move example code to source file for ease of runnability

This commit is contained in:
Allen Day 2020-05-03 13:51:20 +00:00
parent be13429c6e
commit b53a237560
2 changed files with 16 additions and 19 deletions

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@ -78,25 +78,7 @@ process new data sets, in the documentation of
PYTHONPATH="${PYTHONPATH};"+`pwd`
```
and then you can import the data set in Python.
```python
import tensorflow as tf
from mediapipe.examples.desktop.media_sequence.demo_dataset import DemoDataset
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))
print('The shape of labels_ is %s' % str(labels_.shape))
```
and then you can import the data set in Python using [read_demo_dataset.py](mediapipe/examples/desktop/media_sequence/read_demo_dataset.py)
### Preparing a practical data set
As an example of processing a practical data set, a similar set of commands will

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@ -0,0 +1,15 @@
import tensorflow as tf
from mediapipe.examples.desktop.media_sequence.demo_dataset import DemoDataset
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))
print('The shape of labels_ is %s' % str(labels_.shape))