# plot_inset

### deepinv.utils.plot_inset(img_list, titles=None, save_fn=None, save_dir=None, tight=True, max_imgs=4, rescale_mode='min_max', show=True, figsize=None, suptitle=None, subtitles=None, cmap='gray', fontsize=17, interpolation='none', cbar=False, dpi=1200, fig=None, axs=None, labels=(), label_loc=(0.03, 0.03), extract_loc=(0.0, 0.0), extract_size=0.2, inset_loc=(0.0, 0.5), inset_size=0.4, return_fig=False, return_axs=False)

Plots a list of images with zoomed-in insets extracted from the images.

#### Deprecated
Deprecated since version This: function is deprecated and will be removed in a future version.
Use [`plot()`](https://deepinv.org/api/stubs/deepinv.utils.plot.html.md#deepinv.utils.plot) with `plot_inset=True` instead, which has the same functionality.

The inset taken from extract_loc and shown at inset_loc. The coordinates extract_loc, inset_loc, and label_loc correspond to their top left corners taken at (horizontal, vertical) from the image’s top left.

Each loc can either be a tuple (float, float) which uses the same loc for all images across the batch dimension, or a list of these whose length must equal the batch dimension.

Coordinates are fractions from 0-1, (0, 0) is the top left corner and (1, 1) is the bottom right corner.

* **Parameters:**
  * **img_list** ([*list*](https://docs.python.org/3.12/library/stdtypes.html#list) *[*[*torch.Tensor*](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor) *]* *,* [*dict*](https://docs.python.org/3.12/library/stdtypes.html#dict) *[*[*str*](https://docs.python.org/3.12/library/stdtypes.html#str) *,*[*torch.Tensor*](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor) *]* *,* [*torch.Tensor*](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor)) – list of images, single image,
    or dict of titles: images to plot.
  * **titles** ([*list*](https://docs.python.org/3.12/library/stdtypes.html#list) *[*[*str*](https://docs.python.org/3.12/library/stdtypes.html#str) *]* *,* [*str*](https://docs.python.org/3.12/library/stdtypes.html#str) *,* *None*) – list of titles for each image, has to be same length as img_list.
  * **save_fn** (*None* *,* [*str*](https://docs.python.org/3.12/library/stdtypes.html#str) *,* [*pathlib.Path*](https://docs.python.org/3.12/library/pathlib.html#pathlib.Path)) – path to save the plot as a single image (i.e. side-by-side).
  * **save_dir** (*None* *,* [*str*](https://docs.python.org/3.12/library/stdtypes.html#str) *,* [*pathlib.Path*](https://docs.python.org/3.12/library/pathlib.html#pathlib.Path)) – path to save the plots as individual images.
  * **tight** ([*bool*](https://docs.python.org/3.12/library/functions.html#bool)) – use tight layout.
  * **max_imgs** ([*int*](https://docs.python.org/3.12/library/functions.html#int)) – maximum number of images to plot.
  * **rescale_mode** ([*str*](https://docs.python.org/3.12/library/stdtypes.html#str)) – rescale mode, either `'min_max'` (images are linearly rescaled between 0 and 1 using
    their min and max values) or `'clip'` (images are clipped between 0 and 1).
  * **show** ([*bool*](https://docs.python.org/3.12/library/functions.html#bool)) – show the image plot. Under the hood, this calls the `plt.show()` function.
  * **figsize** ([*tuple*](https://docs.python.org/3.12/library/stdtypes.html#tuple) *[*[*int*](https://docs.python.org/3.12/library/functions.html#int) *]*) – size of the figure. If `None`, calculated from the size of `img_list`.
  * **subtitles** ([*list*](https://docs.python.org/3.12/library/stdtypes.html#list) *[*[*list*](https://docs.python.org/3.12/library/stdtypes.html#list) *[*[*str*](https://docs.python.org/3.12/library/stdtypes.html#str) *]* *]* *,* [*list*](https://docs.python.org/3.12/library/stdtypes.html#list) *[*[*str*](https://docs.python.org/3.12/library/stdtypes.html#str) *]* *,* [*str*](https://docs.python.org/3.12/library/stdtypes.html#str) *,* *None*) – list of subtitles for each image, can be either the same length or the same shape as img_list.
  * **suptitle** ([*str*](https://docs.python.org/3.12/library/stdtypes.html#str)) – title of the figure.
  * **cmap** ([*str*](https://docs.python.org/3.12/library/stdtypes.html#str)) – colormap to use for the images. Default: gray
  * **fontsize** ([*int*](https://docs.python.org/3.12/library/functions.html#int)) – fontsize for the plot. Default: 17
  * **interpolation** ([*str*](https://docs.python.org/3.12/library/stdtypes.html#str)) – interpolation to use for the images.
    See [https://matplotlib.org/stable/gallery/images_contours_and_fields/interpolation_methods.html](https://matplotlib.org/stable/gallery/images_contours_and_fields/interpolation_methods.html) for more details.
    Default: none
  * **cbar** ([*bool*](https://docs.python.org/3.12/library/functions.html#bool)) – whether to add colorbar to the images.
  * **dpi** ([*int*](https://docs.python.org/3.12/library/functions.html#int)) – DPI to save images.
  * **fig** (*None* *,* [*matplotlib.figure.Figure*](https://matplotlib.org/stable/api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure)) – matplotlib Figure object to plot on. If None, create new Figure. Defaults to None.
  * **axs** (*None* *,* [*matplotlib.axes.Axes*](https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.html#matplotlib.axes.Axes)) – matplotlib Axes object to plot on. If None, create new Axes. Defaults to None.
  * **labels** ([*list*](https://docs.python.org/3.12/library/stdtypes.html#list) *[*[*str*](https://docs.python.org/3.12/library/stdtypes.html#str) *]*) – list of overlaid labels for each image, has to be same length as img_list.
  * **label_loc** ([*list*](https://docs.python.org/3.12/library/stdtypes.html#list) *,* [*tuple*](https://docs.python.org/3.12/library/stdtypes.html#tuple)) – location or locations for label to be plotted on image, defaults to (.03, .03)
  * **extract_loc** ([*list*](https://docs.python.org/3.12/library/stdtypes.html#list) *,* [*tuple*](https://docs.python.org/3.12/library/stdtypes.html#tuple)) – image location or locations for extract to be taken from, defaults to (0., 0.)
  * **extract_size** ([*float*](https://docs.python.org/3.12/library/functions.html#float)) – size of extract to be taken from image, defaults to 0.2
  * **inset_loc** ([*list*](https://docs.python.org/3.12/library/stdtypes.html#list) *,* [*tuple*](https://docs.python.org/3.12/library/stdtypes.html#tuple)) – location or locations for inset to be plotted on image, defaults to (0., 0.5)
  * **inset_size** ([*float*](https://docs.python.org/3.12/library/functions.html#float)) – size of inset to be plotted on image, defaults to 0.4
  * **return_fig** ([*bool*](https://docs.python.org/3.12/library/functions.html#bool)) – return the figure object.
  * **return_axs** ([*bool*](https://docs.python.org/3.12/library/functions.html#bool)) – return the axs object.

