Search Results for "display"
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Showing 13 open source projects for "display"
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1
mediapy
This Python library makes it easy to display images and videos
Read/write/show images and videos in an IPython/Jupyter notebook. -
2
Python Progressbar
Progressbar 2 - A progress bar for Python 2 and Python 3
A text progress bar is typically used to display the progress of a long-running operation, providing a visual cue that processing is underway. The progressbar is based on the old Python progressbar package that was published on the now-defunct Google Code. Since that project was completely abandoned by its developer and the developer did not respond to my email, I decided to fork the package. -
3
eCxx
A C++ library for AVR and NodeMCU
NOTE: This project is marked with 'Status: Abandoned' on SourceForge because not enough time can be dedicated to this project. However it may still get sporadic commits to the repository. eCxx is a library for AVR and NodeMCU tailored for micro LED displays and lighting effects. eCxx is utilizing Makefile build system. Java and Python based applications/tools are also included to ease the development and debugging process using the host PC. On one side, eCxx supports the original... -
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vim-jukit
Jupyter-Notebook inspired Neovim/Vim Plugin
REPL plugin and Jupyter-Notebook alternative for (Neo)Vim. This plugin is aimed at users in search for a REPL plugin with lots of additional features. -
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5
Neural Network Visualization
Project for processing neural networks and rendering to gain insights
nn_vis is a minimalist visualization tool for neural networks written in Python using OpenGL and Pygame. It provides an interactive, graphical representation of how data flows through neural network layers, offering a unique educational experience for those new to deep learning or looking to explain it visually. By animating input, weights, activations, and outputs, the tool demystifies neural network operations and helps users intuitively grasp complex concepts. Its lightweight codebase is... -
6
earthengine-py-notebooks
A collection of 360+ Jupyter Python notebook examples
...These notebooks are organized into thematic areas such as image processing, machine learning, visualization, filtering, and asset management, exposing users to real geospatial analysis tasks. The repository makes it easier to explore Earth Engine’s large geospatial data catalog, interactively display map layers, and generate visual insights without the need for external GIS software by leveraging interactive widgets and mapping libraries. Many of the notebooks integrate with tools like folium, ipyleaflet, and geemap to bridge Earth Engine data with Python’s rich ecosystem for plotting and analysis. Users can quickly adapt the examples for their own remote sensing, environmental monitoring, or spatial data science projects, and can run the code in environments like Google Colab. -
7
MMdnn
Tools to help users inter-operate among deep learning frameworks
...During the model conversion, we generate some code snippets to simplify later retraining or inference. We provide a model collection to help you find some popular models. We provide a model visualizer to display the network architecture more intuitively. We provide some guidelines to help you deploy DL models to another hardware platform. -
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Alfred-Workflow
Full-featured library for writing Alfred 3 & 4 workflows
Alfred-Workflow is a Python helper library for Alfred 2, 3 and 4 workflow authors, developed and hosted on GitHub. Alfred workflows typically take user input, fetch data from the Web or elsewhere, filter them and display results to the user. Alfred-Workflow takes care of a lot of the details for you, allowing you to concentrate your efforts on your workflow’s functionality. Alfred-Workflow supports macOS 10.7+ (Python 2.7). Easily launch background tasks (daemons) to keep your workflow responsive. Check for and install new workflow versions using GitHub releases. ... -
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PixieDust
Python Helper library for Jupyter Notebooks
PixieDust is an open source Python helper library that works as an add-on to Jupyter notebooks to improve the user experience of working with data. It also fills a gap for users who have no access to configuration files when a notebook is hosted on the cloud. -
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10
PyQtRPT
Pyside QtRPT
Pyside QtRPT Python Binding for QtRPT (PySide Shiboken) QtRPT Report Engine Python Report License LGPL3 compatible with QtRPT (see license) """QtRPT is the easy-to-use print report engine written in C++ QtToolkit. It allows combining several reports in one XML file. For separately taken field, you can specify some condition depending on which this field will display in different font and background color, etc. The project consists of two parts: report library QtRPT and report designer application QtRptDesigner. Report file is a file in XML format. The report designer makes easy to create report XML file. QtRPT (http://www.qtrpt.tk/index.php) Recommendations: please read "readme.txt" file use QtRptDesigner -> to edit xml files. ... -
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tkFileBrowser
File browser for Tkinter
tkFileBrowser is an alternative to tkinter.filedialog that allows the user to select files or directories. The GUI is written with tkinter but the look is closer to GTK and the application uses GTK bookmarks (the one displayed in nautilus or thunar for instance). This filebrowser supports new directory creation and filtype filtering. -
12
pivottablejs
Drag’n’drop Pivot Tables and Charts for Jupyter/IPython Notebook
PivotTable.js is a Javascript Pivot Table and Pivot Chart library with drag-drop interactivity, and it can now be used with Jupyter/IPython Notebook via the pivottablejs module. I first built PivotTable.js with a plan to build an in-browser data analysis tool, and got as far as one where you could load up a CSV file in the browser for display. Since then, however, the Jupyter project has gathered steam and now provides a browser-based interface to some of the most powerful data processing libraries in the world, so it makes sense to interface with it. -
13
Clint
Clint is a library for Qt projects to create charts, trees, etc.
Clint can display data containing in a QAbstractItemModel as charts, trees or timelines. A chart can be linear ( data are displayed as curves, bars or points), radial ( data are displayed like a bar chart but in circle) or a piechart (2D or 3D). A tree displays data from a model like QTreeItemModel in a classic tree (horizontal or vertical) or radial (in circle).
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