如何给自己的数据集keras image_ocr

问题描述：

我知道keras image_ocr模型。它采用图像产生的图像，但是，我面临着一些困难，因为我想给我自己的数据集模型的training.vi如何给自己的数据集keras image_ocr

回购链接是：https://github.com/fchollet/keras/blob/master/examples/image_ocr.py

我已经创建数组： x和y。我的图像路径及其相应的gt是在一个csv文件中。

x被给定作为图像的尺寸： [nb_samples，W，H，C]

y被给定它是一个字符串标签中，GT。

这里是我使用的代码预处理：

for i in range(0,len(read_file)): 
    path = read_file['path'][i] 
    label = read_file['gt'][i] 
    path = path.strip('\n') 
    img = cv2.imread(path,0) 
    #Re-sizing the images 
    #height = 64, width = 128 
    #res_img = cv2.resize(img, (128,64)) 
    #cv2.imwrite(i,res_img) 
    h,w = img.shape 
    x.append(img) 
    y.append(label) 
    size = img.size 
    """ 
    print "Height: ", h #Height 
    print "Width: ", w #Width 
    print "Channel: ", C#Channel 
    print "Size: ", size 
    print "\n" 
    """ 
print "H: ", h 
print "W: ", w 
print "S: ", size 

x = np.array(x).astype(np.float32) 
y = np.array(y) 

x_train, x_test, y_train, y_test = train_test_split(x,y,test_size=0.3,random_state=42) 

x_train = np.array(x_train).astype(np.float32) 
y_train = np.array(y_train) 
x_train = np.array(x_train) 
x_test = np.array(x_test) 
y_test = np.array(y_test) 

print "Printing the shapes. \n" 
print "X_train shape: ", x_train.shape 
print "Y_train shape: ", y_train.shape 
print "X_test shape: ", x_test.shape 
print "Y_test shape: ", y_test.shape 
print "\n"

其次是在keras image_ocr代码。总的代码是在这里： https://gist.github.com/kjanjua26/b46388bbde9ded5cf1f077a9f0dedc4f

的错误，当我运行是这样的：

`Traceback (most recent call last): 
File "preprocess.py", line 323, in <module> 
train(run_name, 0, 20, w) 
File "preprocess.py", line 314, in train 
model.fit(next_train(x_train), y_train, batch_size=7, epochs=20,  verbose=1, validation_split=0.1, shuffle=True, initial_epoch=0) 
File "/home/kamranjanjua/anaconda2/lib/python2.7/site- packages/keras/engine/training.py", line 1358, in fit 
batch_size=batch_size) 
File "/home/kamranjanjua/anaconda2/lib/python2.7/site-packages/keras/engine/training.py", line 1234, in _standardize_user_data 
exception_prefix='input') 
File "/home/kamranjanjua/anaconda2/lib/python2.7/site-packages/keras/engine/training.py", line 100, in _standardize_input_data 
'Found: ' + str(data)[:200] + '...') 
TypeError: Error when checking model input: data should be a Numpy array, or list/dict of Numpy arrays. Found: <generator object next_train at 0x7f8752671640>...`

任何帮助，将不胜感激。

答

如果您仔细查看代码，您将能够看到该模型需要一个字典作为其输入。

inputs = {'the_input': X_data,'the_labels': labels, 'input_length': input_length,'label_length': label_length,'source_str': source_str} 

outputs = {'ctc': np.zeros([size])} # dummy data for dummy loss function

对于输入： 1）X_data是训练实例 2）标签是相应的训练示例的标签 3）label_length是标签的长度 4）Input_Length是您输入的长度 5 ）源字符串是它不是强制性的，它只是用于解码

输出是

现在在你的代码，你只产生X_train，y_train为CTC损失功能的虚拟数据，但OTH呃输入丢失。您需要根据模型的预期输入和输出准备数据集。

如何给自己的数据集keras image_ocr

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