diff --git a/demo/image_classification/.gitignore b/demo/image_classification/.gitignore
index 76961dd1436f859f85f75ff9ed7d3fefdec83dc4..6a05b8f6632db0977fceade8b48a89b9f7f6e6cc 100644
--- a/demo/image_classification/.gitignore
+++ b/demo/image_classification/.gitignore
@@ -5,3 +5,5 @@ plot.png
 train.log
 image_provider_copy_1.py
 *pyc
+train.list
+test.list
diff --git a/demo/image_classification/data/download_cifar.sh b/demo/image_classification/data/download_cifar.sh
old mode 100644
new mode 100755
diff --git a/demo/image_classification/image_provider.py b/demo/image_classification/image_provider.py
index 9e2f8b8949b39b930680e6d84758133eed566881..305efbcdc6bb11f1dac65cc3af82fb997db97f27 100644
--- a/demo/image_classification/image_provider.py
+++ b/demo/image_classification/image_provider.py
@@ -58,24 +58,29 @@ def hook(settings, img_size, mean_img_size, num_classes, color, meta, use_jpeg,
     settings.logger.info('DataProvider Initialization finished')
 
 
-@provider(init_hook=hook)
-def processData(settings, file_name):
+@provider(init_hook=hook, min_pool_size=0)
+def processData(settings, file_list):
     """
     The main function for loading data.
     Load the batch, iterate all the images and labels in this batch.
-    file_name: the batch file name.
+    file_list: the batch file list.
     """
-    data = cPickle.load(io.open(file_name, 'rb'))
-    indexes = list(range(len(data['images'])))
-    if settings.is_train:
-        random.shuffle(indexes)
-    for i in indexes:
-        if settings.use_jpeg == 1:
-            img = image_util.decode_jpeg(data['images'][i])
-        else:
-            img = data['images'][i]
-        img_feat = image_util.preprocess_img(img, settings.img_mean,
-                                             settings.img_size, settings.is_train,
-                                             settings.color)
-        label = data['labels'][i]
-        yield img_feat.tolist(), int(label)
+    with open(file_list, 'r') as fdata:
+        lines = [line.strip() for line in fdata]
+        random.shuffle(lines)
+        for file_name in lines:
+            with io.open(file_name.strip(), 'rb') as file:
+                data = cPickle.load(file)
+                indexes = list(range(len(data['images'])))
+                if settings.is_train:
+                    random.shuffle(indexes)
+                for i in indexes:
+                    if settings.use_jpeg == 1:
+                        img = image_util.decode_jpeg(data['images'][i])
+                    else:
+                        img = data['images'][i]
+                    img_feat = image_util.preprocess_img(img, settings.img_mean,
+                                                         settings.img_size, settings.is_train,
+                                                         settings.color)
+                    label = data['labels'][i]
+                    yield img_feat.astype('float32'), int(label)
diff --git a/demo/image_classification/preprocess.py b/demo/image_classification/preprocess.py
index 0286a5d7e9dc8d0f546b18b1ed846c9452cdbe4b..fe7ea19bf02776629dff0f64f5b671dc457eae64 100755
--- a/demo/image_classification/preprocess.py
+++ b/demo/image_classification/preprocess.py
@@ -35,6 +35,8 @@ if __name__ == '__main__':
      data_creator = ImageClassificationDatasetCreater(data_dir,
                                                       processed_image_size,
                                                       color)
+     data_creator.train_list_name = "train.txt"
+     data_creator.test_list_name = "test.txt"
      data_creator.num_per_batch = 1000
      data_creator.overwrite = True
      data_creator.create_batches()
diff --git a/demo/image_classification/preprocess.sh b/demo/image_classification/preprocess.sh
index dfe3eb95d1ab8b2114fcf5e0f461ea0efb7cc1e5..e3e86ff10675c0622867af2eb0d26c87f4bc2db5 100755
--- a/demo/image_classification/preprocess.sh
+++ b/demo/image_classification/preprocess.sh
@@ -17,3 +17,6 @@ set -e
 data_dir=./data/cifar-out
 
 python preprocess.py -i $data_dir -s 32 -c 1
+
+echo "data/cifar-out/batches/train.txt" > train.list
+echo "data/cifar-out/batches/test.txt" > test.list
diff --git a/demo/image_classification/vgg_16_cifar.py b/demo/image_classification/vgg_16_cifar.py
index e8b8af4bd313d0738aafab8da93fc510e40cc3d6..edd6988c48acd6b554e09b721c37b291e21f46eb 100755
--- a/demo/image_classification/vgg_16_cifar.py
+++ b/demo/image_classification/vgg_16_cifar.py
@@ -25,8 +25,8 @@ if not is_predict:
           'img_size': 32,'num_classes': 10,
           'use_jpeg': 1,'color': "color"}
 
-  define_py_data_sources2(train_list=data_dir+"train.list",
-                          test_list=data_dir+'test.list',
+  define_py_data_sources2(train_list="train.list",
+                          test_list="train.list",
                           module='image_provider',
                           obj='processData',
                           args=args)