ValueError: Fehler beim Überprüfen: erwartet conv2d_1_input, um Form zu haben (None, 300, 300, 1), aber Array mit Shape (1, 260, 300, 1)

Question

Ich versuche, den folgenden Code ausführen: Der Code lädt ein existierendes Modell "model_6cat.h5" und führt eine Vorhersage unter Verwendung derselben aus.

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() 

und weil das Netzwerk haben input_shape wie 300x300 aber mein Modell ist wollte 260x300, ich die Fehlermeldung immer bin „Valueerror: Fehler bei der Überprüfung: erwartete conv2d_1_input Form haben (None, 300, 300, 1) aber während der Laufzeit wurde ein Array mit Shape (1, 260, 300, 1) erstellt.

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) 

Gibt es einen Quickfix für dieses Problem? Oder muss ich das Modell neu erstellen?

Answer 1

Ihr Modell erwartet Bilder 300x300 und Sie geben es ein Bild 260x300.

Answer 2

Ihren Code ändern: -

x0, y0, width = 200, 220, 300 

zu

x0, y0, width = 200, 180, 300 

und das Ergebnis sehen.