Keras:valueerror:无法将大小为4096的数组重塑为形状（1,64,64,3）

Question

我正在使用cv2为网络摄像头拍照 我使用ASL数据集训练了一个模型，我将从webcamp中对图像进行分类。为此，我需要根据训练过的模型调整图像大小

它说我必须将网络摄像头图像转换为（1，64，64，3）的形状，但它给了我一个错误

import cv2
import numpy as np
from keras.models import load_model
from keras.preprocessing import image
import imutils
from numpy import array

model = load_model('trained_model2.h5')
print('model loaded!')
out_label=['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y']

pre = []
s = ''
cchar = [0, 0]
c1 = ''    
aWeight = 0.5    
capture = cv2.VideoCapture(0)    
top, right, bottom, left = 170, 150, 425, 450    
num_frames = 0    
flag = 0
flag1=  0

while capture.isOpened():
    ret, frame = capture.read()
    
    frame = imutils.resize(frame, width=700)

    frame = cv2.flip(frame, 1)

    clone = frame.copy()

    (height, width) = frame.shape[:2]

    roi = frame[top:bottom, right:left]
    
    gray = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY)
    gray = cv2.GaussianBlur(gray, (7, 7), 0)
    
    img = gray
    
    IMG_SIZE = 64
    
    img = cv2.resize(img, (64, 64))
    img = np.expand_dims(img, axis=0)
    data = img.reshape(1, IMG_SIZE, IMG_SIZE, 3)
    print("converted")
         
    data = data / 255
   
    model_out = model.predict([data][0])
    pnb = np.argmax(model_out)
    print(str(np.argmax(model_out)) + " " + str(out_label[pnb]))
    pre.append(out_label[pnb]) 

    cv2.putText(clone,
           '%s ' % (str(out_label[pnb])),
           (450, 150), cv2.FONT_HERSHEY_PLAIN, 5, (0, 255, 0))
    
    cv2.rectangle(frame, (100, 100), (300, 300), (0, 255, 0), 0)
    crop_image = frame[100:300, 100:300]
    
    blur = cv2.GaussianBlur(crop_image, (3, 3), 0)
    hsv = cv2.cvtColor(blur, cv2.COLOR_BGR2HSV)
    mask2 = cv2.inRange(hsv, np.array([2, 0, 0]), np.array([20, 255, 255]))
    kernel = np.ones((5, 5))  
    dilation = cv2.dilate(mask2, kernel, iterations=1)
    erosion = cv2.erode(dilation, kernel, iterations=1)
    filtered = cv2.GaussianBlur(erosion, (3, 3), 0)
    ret, thresh = cv2.threshold(filtered, 127, 255, 0)
    
    cv2.imshow("Gesture", frame)
    cv2.imshow("Thresholded", thresh)
    
    if cv2.waitKey(1) == ord('q'):
        break
    
capture.release()
cv2.destroyAllWindows()

Answer 1

您正在尝试将4096维图像重塑为形状为（64，64，3）的图像，这表示具有RGB颜色（或OpenCV中的BGR颜色）的图像。但是，正在读取的图像是灰度图像。这意味着您不应将其重新设置为（64，64，3），而应改为（64，64，1）

data = img.reshape(1, IMG_SIZE, IMG_SIZE, 1)