def show_batch(
x: AudioTensor,
y,
samples,
ctxs=None,
max_n=6,
nrows=2,
ncols=1,
figsize=None,
**kwargs,
):
if figsize is None:
figsize = (4 * x.nchannels, 6)
if ctxs is None:
ctxs = get_grid(min(len(samples), max_n),
nrows=nrows,
ncols=ncols,
figsize=figsize)
ctxs = show_batch[object](x,
y,
samples,
ctxs=ctxs,
max_n=max_n,
hear=False,
**kwargs)
return ctxs
def show_results(x: TensorTS,
y,
samples,
outs,
ctxs=None,
max_n=9,
nrows=None,
ncols=None,
figsize=(14, 12),
**kwargs):
if ctxs is None:
ctxs = get_grid(min(len(samples), max_n),
nrows=nrows,
ncols=ncols,
add_vert=1,
figsize=figsize)
# outs = [('6.0',),('2.0',)]
outs = [detuplify(o) for o in outs]
# outs = ['6.0', '2.0']
ctxs = default_show_results(x,
y,
samples,
outs,
ctxs=ctxs,
max_n=max_n,
figsize=figsize,
**kwargs)
return ctxs
def plot_images(images):
n = len(images)
axs = get_grid(n, figsize=(12,9))
for ax, im in zip(axs, images):
if im.shape[0]==1:
im = rearrange(im, 'c h w -> h w c')
ax.imshow(im)
elif im.shape[0]==3:
im = rearrange(im, 'c h w -> h w c')
ax.imshow(im)
else:
ax.imshow(im)
ax.axis('off')
plt.show()
def show_batch(x: TensorTS,
y,
samples,
ctxs=None,
max_n=9,
nrows=None,
ncols=None,
figsize=(14, 12),
**kwargs):
if ctxs is None:
ctxs = get_grid(min(len(samples), max_n),
nrows=nrows,
ncols=ncols,
figsize=figsize)
ctxs = default_show_batch(x, y, samples, ctxs=ctxs, max_n=max_n, **kwargs)
return ctxs
def show_batch(x: PTBImage,
y,
samples,
ctxs=None,
max_n=6,
nrows=None,
ncols=2,
figsize=None,
**kwargs):
if figsize is None: figsize = (ncols * 6, max_n // ncols * 3)
if ctxs is None:
ctxs = get_grid(min(x[0].shape[0], max_n),
nrows=None,
ncols=ncols,
figsize=figsize)
type(x)
type(x[0])
for i, ctx in enumerate(ctxs):
PTBImage((x[0][i], x[1][i])).show(ctx=ctx)
def show_batch(x: TSeries,
y,
samples,
ctxs=None,
max_n=10,
rows=None,
cols=None,
figsize=None,
**kwargs):
"Show batch for TSeries objects"
if ctxs is None:
ctxs = get_grid(min(len(samples), max_n),
nrows=rows,
ncols=cols,
add_vert=1,
figsize=figsize)
ctxs = show_batch[object](x,
y,
samples=samples,
ctxs=ctxs,
max_n=max_n,
**kwargs)
return ctxs