tunnelvision 0.3.3

Experimental tensor viewer for IPython built on top of Voxel

Tunnelvision

Tunnelvision is an experimental tensor viewer for IPython environments based on Voxel.

Installation

Tunnelvision requires Python 3.7+. Wheels are only available for MacOS (x86_64) and Linux for now.

To install Tunnelvision, run:

pip install tunnelvision

Quick Start

The API of tunnelvision is very similar to that of matplotlib. Tunnelvision is a 5D tensor viewer that requires tensors to have the following format: Batch x Depth x Height x Width x Channels, where channels can be 1 (grayscale/monochrome) or 3 (RGB). You can quickly plot (medical) images using:

import numpy as np
import tunnelvision as tv

arr = np.random.randint(0, 2048, (2, 3, 224, 224, 1), dtype=np.uint16)
tv.show(arr)

More advanced plots with segmentation overlays (or colormaps in general) can be created as follows:

ax = tv.Axes(figsize=(512, 512))
ax.imshow(arr1)
ax.imshow(arr2, cmap="seg")
ax.show()

Pyvoxel has support for tunnelvision as well, which allows you to plot images with their correct orientation and spacing, without having to manually set those in the configuration:

import voxel as vx

mv = vx.load("../data/ct/")
tv.show(mv)

VS Code Remote

To use tunnelvision through VS Code remote, we need forward an arbitrary available port to the tunnelvision-server. Once you have forwarded a port from the ports pane within VS Code, make sure to add it to your configuration file for tunnelvision:

# ~/.cache/tunnelvision/default_config.yaml
port: 1337