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Update.
[flatland.git]
/
test.py
diff --git
a/test.py
b/test.py
index
314e03d
..
0a065fa
100755
(executable)
--- a/
test.py
+++ b/
test.py
@@
-4,9
+4,11
@@
import torch
import torchvision
from torchvision import datasets
import torchvision
from torchvision import datasets
+from _ext import flatland
+
######################################################################
######################################################################
-def sequences_to_image(x):
+def sequences_to_image(x
, gap=1, gap_color = (0, 128, 255)
):
from PIL import Image
nb_sequences = x.size(0)
from PIL import Image
nb_sequences = x.size(0)
@@
-19,8
+21,6
@@
def sequences_to_image(x):
height = x.size(3)
width = x.size(4)
height = x.size(3)
width = x.size(4)
- gap = 1
- gap_color = (0, 128, 255)
result = torch.ByteTensor(nb_channels,
gap + nb_sequences * (height + gap),
result = torch.ByteTensor(nb_channels,
gap + nb_sequences * (height + gap),
@@
-32,7
+32,9
@@
def sequences_to_image(x):
for s in range(0, nb_sequences):
for i in range(0, nb_images_per_sequences):
for s in range(0, nb_sequences):
for i in range(0, nb_images_per_sequences):
- result.narrow(1, gap + s * (height + gap), height).narrow(2, gap + i * (width + gap), width).copy_(x[s][i])
+ result.narrow(1, gap + s * (height + gap), height) \
+ .narrow(2, gap + i * (width + gap), width) \
+ .copy_(x[s][i])
result_numpy = result.cpu().byte().transpose(0, 2).transpose(0, 1).numpy()
result_numpy = result.cpu().byte().transpose(0, 2).transpose(0, 1).numpy()
@@
-40,10
+42,6
@@
def sequences_to_image(x):
######################################################################
######################################################################
-from _ext import flatland
-
-x = torch.ByteTensor()
-
-flatland.generate_sequence(10, x)
+x = flatland.generate_sequence(10, 6, 80, 80, True, True)
-sequences_to_image(x).save('sequences.png')
+sequences_to_image(x
, gap = 2, gap_color = (0, 0, 0)
).save('sequences.png')