def _make_debug_chips(split):
debug_chips_dir = join(tmp_dir, '{}-debug-chips'.format(split))
zip_path = join(tmp_dir, '{}-debug-chips.zip'.format(split))
zip_uri = join(train_uri, '{}-debug-chips.zip'.format(split))
make_dir(debug_chips_dir)
dl = data.train_dl if split == 'train' else data.valid_dl
i = 0
for _, (x_batch, y_batch) in enumerate(dl):
for x, y in zip(x_batch, y_batch):
x = x.squeeze()
y = y.squeeze()
# fastai has an x.show(y=y) method, but we need to plot the
# debug chips ourselves in order to use
# a custom color map that matches the colors in the class_map.
# This could be a good things to contribute upstream to fastai.
plt.axis('off')
plt.imshow(x.data.permute((1, 2, 0)).numpy())
plt.imshow(y.data.squeeze().numpy(), alpha=0.4, vmin=0,
vmax=len(colors), cmap=cmap)
plt.savefig(join(debug_chips_dir, '{}.png'.format(i)),
figsize=(3, 3))
plt.close()
i += 1
if i > max_count:
break
if i > max_count:
break
zipdir(debug_chips_dir, zip_path)
upload_or_copy(zip_path, zip_uri)
def _make_debug_chips(split):
debug_chips_dir = join(tmp_dir, '{}-debug-chips'.format(split))
zip_path = join(tmp_dir, '{}-debug-chips.zip'.format(split))
zip_uri = join(train_uri, '{}-debug-chips.zip'.format(split))
make_dir(debug_chips_dir)
ds = data.train_ds if split == 'train' else data.valid_ds
for i, (x, y) in enumerate(ds):
if random.uniform(0, 1) < debug_prob:
x.show(y=y)
plt.savefig(join(debug_chips_dir, '{}.png'.format(i)),
figsize=(3, 3))
plt.close()
zipdir(debug_chips_dir, zip_path)
upload_or_copy(zip_path, zip_uri)
def _make_debug_chips(split):
debug_chips_dir = join(tmp_dir, '{}-debug-chips'.format(split))
zip_path = join(tmp_dir, '{}-debug-chips.zip'.format(split))
zip_uri = join(train_uri, '{}-debug-chips.zip'.format(split))
make_dir(debug_chips_dir)
ds = data.train_ds if split == 'train' else data.valid_ds
n = 0
for i, (x, y) in enumerate(ds):
if i >= max_count:
break
x.show(y=y)
plt.savefig(join(debug_chips_dir, '{}.png'.format(i)),
figsize=(5, 5))
plt.close()
zipdir(debug_chips_dir, zip_path)
upload_or_copy(zip_path, zip_uri)
def _make_debug_chips(split):
debug_chips_dir = join(tmp_dir, '{}-debug-chips'.format(split))
zip_path = join(tmp_dir, '{}-debug-chips.zip'.format(split))
zip_uri = join(train_uri, '{}-debug-chips.zip'.format(split))
make_dir(debug_chips_dir)
ds = data.train_ds if split == 'train' else data.valid_ds
for i, (x, y) in enumerate(ds):
if random.uniform(0, 1) < debug_prob:
plt.axis('off')
plt.imshow(x.data.permute((1, 2, 0)).numpy())
plt.imshow(y.data.squeeze().numpy(),
alpha=0.4,
vmin=0,
vmax=len(colors),
cmap=cmap)
plt.savefig(join(debug_chips_dir, '{}.png'.format(i)),
figsize=(3, 3))
plt.close()
zipdir(debug_chips_dir, zip_path)
upload_or_copy(zip_path, zip_uri)
def _make_debug_chips(split):
debug_chips_dir = join(tmp_dir, '{}-debug-chips'.format(split))
zip_path = join(tmp_dir, '{}-debug-chips.zip'.format(split))
zip_uri = join(train_uri, '{}-debug-chips.zip'.format(split))
make_dir(debug_chips_dir)
ds = data.train_ds if split == 'train' else data.valid_ds
for i, (x, y) in enumerate(ds):
if random.uniform(0, 1) < debug_prob:
# fastai has an x.show(y=y) method, but we need to plot the
# debug chips ourselves in order to use
# a custom color map that matches the colors in the class_map.
# This could be a good things to contribute upstream to fastai.
plt.axis('off')
plt.imshow(x.data.permute((1, 2, 0)).numpy())
plt.imshow(y.data.squeeze().numpy(),
alpha=0.4,
vmin=0,
vmax=len(colors),
cmap=cmap)
plt.savefig(join(debug_chips_dir, '{}.png'.format(i)),
figsize=(3, 3))
plt.close()
zipdir(debug_chips_dir, zip_path)
upload_or_copy(zip_path, zip_uri)