开云-OpenCV手势识别方案

2024-12-15

[导读]本文将介绍基在米尔电子MYD-LT527开辟板（米尔基在全志 T527开辟板）的OpenCV手势辨认方案测试。本文将介绍基在米尔电子MYD-LT527开辟板（米尔基在全志T527开辟板）的OpenCV手势辨认方案测试。米尔基在全志T527开辟板 1、软件情况安装 1.安装OpenCV sudo apt-get install libopencv-dev python3-opencv 2.安装pip sudo apt-get install python3-pip OpenCV手势辨认步调 1.图象获得：从摄像头或其他图象源获得手部图象。利用OpenCV的VideoCapture类可以捕捉视频流，或利用imread函数加载图象。 2.图象预处置：对图象进行预处置，以提高特点提取的正确性。经常使用的预处置操作包罗灰度化、滤波、边沿检测、二值化、噪声去除和形态学处置等。灰度化：将彩色图象转换为灰度图象，去除色彩信息，简化图象。滤波：利用滤波器去除图象中的噪声。边沿检测：利用边沿检测算法提取图象中的边沿信息。二值化：将灰度图象转换为二值图象，将像素值分为黑色和白色。形态学处置：利用形态学操作加强手势轮廓。 3.特点提取：从预处置后的图象中提取手部特点。经常使用的特点包罗外形特点、纹理特点和活动轨迹特点等。外形特点：提取手部轮廓、面积、周长、质心等外形特点。纹理特点：提取手部皮肤纹理、皱纹等纹理特点。活动轨迹特点：提取手部活动轨迹、速度、加快度等活动轨迹特点。 4.分类和辨认：利用机械进修算法对提取的特点进行分类，以辨认特定的手势。代码实现 # -*- coding: utf-8 -*- import cv2 def reg(x): o1 = cv2.imread('paper.jpg',1) o2 = cv2.imread('rock.jpg',1) o3 = cv2.imread('scissors.jpg',1) gray1 = cv2.cvtColor(o1,cv2.COLOR_BGR2GRAY) gray2 = cv2.cvtColor(o2,cv2.COLOR_BGR2GRAY) gray3 = cv2.cvtColor(o3,cv2.COLOR_BGR2GRAY) xgray = cv2.cvtColor(x,cv2.COLOR_BGR2GRAY) ret, binary1 = cv2.threshold(gray1,127,255,cv2.THRESH_BINARY) ret, binary2 = cv2.threshold(gray2,127,255,cv2.THRESH_BINARY) ret, binary3 = cv2.threshold(gray3,127,255,cv2.THRESH_BINARY) xret, xbinary = cv2.threshold(xgray,127,255,cv2.THRESH_BINARY) contours1, hierarchy = cv2.findContours(binary1, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) contours2, hierarchy = cv2.findContours(binary2, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) contours3, hierarchy = cv2.findContours(binary3, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) xcontours, hierarchy = cv2.findContours(xbinary, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) cnt1 = contours1[0] cnt2 = contours2[0] cnt3 = contours3[0] x = xcontours[0] ret=[] ret.append(cv2.matchShapes(x,cnt1,1,0.0)) ret.append(cv2.matchShapes(x,cnt2,1,0.0)) ret.append(cv2.matchShapes(x,cnt3,1,0.0)) max_index = ret.index(min(ret)) #计较最年夜值索引 if max_index==0: r="paper" elif max_index==1: r="rock" else: r="sessiors" return r t1=cv2.imread('test1.jpg',1) t2=cv2.imread('test2.jpg',1) t3=cv2.imread('test3.jpg',1) # print(reg(t1)) # print(reg(t2)) # print(reg(t3)) # ===========显示处置成果================== org=(0,60) font = cv2.FONT_HERSHEY_SIMPLEX fontScale=2 color=(255,255,255) thickness=3 cv2.putText(t1,reg(t1),org,font,fontScale,color,thickness) cv2.putText(t2,reg(t2),org,font,fontScale,color,thickness) cv2.putText(t3,reg(t3),org,font,fontScale,color,thickness) cv2.imshow('test1',t1) cv2.imshow('test2',t2) cv2.imshow('test3',t3) cv2.waitKey() cv2.destroyAllWindows() 1.法式运行 2、原始图象包括练习图象辨认成果辨认到了铰剪石头布原始图片