Book Utils

Pieces of code we can re-use between chapters

If we’d like, we can export code from here to use throughout the book…

show_images

 show_images (ims:list, nrows:Optional[int]=None,
              ncols:Optional[int]=None, titles:Optional[list]=None,
              figsize:tuple=None, imsize:int=3, suptitle:str=None,
              sharex=False, sharey=False, squeeze=True, width_ratios=None,
              height_ratios=None, subplot_kw=None, gridspec_kw=None)

Show all images ims as subplots with rows using titles

	Type	Default	Details
ims	list		Images to show
nrows	typing.Optional[int]	None	Number of rows in grid
ncols	typing.Optional[int]	None	Number of columns in grid (auto-calculated if None)
titles	typing.Optional[list]	None	Optional list of titles for each image
figsize	tuple	None	Width, height in inches of the returned figure
imsize	int	3	Size (in inches) of images that will be displayed in the returned figure
suptitle	str	None	Title to be set to returned figure
sharex	bool	False
sharey	bool	False
squeeze	bool	True
width_ratios	NoneType	None
height_ratios	NoneType	None
subplot_kw	NoneType	None
gridspec_kw	NoneType	None

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get_grid

 get_grid (n:int, nrows:int=None, ncols:int=None, title:str=None,
           weight:str='bold', size:int=14, figsize:tuple=None,
           imsize:int=3, suptitle:str=None, sharex=False, sharey=False,
           squeeze=True, width_ratios=None, height_ratios=None,
           subplot_kw=None, gridspec_kw=None)

Return a grid of n axes, rows by cols

	Type	Default	Details
n	int		Number of axes
nrows	int	None	Number of rows, defaulting to `int(math.sqrt(n))`
ncols	int	None	Number of columns, defaulting to `ceil(n/rows)`
title	str	None	If passed, title set to the figure
weight	str	bold	Title font weight
size	int	14	Title font size
figsize	tuple	None	Width, height in inches of the returned figure
imsize	int	3	Size (in inches) of images that will be displayed in the returned figure
suptitle	str	None	Title to be set to returned figure
sharex	bool	False
sharey	bool	False
squeeze	bool	True
width_ratios	NoneType	None
height_ratios	NoneType	None
subplot_kw	NoneType	None
gridspec_kw	NoneType	None

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subplots

 subplots (nrows:int=1, ncols:int=1, figsize:tuple=None, imsize:int=3,
           suptitle:str=None, sharex=False, sharey=False, squeeze=True,
           width_ratios=None, height_ratios=None, subplot_kw=None,
           gridspec_kw=None, **kwargs)

A figure and set of subplots to display images of imsize inches

	Type	Default	Details
nrows	int	1	Number of rows in returned axes grid
ncols	int	1	Number of columns in returned axes grid
figsize	tuple	None	Width, height in inches of the returned figure
imsize	int	3	Size (in inches) of images that will be displayed in the returned figure
suptitle	str	None	Title to be set to returned figure
sharex	bool	False
sharey	bool	False
squeeze	bool	True
width_ratios	NoneType	None
height_ratios	NoneType	None
subplot_kw	NoneType	None
gridspec_kw	NoneType	None
kwargs

/opt/hostedtoolcache/Python/3.9.16/x64/lib/python3.9/site-packages/fastcore/docscrape.py:225: UserWarning: Unknown section Other Parameters
  else: warn(msg)
/opt/hostedtoolcache/Python/3.9.16/x64/lib/python3.9/site-packages/fastcore/docscrape.py:225: UserWarning: Unknown section See Also
  else: warn(msg)
/opt/hostedtoolcache/Python/3.9.16/x64/lib/python3.9/site-packages/fastcore/docscrape.py:225: UserWarning: Unknown section Notes
  else: warn(msg)

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show_image

 show_image (im, ax=None, figsize=None, title=None, noframe=True,
             cmap=None, norm=None, aspect=None, interpolation=None,
             alpha=None, vmin=None, vmax=None, origin=None, extent=None,
             interpolation_stage=None, filternorm=True, filterrad=4.0,
             resample=None, url=None, data=None)

Show a PIL or PyTorch image on ax.

