python初心者です。Taehoon Kim氏のtensorflow(1.13.1)
[画像自動生成デモ](https://github.com/carpedm20/DCGAN-tensorflow)
を実行したところ、以下のエラーが出てしまいました。ご教授頂けましたら幸いです。

```

    File "main.py", line 103, in <module>
     tf.app.run()
    File "/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/platform/app.py", line 125, in run
     _sys.exit(main(argv))
    File "main.py", line 81, in main
     data_dir=FLAGS.data_dir)
    File "/Users/ina/model.py", line 81, in __init__
     raise Exception("[!] No data found in '" + data_path + "'")
    Exception: [!] No data found in './data/celebA/*.jpg'  
    
```

```

    import os
    import scipy.misc
    import numpy as np
    
    from model import DCGAN
    from utils import pp, visualize, to_json, show_all_variables
    
    import tensorflow as tf
    
    flags = tf.app.flags
    flags.DEFINE_integer("epoch", 25, "Epoch to train [25]")
    flags.DEFINE_float("learning_rate", 0.0002, "Learning rate of for adam [0.0002]")
    flags.DEFINE_float("beta1", 0.5, "Momentum term of adam [0.5]")
    flags.DEFINE_float("train_size", np.inf, "The size of train images [np.inf]")
    flags.DEFINE_integer("batch_size", 64, "The size of batch images [64]")```  
    flags.DEFINE_integer("input_height", 108, "The size of image to use (will be center cropped). [108]")  
    flags.DEFINE_integer("input_width", None, "The size of image to use (will be center cropped). If None, same value as input_height [None]")  
    flags.DEFINE_integer("output_height", 64, "The size of the output images to produce [64]")  
    flags.DEFINE_integer("output_width", None, "The size of the output images to produce. If None, same value as output_height [None]")  
    flags.DEFINE_string("dataset", "celebA", "The name of dataset [celebA, mnist, lsun]")  
    flags.DEFINE_string("input_fname_pattern", "*.jpg", "Glob pattern of filename of input images [*]")  
    flags.DEFINE_string("checkpoint_dir", "checkpoint", "Directory name to save the checkpoints [checkpoint]")  
    flags.DEFINE_string("data_dir", "./data", "Root directory of dataset [data]")  
    flags.DEFINE_string("sample_dir", "samples", "Directory name to save the image samples [samples]")  
    flags.DEFINE_boolean("train", False, "True for training, False for testing [False]")  
    flags.DEFINE_boolean("crop", False, "True for training, False for testing [False]")  
    flags.DEFINE_boolean("visualize", False, "True for visualizing, False for nothing [False]")  
    flags.DEFINE_integer("generate_test_images", 100, "Number of images to generate during test. [100]")  
    FLAGS = flags.FLAGS  
    
    
    def main(_):  
    pp.pprint(flags.FLAGS.__flags)  
    
    if FLAGS.input_width is None:  
    FLAGS.input_width = FLAGS.input_height  
    if FLAGS.output_width is None:  
    FLAGS.output_width = FLAGS.output_height  
    
    if not os.path.exists(FLAGS.checkpoint_dir):  
    os.makedirs(FLAGS.checkpoint_dir)  
    if not os.path.exists(FLAGS.sample_dir):  
    os.makedirs(FLAGS.sample_dir)  
    
    gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.333)  
    run_config = tf.ConfigProto()  
    run_config.gpu_options.allow_growth=True  
    
    with tf.Session(config=run_config) as sess:  
    if FLAGS.dataset == 'mnist':  
    dcgan = DCGAN(  
    sess,  
    input_width=FLAGS.input_width,  
    input_height=FLAGS.input_height,  
    output_width=FLAGS.output_width,  
    output_height=FLAGS.output_height,  
    batch_size=FLAGS.batch_size,  
    sample_num=FLAGS.batch_size,  
    y_dim=10,  
    z_dim=FLAGS.generate_test_images,  
    dataset_name=FLAGS.dataset,  
    input_fname_pattern=FLAGS.input_fname_pattern,  
    crop=FLAGS.crop,  
    checkpoint_dir=FLAGS.checkpoint_dir,  
    sample_dir=FLAGS.sample_dir,  
    data_dir=FLAGS.data_dir )  
    else:  
    dcgan = DCGAN(  
    sess,  
    input_width=FLAGS.input_width,  
    input_height=FLAGS.input_height,  
    output_width=FLAGS.output_width,  
    output_height=FLAGS.output_height,  
    batch_size=FLAGS.batch_size,  
    sample_num=FLAGS.batch_size,  
    z_dim=FLAGS.generate_test_images,  
    dataset_name=FLAGS.dataset,  
    input_fname_pattern=FLAGS.input_fname_pattern,  
    crop=FLAGS.crop,  
    checkpoint_dir=FLAGS.checkpoint_dir,  
    sample_dir=FLAGS.sample_dir,  
    data_dir=FLAGS.data_dir)  
    
    show_all_variables()  
    
    if FLAGS.train:  
    dcgan.train(FLAGS)  
    else:  
    if not dcgan.load(FLAGS.checkpoint_dir)[0]:  
    raise Exception("[!] Train a model first, then run test mode")  
    
    
    to_json("./web/js/layers.js", [dcgan.h0_w, dcgan.h0_b, dcgan.g_bn0],  
    [dcgan.h1_w, dcgan.h1_b, dcgan.g_bn1],  
    [dcgan.h2_w, dcgan.h2_b, dcgan.g_bn2],  
    [dcgan.h3_w, dcgan.h3_b, dcgan.g_bn3],  
    [dcgan.h4_w, dcgan.h4_b, None])  
    
    Below is codes for visualization  
    OPTION = 1  
    visualize(sess, dcgan, FLAGS, OPTION)  
    
    if __name__ == '__main__':  
    tf.app.run()
    
```
CC BY-SA 4.0
2019-03-26T01:21:49.597
53730
2019-04-05T12:29:41.113
2019-03-26T08:51:51.497
3060
32674
question
python tensorflow
tensorflowの実行で例外エラーが出てしまいます
まず、画像の該当データ(celebA)をdataフォルダーに移動し、次にPillowインストール後実行しました。  
それでもエラーが出てしまったのですが、一度コードを削除し再度実行したところ成功しました。  
コメント頂き有難うございました。
CC BY-SA 4.0
2019-04-05T12:22:13.270
53956
2019-04-05T12:29:41.113
2019-04-05T12:29:41.113
19110
32674
53730
answer