Python OpenCV Error

Question

Простой код, используемый для идентификации игральных карт через кулачок, но я пытался запустить этот код, но я получаю эту ошибку при попытке использовать любой из методов

TypeError: ЦСИ не NumPy массив, ни скаляром

import sys 
import numpy as np 
sys.path.insert(0, "/usr/local/lib/python2.7/site-packages/") 
import cv2 


############################################################################### 
# Utility code 
############################################################################### 

def rectify(h): 
    h = h.reshape((4,2)) 
    hnew = np.zeros((4,2),dtype = np.float32) 

    add = h.sum(1) 
    hnew[0] = h[np.argmin(add)] 
    hnew[2] = h[np.argmax(add)] 

    diff = np.diff(h,axis = 1) 
    hnew[1] = h[np.argmin(diff)] 
    hnew[3] = h[np.argmax(diff)] 

    return hnew 

############################################################################### 
# Image Matching 
############################################################################### 
def preprocess(img): 

    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) 
    blur = cv2.GaussianBlur(gray,(5,5),2) 
    thresh = cv2.adaptiveThreshold(blur,255,1,1,11,1) 
    return thresh 

def imgdiff(img1,img2): 
    img1 = cv2.GaussianBlur(img1,(5,5),5) 
    img2 = cv2.GaussianBlur(img2,(5,5),5)  
    diff = cv2.absdiff(img1,img2) 
    diff = cv2.GaussianBlur(diff,(5,5),5)  
    flag, diff = cv2.threshold(diff, 200, 255, cv2.THRESH_BINARY) 
    return np.sum(diff) 

def find_closest_card(training,img): 
    features = preprocess(img) 
    return sorted(training.values(), key=lambda x:imgdiff(x[1],features))[0][0] 


############################################################################### 
# Card Extraction 
############################################################################### 
def getCards(im, numcards=4): 
    gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY) 
    blur = cv2.GaussianBlur(gray,(1,1),1000) 
    flag, thresh = cv2.threshold(blur, 120, 255, cv2.THRESH_BINARY) 

    contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE) 

    contours = sorted(contours, key=cv2.contourArea,reverse=True)[:numcards] 

    for card in contours: 
    peri = cv2.arcLength(card,True) 
    approx = rectify(cv2.approxPolyDP(card,0.02*peri,True)) 

    # box = np.int0(approx) 
    # cv2.drawContours(im,[box],0,(255,255,0),6) 
    # imx = cv2.resize(im,(1000,600)) 
    # cv2.imshow('a',imx)  

    h = np.array([ [0,0],[449,0],[449,449],[0,449] ],np.float32) 

    transform = cv2.getPerspectiveTransform(approx,h) 
    warp = cv2.warpPerspective(im,transform,(450,450)) 

    yield warp 


def get_training(training_labels_filename,training_image_filename,num_training_cards,avoid_cards=None): 
    training = {} 

    labels = {} 
    for line in file(training_labels_filename): 
    key, num, suit = line.strip().split() 
    labels[int(key)] = (num,suit) 

    print "Training" 

    im = cv2.imread(training_image_filename) 
    for i,c in enumerate(getCards(im,num_training_cards)): 
    if avoid_cards is None or (labels[i][0] not in avoid_cards[0] and labels[i][1] not in avoid_cards[1]): 
     training[i] = (labels[i], preprocess(c)) 

    print "Done training" 
    return training 


if __name__ == '__main__': 
    if len(sys.argv) == 6: 
    filename = sys.argv[1] 
    num_cards = int(sys.argv[2]) 
    training_image_filename = sys.argv[3] 
    training_labels_filename = sys.argv[4]  
    num_training_cards = int(sys.argv[5]) 

    training = get_training(training_labels_filename,training_image_filename,num_training_cards) 

    im = cv2.imread("test") 

    width = im.shape[0] 
    height = im.shape[1] 
    if width < height: 
     im = cv2.transpose(im) 
     im = cv2.flip(im,1) 

    # Debug: uncomment to see registered images 
    #for i,c in enumerate(getCards(im,num_cards)): 
    # card = find_closest_card(training,c,) 
    # cv2.imshow(str(card),c) 
    # cv2.waitKey(0) 

    cards = [find_closest_card(training,c) for c in getCards(im,num_cards)] 
    print cards 

    else: 
    print __doc__ 

здесь все сообщение об ошибке

Traceback (most recent call last): 
    File "<pyshell#15>", line 1, in <module> 
    preprocess("test.JPG") 
    File "C:\Users\Don Ellison\Desktop\Class Programs\CSC 490 Project\Cards\Python\Playing-Card-Recognition-master\card_img.py", line 43, in preprocess 
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) 
TypeError: src is not a numpy array, neither a scalar 

Answer 1

вы передаете в неправильном аргументе функции Preprocess, я предполагаю, что вы вызываете его из оболочка python.

Вы не должны передавать имя файла изображения, а скорее массив numpy. Кажется, вы вызвали функцию proprocess и передали в «test.JPG» в вашей оболочке python. Если вы хотите проверить свою функцию препроцесса, сделайте

test_img = cv2.imread("test.JPG") 
preprocess(test_img)