.hand_tracking.process(image)
# Draw the hand annotations on the image.
image.flags.writeable = True
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
self.hand_closed = False
print(self.results.multi_hand_landmarks)
if self.results.multi_hand_landmarks:
for hand_landmarks in self.results.multi_hand_landmarks:
x, y = hand_landmarks.landmark[9].x, hand_landmarks.landmark[9].y
self.hand_x = int(x * SCREEN_WIDTH)
self.hand_y = int(y * SCREEN_HEIGHT)
x1, y1 = hand_landmarks.landmark[12].x, hand_landmarks.landmark[12].y
if y1 > y:
self.hand_closed = True
mp_drawing.draw_landmarks(

本文介绍了一个使用Mediapipe库进行手势识别的游戏应用。游戏中,玩家需通过握拳手势来捕捉屏幕上的蚊子得分,同时避免蜜蜂。代码包括手势检测、图像处理和游戏逻辑,涉及Python、OpenCV和Pygame等技术。
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