Python datasets.download_and_convert_flowers.run() Examples

The following are 30 code examples of datasets.download_and_convert_flowers.run(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module datasets.download_and_convert_flowers , or try the search function .
Example #1
Source File: download_and_convert_data.py    From terngrad with Apache License 2.0 6 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    if FLAGS.shard:
      download_convert_and_shard_cifar10.run(FLAGS.dataset_dir)
    else:
      download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_dir)
Example #2
Source File: data_generator.py    From SSD_tensorflow_VOC with Apache License 2.0 6 votes vote down vote up 
def display_data():
    
    with tf.Graph().as_default(): 
        dataset = flowers.get_split('train', flowers_data_dir)
        data_provider = slim.dataset_data_provider.DatasetDataProvider(
            dataset, common_queue_capacity=32, common_queue_min=1)
        image, label = data_provider.get(['image', 'label'])
        
        with tf.Session() as sess:    
            with slim.queues.QueueRunners(sess):
                for i in range(4):
                    np_image, np_label = sess.run([image, label])
                    height, width, _ = np_image.shape
                    class_name = name = dataset.labels_to_names[np_label]
                    
                    plt.figure()
                    plt.imshow(np_image)
                    plt.title('%s, %d x %d' % (name, height, width))
                    plt.axis('off')
                    plt.show()
    return
Example #3
Source File: download_and_convert_data.py    From Machine-Learning-with-TensorFlow-1.x with MIT License 6 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'diabetic':
      download_and_convert_diabetic.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #4
Source File: data_generator.py    From SSD_tensorflow_VOC with Apache License 2.0 6 votes vote down vote up 
def disp_data():
    with tf.Graph().as_default(): 
        dataset = flowers.get_split('train', flowers_data_dir)
        data_provider = slim.dataset_data_provider.DatasetDataProvider(
            dataset, common_queue_capacity=32, common_queue_min=1)
        image, label,format = data_provider.get(['image', 'label', 'format'])
        
        with tf.Session() as sess:    
            with slim.queues.QueueRunners(sess):
                for i in range(4):
                    np_image, np_label,np_format = sess.run([image, label,format])
                    height, width, _ = np_image.shape
                    class_name = name = dataset.labels_to_names[np_label]
                    
                    plt.figure()
                    plt.imshow(np_image)
                    plt.title('%s, %d x %d' % (name, height, width))
                    plt.axis('off')
                    plt.show()
                
    return
Example #5
Source File: download_and_convert_data.py    From uai-sdk with Apache License 2.0 6 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'fer':
    download_and_convert_fer.run(FLAGS.dataset_dir,FLAGS.pic_path)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #6
Source File: download_and_convert_data.py    From Creative-Adversarial-Networks with MIT License 6 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'wikiart':
    if not FLAGS.input_dataset_dir is None:
      convert_wikiart.run(FLAGS.input_dataset_dir, FLAGS.dataset_dir)

    else:
      raise ValueError("For wikiart, you must supply a valid input directory with --input_dataset_dir")
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #7
Source File: convert_customized_data.py    From nasnet-tensorflow with Apache License 2.0 6 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'customized':
    convert_customized.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #8
Source File: download_and_convert_data.py    From models with Apache License 2.0 6 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'visualwakewords':
    download_and_convert_visualwakewords.run(
        FLAGS.dataset_dir, FLAGS.small_object_area_threshold,
        FLAGS.foreground_class_of_interest)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #9
Source File: download_and_convert_data.py    From HumanRecognition with MIT License 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_dir)
Example #10
Source File: download_and_convert_data.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #11
Source File: download_and_convert_data.py    From nasnet-tensorflow with Apache License 2.0 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #12
Source File: download_and_convert_data.py    From ECO-pytorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_dir)
Example #13
Source File: download_and_convert_data.py    From MAX-Object-Detector with Apache License 2.0 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #14
Source File: download_and_convert_data.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #15
Source File: download_and_convert_data.py    From MBMD with MIT License 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #16
Source File: download_and_convert_data.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #17
Source File: data_generator.py    From SSD_tensorflow_VOC with Apache License 2.0 5 votes vote down vote up 
def apply_random_image():
    with tf.Graph().as_default():
        # The model can handle any input size because the first layer is convolutional.
        # The size of the model is determined when image_node is first passed into the my_cnn function.
        # Once the variables are initialized, the size of all the weight matrices is fixed.
        # Because of the fully connected layers, this means that all subsequent images must have the same
        # input size as the first image.
        batch_size, height, width, channels = 3, 28, 28, 3
        images = tf.random_uniform([batch_size, height, width, channels], maxval=1)
        
        # Create the model.
        num_classes = 10
        logits = my_cnn(images, num_classes, is_training=True)
        probabilities = tf.nn.softmax(logits)
      
        # Initialize all the variables (including parameters) randomly.
        init_op = tf.global_variables_initializer()
      
        with tf.Session() as sess:
            # Run the init_op, evaluate the model outputs and print the results:
            sess.run(init_op)
            probabilities = sess.run(probabilities)
            
    print('Probabilities Shape:')
    print(probabilities.shape)  # batch_size x num_classes 
    
    print('\nProbabilities:')
    print(probabilities)
    
    print('\nSumming across all classes (Should equal 1):')
    print(np.sum(probabilities, 1)) # Each row sums to 1
    return
Example #18
Source File: download_and_convert_data.py    From motion-rcnn with MIT License 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #19
Source File: data_generator.py    From SSD_tensorflow_VOC with Apache License 2.0 5 votes vote down vote up 
def download_convert():
    dataset_dir = flowers_data_dir
    download_and_convert_flowers.run(dataset_dir)
    return
Example #20
Source File: download_and_convert_data.py    From mtl-ssl with Apache License 2.0 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #21
Source File: download_and_convert_data.py    From multilabel-image-classification-tensorflow with MIT License 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #22
Source File: download_and_convert_data.py    From hands-detection with MIT License 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #23
Source File: download_and_convert_data.py    From DOTA_models with Apache License 2.0 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #24
Source File: download_and_convert_data.py    From Action_Recognition_Zoo with MIT License 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_dir)
Example #25
Source File: download_and_convert_data.py    From tensorflow-densenet with Apache License 2.0 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_dir)
Example #26
Source File: download_and_convert_data.py    From tumblr-emotions with Apache License 2.0 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_dir)
Example #27
Source File: download_and_convert_data.py    From tensorflow_yolo2 with MIT License 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_dir)
Example #28
Source File: download_and_convert_data.py    From MAX-Image-Segmenter with Apache License 2.0 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
Example #29
Source File: download_and_convert_data.py    From hops-tensorflow with Apache License 2.0 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_dir)
Example #30
Source File: download_and_convert_data.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
def main(_):
  if not FLAGS.dataset_name:
    raise ValueError('You must supply the dataset name with --dataset_name')
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  if FLAGS.dataset_name == 'cifar10':
    download_and_convert_cifar10.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'flowers':
    download_and_convert_flowers.run(FLAGS.dataset_dir)
  elif FLAGS.dataset_name == 'mnist':
    download_and_convert_mnist.run(FLAGS.dataset_dir)
  else:
    raise ValueError(
        'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)