def image_boxes(tag,
tensor_image,
tensor_boxes,
rescale=0.8,
mean_pixs=(122.7717, 115.9465, 102.9801)):
'''Outputs a `Summary` protocol buffer with images.'''
tensor_image = make_np(tensor_image, 'IMG')
tensor_boxes = make_np(tensor_boxes)
if isinstance(tensor_image, list):
res = []
for i, t in enumerate(tensor_image):
t = t + mean_pixs
rois = tensor_boxes[tensor_boxes[:, 0] == i, 1:5]
image = make_image(t.astype(np.uint8, copy=False),
rescale=rescale,
rois=rois)
res.append(
Summary(
value=[Summary.Value(tag=tag + ('_%d' % i), image=image)]))
return res
else:
tensor_image = tensor_image + mean_pixs
# Assuming the values are within [0,255] now
rois = tensor_boxes[:, 1:5]
image = make_image(tensor_image.astype(np.uint8, copy=False),
rescale=rescale,
rois=rois)
return Summary(value=[Summary.Value(tag=tag, image=image)])
def text(tag, text):
'''Outputs a `Summary` protocol buffer with text.'''
PluginData = [SummaryMetadata.PluginData(plugin_name='text')]
smd = SummaryMetadata(plugin_data=PluginData)
tensor = TensorProto(dtype='DT_STRING',
string_val=[text.encode(encoding='utf_8')],
tensor_shape=TensorShapeProto(dim=[TensorShapeProto.Dim(size=1)]))
return Summary(value=[Summary.Value(node_name=tag, metadata=smd, tensor=tensor)])
def image(tag,
tensor,
rescale=0.6,
mean_pixs=(122.7717, 115.9465, 102.9801)):
'''Outputs a `Summary` protocol buffer with images.'''
tensor = make_np(tensor, 'IMG')
if isinstance(tensor, list):
res = []
for i, t in enumerate(tensor):
t = t + mean_pixs
image = make_image(t.astype(np.uint8, copy=False), rescale=rescale)
res.append(Summary(value=[Summary.Value(tag=tag + ('_%d' % i), image=image)]))
else:
tensor = tensor + mean_pixs
# Assuming the values are within [0,255] now
image = make_image(tensor.astype(np.uint8, copy=False), rescale=rescale)
return Summary(value=[Summary.Value(tag=tag, image=image)])
def memory(tag, tensor, rescale=4.0, value_scale=1.0):
tensor = make_np(tensor, 'MEM')
if isinstance(tensor, list):
res = []
for i, t in enumerate(tensor):
t = np.minimum(t * (255. / value_scale), 255.)
t = np.concatenate((t, t, t), axis=2)
image = make_image(t.astype(np.uint8, copy=False), rescale=rescale)
res.append(
Summary(
value=[Summary.Value(tag=tag + ('_%d' % i), image=image)]))
return res
else:
t = np.minimum(tensor * (255. / value_scale), 255.)
tensor = np.concatenate((t, t, t), axis=2)
image = make_image(tensor.astype(np.uint8, copy=False),
rescale=rescale)
return Summary(value=[Summary.Value(tag=tag, image=image)])
def make_image(tensor, rescale):
'''Convert an numpy representation image to Image protobuf.'''
height, width, channel = tensor.shape
theight = int(height * rescale)
twidth = int(width * rescale)
image = Image.fromarray(tensor)
image = image.resize((twidth, theight), Image.ANTIALIAS)
output = io.BytesIO()
image.save(output, format='PNG')
image_string = output.getvalue()
output.close()
return Summary.Image(height=theight,
width=twidth,
colorspace=channel,
encoded_image_string=image_string)
def scalar(name, scalar):
'''Assume for the scalar values are NOT needed to fetch.'''
assert np.isscalar(scalar), 'ERROR: scalar values are not to be fetched'
scalar = np.float32(scalar)
return Summary(value=[Summary.Value(tag=name, simple_value=scalar)])
def histogram_with_values(name, values, bins):
hist = make_histogram(values.astype(np.float32, copy=False), bins)
return Summary(value=[Summary.Value(tag=name, histo=hist)])
def image(tag, tensor, rescale=0.6, mean_pixs=(122.7717, 115.9465, 102.9801)):
'''Outputs a `Summary` protocol buffer with images.'''
tensor = make_np(tensor, 'IMG') + mean_pixs
# Assuming the values are within [0,255] now
image = make_image(tensor.astype(np.uint8, copy=False), rescale=rescale)
return Summary(value=[Summary.Value(tag=tag, image=image)])
def histogram(name, values, bins):
'''Outputs a `Summary` protocol buffer with a histogram.'''
values = make_np(values)
hist = make_histogram(values.astype(np.float32, copy=False), bins)
return Summary(value=[Summary.Value(tag=name, histo=hist)])