ValueError：錯誤時檢查：預期conv2d_1_input有形狀（無，300,300,1），但有形狀的陣列（1,260,300,1）

-2

我想運行下面的代碼：代碼加載現有模型「model_6cat.h5」，並使用它進行預測。ValueError：錯誤時檢查：預期conv2d_1_input有形狀（無，300,300,1），但有形狀的陣列（1,260,300,1）

from keras.models import load_model 
import matplotlib.pyplot as plt 
import numpy as np 
import copy 
import cv2 
import os 


dataColor = (0,255,0) 
font = cv2.FONT_HERSHEY_SIMPLEX 
fx, fy, fh = 10, 50, 45 
takingData = 0 
className = 'NONE' 
count = 0 
showMask = 0 


classes = 'NONE ONE TWO THREE FOUR FIVE'.split() 


def initClass(name): 
    global className, count 
    className = name 
    os.system('mkdir -p data/%s' % name) 
    count = len(os.listdir('data/%s' % name)) 


def binaryMask(img): 
    img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 
    img = cv2.GaussianBlur(img, (7,7), 3) 
    img = cv2.adaptiveThreshold(img, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 11, 2) 
    ret, new = cv2.threshold(img, 25, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU) 
    return new 


def main(): 
    global font, size, fx, fy, fh 
    global takingData, dataColor 
    global className, count 
    global showMask 

    model = load_model('model_6cat.h5') 

    x0, y0, width = 200, 220, 300 

    cam = cv2.VideoCapture(0) 
    cv2.namedWindow('Original', cv2.WINDOW_NORMAL) 

    while True: 
     # Get camera frame 
     ret, frame = cam.read() 
     frame = cv2.flip(frame, 1) # mirror 
     window = copy.deepcopy(frame) 
     cv2.rectangle(window, (x0,y0), (x0+width-1,y0+width-1), dataColor, 12) 

     # draw text 
     if takingData: 
      dataColor = (0,250,0) 
      cv2.putText(window, 'Data Taking: ON', (fx,fy), font, 1.2, dataColor, 2, 1) 
     else: 
      dataColor = (0,0,250) 
      cv2.putText(window, 'Data Taking: OFF', (fx,fy), font, 1.2, dataColor, 2, 1) 
     cv2.putText(window, 'Class Name: %s (%d)' % (className, count), (fx,fy+fh), font, 1.0, (245,210,65), 2, 1) 

     # get region of interest 
     roi = frame[y0:y0+width,x0:x0+width] 
     roi = binaryMask(roi) 

     # apply processed roi in frame 
     if showMask: 
      window[y0:y0+width,x0:x0+width] = cv2.cvtColor(roi, cv2.COLOR_GRAY2BGR) 

     # take data or apply predictions on ROI 
     if takingData: 
      cv2.imwrite('data/{0}/{0}_{1}.png'.format(className, count), roi) 
      count += 1 
     else: 
      img = np.float32(roi)/255. 
      img = np.expand_dims(img, axis=0) 
      img = np.expand_dims(img, axis=-1) 
      pred = classes[np.argmax(model.predict(img)[0])] 
      cv2.putText(window, 'Prediction: %s' % (pred), (fx,fy+2*fh), font, 1.0, (245,210,65), 2, 1) 
      # use below for demoing purposes 
      #cv2.putText(window, 'Prediction: %s' % (pred), (x0,y0-25), font, 1.0, (255,0,0), 2, 1) 

     # show the window 
     cv2.imshow('Original', window) 

     # Keyboard inputs 
     key = cv2.waitKey(10) & 0xff 

     # use q key to close the program 
     if key == ord('q'): 
      break 

     # Toggle data taking 
     elif key == ord('s'): 
      takingData = not takingData 

     elif key == ord('b'): 
      showMask = not showMask 

     # Toggle class 
     elif key == ord('0'): initClass('NONE') 
     elif key == ord('`'): initClass('NONE') # because 0 is on other side of keyboard 
     elif key == ord('1'): initClass('ONE') 
     elif key == ord('2'): initClass('TWO') 
     elif key == ord('3'): initClass('THREE') 
     elif key == ord('4'): initClass('FOUR') 
     elif key == ord('5'): initClass('FIVE') 

     # adjust the size of window 
     #elif key == ord('z'): 
     # width = width - 5 
     #elif key == ord('a'): 
     # width = width + 5 

     # adjust the position of window 
     elif key == ord('i'): 
      y0 = max((y0 - 5, 0)) 
     elif key == ord('k'): 
      y0 = min((y0 + 5, window.shape[0]-width)) 
     elif key == ord('j'): 
      x0 = max((x0 - 5, 0)) 
     elif key == ord('l'): 
      x0 = min((x0 + 5, window.shape[1]-width)) 

    cam.release() 


if __name__ == '__main__': 
    initClass('NONE') 
    main()

而且由於網絡希望有input_shape爲300×300，但我的模型是260x300，我收到錯誤消息「ValueError異常：檢查時出現錯誤：預期conv2d_1_input有形狀（無，300，300，1）但在運行期間獲得了陣列形狀（1，260，300，1）「。

Traceback (most recent call last): 
    File "application.py", line 137, in <module> 
    main() 
    File "application.py", line 84, in main 
    pred = classes[np.argmax(model.predict(img)[0])] 
    File "/home/pankaj/vev/lib/python3.5/site-packages/keras/models.py", line 913, in predict 
    return self.model.predict(x, batch_size=batch_size, verbose=verbose) 
    File "/home/pankaj/vev/lib/python3.5/site-packages/keras/engine/training.py", line 1695, in predict 
    check_batch_axis=False) 
    File "/home/pankaj/vev/lib/python3.5/site-packages/keras/engine/training.py", line 144, in _standardize_input_data 
    str(array.shape)) 
ValueError: Error when checking : expected conv2d_1_input to have shape (None, 300, 300, 1) but got array with shape (1, 260, 300, 1)

有沒有這個問題的任何quickfix？還是我必須重新創建模型？

來源

2017-08-30 PetPan

該回購中的確切腳本？哪裏發生錯誤？嘗試更具體，否則沒有人可以有任何幫助... – desertnaut

嘗試改進你的問題，編輯它，而不是把鏈接的評論。嘗試發佈[示例]（https://stackoverflow.com/help/mcve） –

您必須將圖像大小調整爲正確的大小... – api55

你的模型預計圖像300x300，你給它一個圖像260x300。

來源

2017-08-30 17:49:28

更改代碼： -

x0, y0, width = 200, 220, 300

到

x0, y0, width = 200, 180, 300

和看到的結果。

來源

2017-12-01 02:27:29

ValueError：錯誤時檢查：預期conv2d_1_input有形狀（無，300,300,1），但有形狀的陣列（1,260,300,1）

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