48 lines
1.6 KiB
Python
48 lines
1.6 KiB
Python
# Copyright 2020 The MediaPipe Authors.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
# Lint as: python3
|
|
"""Example of reading a MediaSequence dataset.
|
|
"""
|
|
|
|
from absl import app
|
|
from absl import flags
|
|
|
|
from mediapipe.examples.desktop.media_sequence.demo_dataset import DemoDataset
|
|
import tensorflow as tf
|
|
|
|
FLAGS = flags.FLAGS
|
|
|
|
|
|
def main(argv):
|
|
if len(argv) > 1:
|
|
raise app.UsageError('Too many command-line arguments.')
|
|
demo_data_path = '/tmp/demo_data/'
|
|
with tf.Graph().as_default():
|
|
d = DemoDataset(demo_data_path)
|
|
dataset = d.as_dataset('test')
|
|
# implement additional processing and batching here
|
|
dataset_output = dataset.make_one_shot_iterator().get_next()
|
|
images = dataset_output['images']
|
|
labels = dataset_output['labels']
|
|
|
|
with tf.Session() as sess:
|
|
images_, labels_ = sess.run([images, labels])
|
|
print('The shape of images_ is %s' % str(images_.shape)) # pylint: disable=superfluous-parens
|
|
print('The shape of labels_ is %s' % str(labels_.shape)) # pylint: disable=superfluous-parens
|
|
|
|
|
|
if __name__ == '__main__':
|
|
app.run(main)
|