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