Dear ImGui Bundle is a quick-start and all-batteries-included framework to create cross-platform apps with Dear ImGui. It enables to easily create ImGui applications in C++ and Python, under Windows, macOS, Linux, and emscripten (and also iOS).
It is aimed at application developers, researchers, and who want to quickly develop apps and prototypes, taking advantage of the Immediate Gui paradigm.
Dear ImGui Bundle includes the following libraries:
- imgui : Dear ImGui, bloat-free Graphical User interface for C++ with minimal dependencies
- implot: Immediate Mode Plotting
- Hello ImGui: cross-platform Gui apps with the simplicity of a "Hello World" app
- ImGuizmo: Immediate mode 3D gizmo for scene editing and other controls based on Dear ImGui
- ImGuiColorTextEdit: Colorizing text editor for ImGui
- imgui-node-editor: Node Editor built using Dear ImGui
- imgui-knobs: Knobs widgets for ImGui
- ImFileDialog: A file dialog library for Dear ImGui
- portable-file-dialogs Portable GUI dialogs library (C++11, single-header)
- imgui_md: Markdown renderer for Dear ImGui using MD4C parser
- imspinner: Set of nice spinners for imgui
- imgui_toggle: A toggle switch widget for Dear ImGui.
- ImmVision: Immediate image debugger and insights
- imgui_tex_inspect: A texture inspector tool for Dear ImGui
- imgui-command-palette: A Sublime Text or VSCode style command palette in ImGui
This annoucement is voluntarily short, since ImGui Bundle also introduces a somewhat innovative way to present its documentation, since the online demo is also the manual (you can also look at the web manual)
Some highlights with screenshots below:
Lots of widgets
Documentation via a markdow and snippets renderer
Example of a image processing tool developped with the included node editor (imgui-node-editor) and Image analysis (ImmVision) tools
A example with python inside Jupyter Notebook
Hello World, in C++ and Python
The python and C++ api are extremely close and fully documented, enabling an almost line by line transcription, which makes it a great fit for R&D teams who want to quickly develop research tools in python, and still be able to easily port them in production.