iminspect 1.4.1

Qt-based GUI to visualize image-like data

iminspect

A python utility package for image/matrix visualization.

Moving from MATLAB to python I was missing fast and easy-to-use inspection tools for image data. Thus, iminspect provides a collection of visualization/inspection capabilities along with a simplistic Qt-based GUI. The goal is to enable quick and easy visualization/analysis of:

• color images,
• monochrome images (i.e. any type of 2D matrices),
• label images (i.e. categorical data),
• binary masks,
• depth maps, and
• optical flow data.

Qt Backend

iminspect requires a Qt backend. In Python, you need to either install PyQt or PySide.
The default installation will not install any of these backends, you have to select one on your own.

Optionally, you can install iminspect with a specific backend. Currently, pyqt5, pyqt6, pyside2, and pyside6 are supported:

# PyQt5
python3 -m pip install "iminspect[pyqt5]"

# OR PyQt6
python3 -m pip install "iminspect[pyqt6]"

# OR PySide2
python3 -m pip install "iminspect[pyside2]"

# OR PySide6
python3 -m pip install "iminspect[pyside6]"

Example usage (within a Python script):

from iminspect.inspector import inspect, DataType
import numpy as np

# Show random noise image:
inspect(np.random.rand(4096,4096) - 0.5)

# Show as class labels:
inspect((np.random.rand(16,16) * 1e2 % 5).astype(np.int16), data_type=DataType.CATEGORICAL)

# Show two images next to each other, e.g. useful to analyse RGB and
# corresponding depth, or RGB and corresponding optical flow:
inspect((data_color, data_depth))
# or specify the data types manually:
inspect((rgb, flow), data_type=(DataType.COLOR, DataType.FLOW)))

Example: visualizing categorical data (i.e. labels)

Example: visualizing a mask image

Example: visualizing RGB image and optical flow

Example usage (standalone):

The iminspect package can be run as a standalone application, so you could create a launcher, add it to your system's binary/executable path, etc. You can either do this manually via the following steps or try the standalone/install-... scripts.

1. Set up a virtual environment (in this example, I'll use a separate util-iminspect folder to install the iminspect package):

   cd desired/installation/path
   python3 -m venv util-iminspect
   source util-iminspect/bin/activate
   pip install -U pip
   pip install iminspect
   

2. Run iminspect standalone via:

   desired/installation/path/util-iminspect/bin/python3 -m iminspect
   

Custom input widgets:

The iminspect.inputs subpackage provides common user input widgets, e.g. to select a rectangular region-of-interest, enter an IP address, etc. See the examples/inputs_demo.py application on how to use it. Exemplary screenshot:

UI Documentation

• To inspect a data point/pixel, just move the mouse above it.
• Zooming:
  • Ctrl+Wheel to zoom in/out.
  • Ctrl+Shift+Wheel to speed up zooming.
  • Ctrl+{+|-} to zoom in/out.
  • Ctrl+Shift+{+|-} to zoom in/out faster.
  • Ctrl+F to zoom such that the image fills the available canvas.
  • Ctrl+1 to scale to original size.
• Scrolling:
  • Wheel scrolls up/down.
  • Shift+Wheel speeds up scrolling.
  • Ctrl+{Up|Down|Left|Right} to scroll using keyboard.
  • Ctrl+Shift+{Up|Down|Left|Right} to scroll faster/further.
  • Press and move left/right button to drag the image if zoomed in.
• Keyboard shortcuts:
  • Ctrl+Q and Ctrl+W close the inspection GUI.
  • Ctrl+O shows a dialog to open another file.
  • Ctrl+S shows a dialog to save either the (raw) input or its current visualization.
  • Ctrl+T toggles tool tip display when moving the mouse over the data.
  • Ctrl+R reloads the current data such that the user can select a different visualization/data type.

Changelog

• 1.4.1
  • Adds the missing asset.
• 1.4.0
  • Updates the build process, switching to pyproject.toml
  • Users can choose which Qt/PySide version should be used via the package extras.
• 1.3.11
  • Prevents a TypeError that occurs for some mouse wheel zoom actions on recent OS/Qt versions.
  • Github workflow updates
  • Remove Python EOL versions
  • Fix OS & Python setup for CI test runner
  • Update PyPI action to use Trusted Publishing / OpenID Connect (OIDC)
• 1.3.10
  • Added utility scripts for standalone installation (on Ubuntu).
  • Clarified standalone usage example.
  • Minor tweaks to the inputs subpackage.
• 1.3.9
  • Handle non-finite values: Info/caution message shows in the data summary label, non-finite values are ignored in computing the data statistics.
  • Option (Shortcut and toolbar button) to reload the currently inspected data with a different visualization/data type.
  • Added application icon.
• 1.3.8
  • Added support for opening files via dropping them from external image viewer applications. Tested with common Linux viewers (eog and geeqie).
• 1.3.7
  • Support opening files by dropping them into the viewer.
  • Added __main__ to run module (open the inspector) via python -m iminspect
• 1.3.6
  • Inspector handles 1D inputs.
  • Minor tweaks to the inputs subpackage.
• 1.3.5
  • Bug fix - rounding issues during initialization of custom slider widgets (which use floats).
• 1.3.4
  • Minor tweaks to the inputs subpackage.
• 1.3.3
  • Add functionality to open the inspector without data (in case you want to load from disk).
• 1.3.2
  • Added color picker widget to inputs.
  • Support multiple file selection dialog.
• 1.3.1
  • Minor extensions to user inputs subpackage.
• 1.3.0
  • Added a range slider to adjust visualization limits on the fly.
  • Image viewer (canvas) now supports dragging.
  • Support toggling the tool tip display.
  • Support adding custom labels for categorical data.
  • Fix running inputs.py as standalone demo (relative import confusion).
• 1.2.0
  • Support multi-channel input data (with more than 4 channels).
  • Support analysing multiple images at once, e.g. color images and corresponding optical flow.
  • Major refactoring under the hood.
• 1.1.0
  • Support saving visualization and raw input data to disk.
  • Added shorthand wrapper to inspect() call.
  • UI improvements/layout changes.
  • Fixed typos such as DataType.CATEGORICAL.
  • Added support for partially transparent images (i.e. RGBA).
• 1.0.0
  • Major code refactoring: use data type enum instead of various flags (this breaks previous inspect() calls).
  • Optical flow support.
  • Load another file from disk (via Ctrl+O).
  • Usability improvements, e.g. restore display settings when opening similar data type, handle file loading errors, etc.
• 0.2.0
  • Major refactoring: moved image utils and colorizing code to separate vito package.
  • Usability improvements: keyboard shortcuts for zooming, scaling and scrolling.
• 0.1.2
  • Added tests for non-GUI functionality.
  • Integrate github runners for test/build/deploy.
  • Fix definition for colormap gray.
• 0.1.1
  • Additional features:
    • ImageCanvas supports ROI selection (useful for custom input widgets).
  • Refactoring:
    • Clean up imports.
    • Make pylint/flake8 happier.
  • Fixes:
    • Adjust scrollbars when zooming multiple linked ImageCanvas.
• 0.1.0 - Initial public release.