python - 属性错误：使用 tf.keras fit_generator() 时，“NoneType”对象没有属性“shape”

问题描述

我有超过 10000 张图像的数据集，我正在使用 tf.keras DataGenerator 批量加载数据。但是，当我使用 model.fit_generator 拟合模型时出现错误：“NoneType”对象没有属性“shape”。

这是代码片段：

import math
import random
import cv2
import numpy as np
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.utils import Sequence
from tensorflow.keras.applications.mobilenet import preprocess_input

class DataGenerator(Sequence):
    
    def __init__(self, dataset, batch_size=30, shuffle=True, predict=False):        
        self.dataset = dataset
        self.batch_size=batch_size
        self.shuffle=shuffle
        self.predict=predict
        self.on_epoch_end()
    
    def __len__(self):        
        return math.ceil(len(self.dataset) /self.batch_size)
    
    def __getitem__(self, index):   
        
        indexes = self.indexes[index*self.batch_size:(index+1)*self.batch_size]        
        image_batch = [self.dataset[i][1]['dicom'] for i in indexes]
        bbox_batch = [self.dataset[i][1]['boxes'] for i in indexes]
        
        X = self.__generate_X(image_batch)
        if self.predict:
            return X
        else:
            masks = self.__generate_masks(bbox_batch)
            return X, masks
        
    def __generate_X(self, image_batch): 
        X = np.zeros((len(image_batch), IMAGE_WIDTH, IMAGE_HEIGHT, 1))
        for k, image_path in enumerate(image_batch):
            img = dicom.read_file(image_path).pixel_array
            img = cv2.resize(img, dsize=(IMAGE_HEIGHT, IMAGE_WIDTH), interpolation=cv2.INTER_CUBIC)
            img = np.expand_dims(img, axis=-1)
            X[k] = preprocess_input(np.array(img, dtype=np.float32))
                
    def __generate_masks(self, bbox_batch):        
        masks = np.zeros((len(bbox_batch), IMAGE_WIDTH, IMAGE_HEIGHT))
        width_factor = IMAGE_WIDTH/imageWidth
        height_factor = IMAGE_HEIGHT/imageHeight
        
        for k, bbox_items in enumerate(bbox_batch):
            if len(bbox_items) > 0:
                for idx, val in enumerate(bbox_items):
                    x1 = round(val[0]* width_factor)
                    x2 = round((val[0]+val[2])* width_factor)
                    y1 = round(val[1]*height_factor)  
                    y2 = round((val[1]+val[3])*height_factor)
                    masks[k][y1:y2, x1:x2]=1 
                
    def on_epoch_end(self):       
        self.indexes = np.arange(len(self.dataset))
        if self.shuffle == True:
            np.random.shuffle(self.indexes)

model = create_model()
model.compile()

train_gen = DataGenerator(X_train, batch_size=30, shuffle=True, predict=False)
val_gen= DataGenerator(X_val, batch_size=30, shuffle=True, predict=False)

model.fit_generator(train_gen, validation_data = val_gen, epochs=1, shuffle=True, verbose=1)

输入：X_train 和 X_val 是 numpy 数组 Tensorflow 版本：1.15.0 Keras 版本：2.2.4 这是我在使用 fit_generator 时遇到的错误

AttributeError                            Traceback (most recent call last)
<ipython-input-52-b30d342db2da> in <module>
----> 1 model.fit_generator(train_gen, validation_data = val_gen, epochs=1,  verbose=1)
      2 

~\Anaconda3\envs\tf\lib\site-packages\tensorflow_core\python\keras\engine\training.py in fit_generator(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, validation_freq, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)
   1294         shuffle=shuffle,
   1295         initial_epoch=initial_epoch,
-> 1296         steps_name='steps_per_epoch')
   1297 
   1298   def evaluate_generator(self,

~\Anaconda3\envs\tf\lib\site-packages\tensorflow_core\python\keras\engine\training_generator.py in model_iteration(model, data, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, validation_freq, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch, mode, batch_size, steps_name, **kwargs)
    255       # `batch_size` used for validation data if validation
    256       # data is NumPy/EagerTensors.
--> 257       batch_size = int(nest.flatten(batch_data)[0].shape[0])
    258 
    259       # Callbacks batch begin.

AttributeError: 'NoneType' object has no attribute 'shape'

我非常感谢任何解决此问题的指导。

标签： pythontensorflowkerasdeep-learningtf.keras

python - 属性错误：使用 tf.keras fit_generator() 时，“NoneType”对象没有属性“shape”

问题描述

解决方案

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