def log_image(self, step, tag, val):
'''
Write an image event.
:param int step: Time step (x-axis in TensorBoard graphs)
:param str tag: Label for this value
:param numpy.ndarray val: Image in RGB format with values from
0 to 255; a 3-D array with index order (row, column, channel).
`val.shape[-1] == 3`
'''
# TODO: support floating-point tensors, 4-D tensors, grayscale
if len(val.shape) != 3:
raise ValueError(
'`log_image` value should be a 3-D tensor, instead got shape %s'
% (val.shape, ))
if val.shape[2] != 3:
raise ValueError(
'Last dimension of `log_image` value should be 3 (RGB), '
'instead got shape %s' % (val.shape, ))
fakefile = StringIO()
png.Writer(size=(val.shape[1], val.shape[0])).write(
fakefile, val.reshape(val.shape[0], val.shape[1] * val.shape[2]))
encoded = fakefile.getvalue()
# https://tensorflow.googlesource.com/tensorflow/+/master/tensorflow/core/framework/summary.proto
RGB = 3
image = Summary.Image(height=val.shape[0],
width=val.shape[1],
colorspace=RGB,
encoded_image_string=encoded)
summary = Summary(value=[Summary.Value(tag=tag, image=image)])
self._add_event(step, summary)
def make_image(tensor, height, width, channel):
"""Convert an numpy representation image to Image protobuf"""
image = Image.fromarray(tensor)
output = StringIO()
image.save(output, format='PNG')
image_string = output.getvalue()
output.close()
return Summary.Image(height=height,
width=width,
colorspace=channel,
encoded_image_string=image_string)
def make_image(tensor):
"""Convert an numpy representation image to Image protobuf"""
from PIL import Image
height, width, channel = tensor.shape
image = Image.fromarray(tensor)
import io
output = io.BytesIO()
image.save(output, format='PNG')
image_string = output.getvalue()
output.close()
return Summary.Image(height=height,
width=width,
colorspace=channel,
encoded_image_string=image_string)
def image(self, tag, image, step):
image = np.asarray(image)
if image.ndim == 2:
image = image[:, :, None]
if image.shape[-1] == 1:
image = np.repeat(image, 3, axis=-1)
bytesio = io.BytesIO()
PIL.Image.fromarray(image).save(bytesio, 'PNG')
image_summary = Summary.Image(encoded_image_string=bytesio.getvalue(),
colorspace=3,
height=image.shape[0],
width=image.shape[1])
self._write_event(Summary.Value(tag=tag, image=image_summary), step)
def add_entry(self, index, tag, value, **kwargs):
if "image" in kwargs and value is not None:
image_string = tf.image.encode_jpeg(value,
optimize_size=True,
quality=80)
summary_value = Summary.Image(width=value.shape[1],
height=value.shape[0],
colorspace=value.shape[2],
encoded_image_string=image_string)
else:
summary_value = Summary.Value(tag=tag, simple_value=value)
if summary_value is not None:
entry = Summary(value=[summary_value])
self._train_writer.add_summary(entry, index)
