@ -192,7 +192,7 @@ def train_mnist(folding_id: int, inlier_classes: Sequence[int], total_classes: i
|
|||||||
os.makedirs(directory)
|
os.makedirs(directory)
|
||||||
comparison = k.concatenate([x[:64], x_decoded[:64]], axis=0)
|
comparison = k.concatenate([x[:64], x_decoded[:64]], axis=0)
|
||||||
grid = prepare_image(comparison.cpu(), nrow=64)
|
grid = prepare_image(comparison.cpu(), nrow=64)
|
||||||
summary_ops_v2.image(name='reconstruction_' + str(epoch), tensor=grid, max_images=1)
|
summary_ops_v2.image(name='reconstruction_' + str(epoch), tensor=k.expand_dims(grid, axis=0), max_images=1)
|
||||||
from PIL import Image
|
from PIL import Image
|
||||||
filename = 'results' + str(inlier_classes[0]) + '/reconstruction_' + str(epoch) + '.png'
|
filename = 'results' + str(inlier_classes[0]) + '/reconstruction_' + str(epoch) + '.png'
|
||||||
ndarr = grid.cpu().numpy()
|
ndarr = grid.cpu().numpy()
|
||||||
@ -220,7 +220,7 @@ def train_mnist(folding_id: int, inlier_classes: Sequence[int], total_classes: i
|
|||||||
directory = 'results' + str(inlier_classes[0])
|
directory = 'results' + str(inlier_classes[0])
|
||||||
os.makedirs(directory, exist_ok=True)
|
os.makedirs(directory, exist_ok=True)
|
||||||
grid = prepare_image(resultsample)
|
grid = prepare_image(resultsample)
|
||||||
summary_ops_v2.image(name='sample_' + str(epoch), tensor=grid, max_images=1)
|
summary_ops_v2.image(name='sample_' + str(epoch), tensor=k.expand_dims(grid, axis=0), max_images=1)
|
||||||
from PIL import Image
|
from PIL import Image
|
||||||
filename = 'results' + str(inlier_classes[0]) + '/sample_' + str(epoch) + '.png'
|
filename = 'results' + str(inlier_classes[0]) + '/sample_' + str(epoch) + '.png'
|
||||||
ndarr = grid.cpu().numpy()
|
ndarr = grid.cpu().numpy()
|
||||||
|
|||||||
Reference in New Issue
Block a user