	Type	Default	Details
im
ax	NoneType	None
figsize	NoneType	None
title	NoneType	None
noframe	bool	True
cmap	NoneType	None	The Colormap instance or registered colormap name used to map scalar data to colors. This parameter is ignored if X is RGB(A).
norm	NoneType	None	The normalization method used to scale scalar data to the [0, 1] range before mapping to colors using cmap. By default, a linear scaling is used, mapping the lowest value to 0 and the highest to 1. If given, this can be one of the following: - An instance of `.Normalize` or one of its subclasses (see :doc:`/tutorials/colors/colormapnorms`). - A scale name, i.e. one of “linear”, “log”, “symlog”, “logit”, etc. For a list of available scales, call `matplotlib.scale.get_scale_names()`. In that case, a suitable `.Normalize` subclass is dynamically generated and instantiated. This parameter is ignored if X is RGB(A).
aspect	NoneType	None	The aspect ratio of the Axes. This parameter is particularly relevant for images since it determines whether data pixels are square. This parameter is a shortcut for explicitly calling `.Axes.set_aspect`. See there for further details. - ‘equal’: Ensures an aspect ratio of 1. Pixels will be square (unless pixel sizes are explicitly made non-square in data coordinates using extent). - ‘auto’: The Axes is kept fixed and the aspect is adjusted so that the data fit in the Axes. In general, this will result in non-square pixels.
interpolation	NoneType	None	The interpolation method used. Supported values are ‘none’, ‘antialiased’, ‘nearest’, ‘bilinear’, ‘bicubic’, ‘spline16’, ‘spline36’, ‘hanning’, ‘hamming’, ‘hermite’, ‘kaiser’, ‘quadric’, ‘catrom’, ‘gaussian’, ‘bessel’, ‘mitchell’, ‘sinc’, ‘lanczos’, ‘blackman’. If interpolation is ‘none’, then no interpolation is performed on the Agg, ps, pdf and svg backends. Other backends will fall back to ‘nearest’. Note that most SVG renderers perform interpolation at rendering and that the default interpolation method they implement may differ. If interpolation is the default ‘antialiased’, then ‘nearest’ interpolation is used if the image is upsampled by more than a factor of three (i.e. the number of display pixels is at least three times the size of the data array). If the upsampling rate is smaller than 3, or the image is downsampled, then ‘hanning’ interpolation is used to act as an anti-aliasing filter, unless the image happens to be upsampled by exactly a factor of two or one. See :doc:`/gallery/images_contours_and_fields/interpolation_methods` for an overview of the supported interpolation methods, and :doc:`/gallery/images_contours_and_fields/image_antialiasing` for a discussion of image antialiasing. Some interpolation methods require an additional radius parameter, which can be set by filterrad. Additionally, the antigrain image resize filter is controlled by the parameter filternorm.
alpha	NoneType	None	The alpha blending value, between 0 (transparent) and 1 (opaque). If alpha is an array, the alpha blending values are applied pixel by pixel, and alpha must have the same shape as X.
vmin	NoneType	None
vmax	NoneType	None
origin	NoneType	None	Place the [0, 0] index of the array in the upper left or lower left corner of the Axes. The convention (the default) ‘upper’ is typically used for matrices and images. Note that the vertical axis points upward for ‘lower’ but downward for ‘upper’. See the :doc:`/tutorials/intermediate/imshow_extent` tutorial for examples and a more detailed description.
extent	NoneType	None	The bounding box in data coordinates that the image will fill. These values may be unitful and match the units of the Axes. The image is stretched individually along x and y to fill the box. The default extent is determined by the following conditions. Pixels have unit size in data coordinates. Their centers are on integer coordinates, and their center coordinates range from 0 to columns-1 horizontally and from 0 to rows-1 vertically. Note that the direction of the vertical axis and thus the default values for top and bottom depend on origin: - For `origin == 'upper'` the default is `(-0.5, numcols-0.5, numrows-0.5, -0.5)`. - For `origin == 'lower'` the default is `(-0.5, numcols-0.5, -0.5, numrows-0.5)`. See the :doc:`/tutorials/intermediate/imshow_extent` tutorial for examples and a more detailed description.
interpolation_stage	NoneType	None	If ‘data’, interpolation is carried out on the data provided by the user. If ‘rgba’, the interpolation is carried out after the colormapping has been applied (visual interpolation).
filternorm	bool	True	A parameter for the antigrain image resize filter (see the antigrain documentation). If filternorm is set, the filter normalizes integer values and corrects the rounding errors. It doesn’t do anything with the source floating point values, it corrects only integers according to the rule of 1.0 which means that any sum of pixel weights must be equal to 1.0. So, the filter function must produce a graph of the proper shape.
filterrad	float	4.0	The filter radius for filters that have a radius parameter, i.e. when interpolation is one of: ‘sinc’, ‘lanczos’ or ‘blackman’.
resample	NoneType	None	When True, use a full resampling method. When False, only resample when the output image is larger than the input image.
url	NoneType	None	Set the url of the created `.AxesImage`. See `.Artist.set_url`.
data	NoneType	None

show_images(torch.rand(4,3,28,28), nrows=2, titles=['a','b','c','d'])

Jeremy noticed that there is no fancy init done with the UNet in diffusers. Hence this function, which does some sensible-looking initialization:

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init_ddpm

 init_ddpm (model)

It’s nice to quickly load images from a URL or file:

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load_image

 load_image (url, size=None, return_tensor=False)