split_video.py 文件源码

def build_graph():
    feature_names=['rgb','audio']
    feature_sizes = [1024, 128] 
    max_quantized_value=2
    min_quantized_value=-2

    seq_example_bytes = tf.placeholder(tf.string)
    contexts, features = tf.parse_single_sequence_example(
        seq_example_bytes,
        context_features={"video_id": tf.FixedLenFeature(
            [], tf.string),
                          "labels": tf.VarLenFeature(tf.int64)},
        sequence_features={
            feature_name : tf.FixedLenSequenceFeature([], dtype=tf.string)
            for feature_name in feature_names
        })

    decoded_features = { name: tf.reshape(
        tf.cast(tf.decode_raw(features[name], tf.uint8), tf.float32),
        [-1, size]) for name, size in zip(feature_names, feature_sizes)
        }
    feature_matrices = {
        name: utils.Dequantize(decoded_features[name],
          max_quantized_value, min_quantized_value) for name in feature_names}

    tf.add_to_collection("vid_tsr", contexts['video_id'])
    tf.add_to_collection("labs_tsr", contexts['labels'].values)
    tf.add_to_collection("rgb_tsr", feature_matrices['rgb'])
    tf.add_to_collection("audio_tsr", feature_matrices['audio'])
    tf.add_to_collection("seq_example_bytes", seq_example_bytes)

#   with tf.Session() as sess:
#       writer = tf.summary.FileWriter('./graphs', sess.graph)