def show(
self,
ds_info,
ds,
rows=2,
cols=2,
plot_scale=3.,
audio_key=None,
):
"""Display the audio dataset.
Args:
ds_info: `tfds.core.DatasetInfo` object of the dataset to visualize.
ds: `tf.data.Dataset`. The tf.data.Dataset object to visualize.
rows: `int`, number of rows of the display grid : Default is 2.
cols: `int`, number of columns of the display grid : Default is 2.
plot_scale: `float`, controls the plot size of the images. Keep this
value around 3 to get a good plot. High and low values may cause
the labels to get overlapped.
audio_key: `string`, name of the feature that contains the audio. If not
set, the system will try to auto-detect it.
"""
if not audio_key:
#Auto inferring the audio key
audio_keys = visualizer.extract_keys(ds_info.features,
features_lib.Audio)
key = audio_keys[0]
# Identifying the sample rate If None - 16000KHz is used as default
samplerate = ds_info.features[key].sample_rate
if not samplerate:
samplerate = 16000
_make_audio_grid(ds, key, samplerate, rows, cols, plot_scale)
def show(
self,
ds_info,
ds,
rows=3,
cols=3,
plot_scale=3.,
image_key=None,
):
"""Display the dataset.
Args:
ds_info: `tfds.core.DatasetInfo` object of the dataset to visualize.
ds: `tf.data.Dataset`. The tf.data.Dataset object to visualize. Examples
should not be batched. Examples will be consumed in order until
(rows * cols) are read or the dataset is consumed.
rows: `int`, number of rows of the display grid.
cols: `int`, number of columns of the display grid.
plot_scale: `float`, controls the plot size of the images. Keep this
value around 3 to get a good plot. High and low values may cause
the labels to get overlapped.
image_key: `string`, name of the feature that contains the image. If not
set, the system will try to auto-detect it.
Returns:
fig: The pyplot figure.
"""
# Extract the image key
if not image_key:
image_keys = visualizer.extract_keys(ds_info.features,
features_lib.Image)
if len(image_keys) > 1:
raise ValueError(
'Multiple image features detected in the dataset. '
'Use `image_key` argument to override. Images detected: {}'
.format(image_keys))
image_key = image_keys[0]
# Optionally extract the label key
label_keys = visualizer.extract_keys(ds_info.features,
features_lib.ClassLabel)
label_key = label_keys[0] if len(label_keys) == 1 else None
if not label_key:
logging.info('Was not able to auto-infer label.')
# Single image display
def make_cell_fn(ax, ex):
plt = lazy_imports_lib.lazy_imports.matplotlib.pyplot
if not isinstance(ex, dict):
raise ValueError(
'{} requires examples as `dict`, with the same '
'structure as `ds_info.features`. It is currently not compatible '
'with `as_supervised=True`. Received: {}'.format(
type(self).__name__, type(ex)))
_add_image(ax, ex[image_key])
if label_key:
label = ex[label_key]
label_str = ds_info.features[label_key].int2str(label)
plt.xlabel('{} ({})'.format(label_str, label))
# Returns the grid.
fig = _make_grid(make_cell_fn, ds, rows, cols, plot_scale)
return fig
def match(self, ds_info):
"""See base class."""
# Supervised required a single image key
image_keys = visualizer.extract_keys(ds_info.features,
features_lib.Image)
return len(image_keys) >= 1
def match(self, ds_info):
""" See base class."""
audio_keys = visualizer.extract_keys(ds_info.features,
features_lib.Audio)
return len(audio_keys) > 0
