OpenCV SURF,用于从Python中的网络摄像头进行实时流式传输



我正在使用python在opencv中进行冲浪实现,这将检测给定图像中的模板。我已经修改了代码,以便它将从连接的网络摄像头捕获视频并将其转换为图像,然后在其上应用冲浪。以下是修改后的代码。

import cv2
import numpy as np

cap = cv2.VideoCapture(0)
while(True):
        ret ,img = cap.read()
# Convert them to grayscale
        imgg =cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
# SURF extraction
    surf = cv2.SURF()
    kp, descritors = surf.detect(imgg,None,useProvidedKeypoints = False)
# Setting up samples and responses for kNN
    samples = np.array(descritors) 
    responses = np.arange(len(kp),dtype = np.float32)
# kNN training
    knn = cv2.KNearest()
    knn.train(samples,responses)
# Now loading a template image and searching for similar keypoints
    template = cv2.imread('template.png')
    templateg= cv2.cvtColor(template,cv2.COLOR_BGR2GRAY)
    keys,desc = surf.detect(templateg,None,useProvidedKeypoints = False)
    for h,des in enumerate(desc):
            des = np.array(des,np.float32).reshape((1,128))
            retval, results, neigh_resp, dists = knn.find_nearest(des,1)
            res,dist =  int(results[0][0]),dists[0][0]
            if dist<0.1: # draw matched keypoints in red color
                color = (0,0,255)
            else:  # draw unmatched in blue color
                print dist
                color = (255,0,0)
    #Draw matched key points on original image
            x,y = kp[res].pt
            center = (int(x),int(y))
            cv2.circle(img,center,2,color,-1)
    #Draw matched key points on template image
            x,y = keys[h].pt
            center = (int(x),int(y))
            cv2.circle(template,center,2,color,-1)
    cv2.imwrite('img',img)
    cv2.imwrite('tm',template)
    cv2.waitKey(0)
cap.release()

但是即将到来的错误是 knn.train(样本,响应) 类型错误:不支持数据类型 = 17

有人对此有任何想法吗?

CV 可能需要常规数组,但您正在传递 numpy 数组。试试这个

knn.train(samples.tolist(),responses.tolist())

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