Keras錯誤使用Lambda

我剛剛開始與keras本週，並已經通過文檔來弄清楚爲什麼我得到一個錯誤。但我認爲如果我得到一些幫助，速度會更快，而且感覺就像我沒有看到的細節。Keras錯誤使用Lambda

Error when checking model input: expected lambda_input_1 to have 4 dimensions, 
but got array with shape (0, 1)

這是整個代碼，看看是否可以幫助你看到我做錯了什麼。

import csv 
import cv2 
import numpy as np 

lines = [] 
with open('../data2/driving_log.csv') as csvfile: 
     reader = csv.reader(csvfile) 
     for line in reader: 
       lines.append(line) 
     for row in reader: 
      steering_center = float(row[3]) 
       # create adjusted steering measurements for the side camera images 
      correction = 0.2 # this is a parameter to tune 
      steering_left = steering_center + correction 
      steering_right = steering_center - correction 
       # read in images from center, left and right cameras 
      directory = "..." # fill in the path to your training IMG directory 
      img_center = process_image(np.asarray(Image.open(path + row[0]))) 
      img_left = process_image(np.asarray(Image.open(path + row[1]))) 
      img_right = process_image(np.asarray(Image.open(path + row[2]))) 
       # add images and angles to data set 
      car_images.extend(img_center, img_left, img_right) 
      steering_angles.extend(steering_center, steering_left, steering_right) 

images = [] 
measurements =[] 
for line in lines: 
     source_path = line[0] 
     filename = source_path.split('/')[-1] 
     current_path = '../data2/IMG/' + filename 
     image = cv2.imread(current_path) 
     measurement = float(line[3]) 
     measurements.append(measurement) 

augmented_images, augmented_measuremnets = [], [] 
for image, measurement in zip(image, measurements): 
     augmented_images.append(image) 
     augmented_measuremnets.append(measurement) 
     augmented_images.append(cv2.flip(image,1)) 
     augmented_measuremnets.append(measurement*-1) 

X_train = np.array(images) 
y_train = np.array(measurements) 

from keras.models import Sequential 
from keras.layers import Flatten, Dense, Lambda, Cropping2D 
from keras.layers.convolutional import Convolution2D 
from keras.layers.pooling import MaxPooling2D 

model = Sequential() 
model.add(Lambda(lambda x: x/255.0 - 0.5, input_shape=(160,320,3))) 
model.add(Cropping2D(cropping=((70,25), (0,0)))) 
model.add(Convolution2D(24,5,5, subsample=(2,2), activation="relu")) 
model.add(Convolution2D(36,5,5, subsample=(2,2), activation="relu")) 
model.add(Convolution2D(48,5,5, subsample=(2,2), activation="relu")) 
model.add(Convolution2D(64,3,3, activation="relu")) 
model.add(Convolution2D(64,3,3, activation="relu")) 
model.add(Flatten()) 
model.add(Dense(120)) 
model.add(Dense(84)) 
model.add(Dense(1)) 

model.compile(loss='mse', optimizer='adam') 
model.fit(X_train, y_train, validation_split=0.2, shuffle=True, nb_epoch=5) 


model.save('model.h5') 
exit()

我試圖找出如果我需要調整我的輸入數據設置該model.fit(...)功能正常工作。它之前工作沒有問題，直到我添加裁剪和更多的數據。

謝謝，任何方向都會有幫助，即使它讓我更接近理解這個尺寸誤差。

File "nvidia.py", line 64, in <module> 
     model.fit(X_train, y_train, validation_split=0.2, shuffle=True, nb_epoch=5) 
     File "/home/carnd/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/models.py", line 672, in fit 
     initial_epoch=initial_epoch) 
     File "/home/carnd/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/engine/training.py", line 1117, in fit 
     batch_size=batch_size) 
     File "/home/carnd/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/engine/training.py", line 1030, in _standardize_user_data 
     exception_prefix='model input') 
     File "/home/carnd/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/engine/training.py", line 112, in standardize_input_data 
     str(array.shape)) 
    ValueError: Error when checking model input: expected lambda_input_1 to have 4 dimensions, but got array with shape (0, 1)

來源

2017-07-25 Nicholas Johnson