Exemplos de bucketed_input_pipeline em Python

Exemplo n.º 1

Arquivo: train_crnn.py Projeto: mlnagents/cnn_lstm_ctc_ocr

def _get_input():
    # Set up and return image, label, and image width tensors
    image, width, label, length, text, filename, number_of_images = mjsynth.bucketed_input_pipeline(
        FLAGS.train_path,
        str.split(FLAGS.filename_pattern, ','),
        batch_size=FLAGS.batch_size,
        num_threads=FLAGS.num_input_threads,
        input_device=FLAGS.input_device,
        width_threshold=FLAGS.width_threshold,
        length_threshold=FLAGS.length_threshold)
    return image, width, label, length, text, filename, number_of_images

Exemplo n.º 2

def _get_input():
    """Set up and return image, label, width and text tensors"""

    image, width, label, length, text, filename = mjsynth.bucketed_input_pipeline(
        FLAGS.test_path,
        str.split(FLAGS.filename_pattern, ','),
        batch_size=FLAGS.batch_size,
        num_threads=FLAGS.num_input_threads,
        num_epochs=1)

    return image, width, label, length, text, filename

Exemplo n.º 3

Arquivo: train.py Projeto: ezglory/cnn_lstm_ctc_ocr

def _get_input():
    """Set up and return image, label, and image width tensors"""

    image, width, label, _, _, _ = mjsynth.bucketed_input_pipeline(
        FLAGS.train_path,
        str.split(FLAGS.filename_pattern, ','),
        batch_size=FLAGS.batch_size,
        num_threads=FLAGS.num_input_threads,
        input_device=FLAGS.input_device,
        width_threshold=FLAGS.width_threshold,
        length_threshold=FLAGS.length_threshold)

    #tf.summary.image('images',image) # Uncomment to see images in TensorBoard
    return image, width, label

Exemplo n.º 4

Arquivo: train.py Projeto: trigrass2/cnn_lstm_ctc_ocr

def _get_input():
    """Set up and return image, label, and image width tensors"""

    image,width,label,_,_,_=mjsynth.bucketed_input_pipeline(
        FLAGS.train_path, 
        str.split(FLAGS.filename_pattern,','),
        batch_size=FLAGS.batch_size,
        num_threads=FLAGS.num_input_threads,
        input_device=FLAGS.input_device,
        width_threshold=FLAGS.width_threshold,
        length_threshold=FLAGS.length_threshold )

    #tf.summary.image('images',image) # Uncomment to see images in TensorBoard
    return image,width,label