## Examples using `plot_inset`:

<div class="sphx-glr-thumbnails">
<!-- thumbnail-parent-div-open --><div class="sphx-glr-thumbcontainer" tooltip="This example focuses on blind image Gaussian denoising, i.e. the problem">![](auto_examples/blind-inverse-problems/images/thumb/sphx_glr_demo_blind_denoising_thumb.png)

[Blind denoising with noise level estimation](https://deepinv.org/auto_examples/blind-inverse-problems/demo_blind_denoising.html.md)

  <div class="sphx-glr-thumbnail-title">Blind denoising with noise level estimation</div>
</div><div class="sphx-glr-thumbcontainer" tooltip="In this example, we investigate a simple 2D Radio Interferometry (RI) imaging task with deepinverse. The following example and data are taken from aghabiglou2024r2d2. If you are interested in RI imaging problem and would like to see more examples or try the state-of-the-art algorithms, please check BASPLib.">![](auto_examples/external-libraries/images/thumb/sphx_glr_demo_ri_basic_thumb.png)

[Radio interferometric imaging with deepinverse](https://deepinv.org/auto_examples/external-libraries/demo_ri_basic.html.md)

  <div class="sphx-glr-thumbnail-title">Radio interferometric imaging with deepinverse</div>
</div><div class="sphx-glr-thumbcontainer" tooltip="This example provides a tour of the denoisers in DeepInverse. A denoiser is a model that takes in a noisy image and outputs a denoised version of it. Basically, it solves the following problem:">![](auto_examples/models/images/thumb/sphx_glr_demo_denoiser_tour_thumb.png)

[Benchmarking pretrained denoisers](https://deepinv.org/auto_examples/models/demo_denoiser_tour.html.md)

  <div class="sphx-glr-thumbnail-title">Benchmarking pretrained denoisers</div>
</div>
<!-- thumbnail-parent-div-close --></div>