Python如何利用opencv實現手勢識別

cap = cv2.VideoCapture("C:/Users/lenovo/Videos/1.mp4")#讀取檔案
#cap = cv2.VideoCapture(0)#讀取攝像頭
while(True):
    ret, frame = cap.read()    key = cv2.waitKey(50) & 0xFF
    if key == ord('q'):
      break
cap.release()
cv2.destroyAllWindows()

def A(img):
    YCrCb = cv2.cvtColor(img, cv2.COLOR_BGR2YCR_CB) #轉換至YCrCb空間
    (y,cr,cb) = cv2.split(YCrCb) #拆分出Y,Cr,Cb值
    cr1 = cv2.GaussianBlur(cr, (5,5), 0)
    _, skin = cv2.threshold(cr1, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU) #Ostu處理
    res = cv2.bitwise_and(img,img, mask = skin)
    return res

def B(img):
    #binaryimg = cv2.Canny(Laplacian, 50, 200) #二值化，canny檢測
    h = cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE) #尋找輪廓
    contour = h[0]
    contour = sorted(contour, key = cv2.contourArea, reverse=True)#已輪廓區域面積進行排序
    #contourmax = contour[0][:, 0, :]#保留區域面積最大的輪廓點座標
    bg = np.ones(dst.shape, np.uint8) *255#建立白色幕布
    ret = cv2.dra
wContours(bg,contour[0],-1,(0,0,0),3) #繪製黑色輪廓
    return ret

""" 從視訊讀取幀儲存為圖片"""
import cv2
import numpy as np
cap = cv2.VideoCapture("C:/Users/lenovo/Videos/1.mp4")#讀取檔案
#cap = cv2.VideoCapture(0)#讀取攝像頭
#面板檢測
def A(img):

    YCrCb = cv2.cvtColor(img, cv2.COLOR_BGR2YCR_CB) #轉換至YCrCb空間
    (y,cr,cb) = cv2.split(YCrCb) #拆分出Y,Cr,Cb值
    cr1 = cv2.GaussianBlur(cr, (5,5), 0)
    _, skin = cv2.threshold(cr1, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU) #Ostu處理
    res = cv2.bitwise_and(img,img, mask = skin)
    return res
def B(img):
    #binaryimg = cv2.Canny(Laplacian, 50, 200) #二值化，canny檢測
    h = cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE) #尋找輪廓
    contour = h[0]
    contour = sorted(contour, key = cv2.contourArea, reverse=True)#已輪廓區域面積進行排序
    #contourmax = contour[0][:, 0, :]#保留區域面積最大的輪廓點座標
    bg = np.ones(dst.shape, np.uint8) *255#建立白色幕布
    ret = cv2.drawContours(bg,contour[0],-1,(0,0,0),3) #繪製黑色輪廓
    return ret
while(True):
    ret, frame = cap.read()
    #下面三行可以根據自己的電腦進行調節
    src = cv2.resize(frame,(400,350), interpolation=cv2.INTER_CUBIC)#視窗大小
    cv2.rectangle(src, (90, 60), (300, 300 ), (0, 255, 0))#框出擷取位置
    roi = src[60:300 , 90:300]  # 獲取手勢框圖

    res = A(roi)  # 進行膚色檢測
    cv2.imshow("0",roi)
    gray = cv2.cvtColor(res, cv2.COLOR_BGR2GRAY)
    dst = cv2.Laplacian(gray, cv2.CV_16S, ksize = 3)
    Laplacian = cv2.convertScaleAbs(dst)
    contour = B(Laplacian)#輪廓處理
    cv2.imshow("2",contour)

    key = cv2.waitKey(50) & 0xFF
    if key == ord('q'):
            break
cap.release()
cv2.destroyAllWindows()