Search Results for "python image editor" - Page 24
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Showing 1297 open source projects for "python image editor"
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TensorFlow Object Counting API
The TensorFlow Object Counting API is an open source framework
The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems. Please contact if you need professional object detection & tracking & counting project with super high accuracy and reliability! You can train TensorFlow models with your own training data to built your own custom object counter system! If you want to learn how to do it, please check one of the sample projects, which cover some of the... -
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gditools
A Python program/library aimed at GD-ROM image files.
This Python program/library is designed to handle GD-ROM image (GDI) files. It can be used to list files, extract data, generate sorttxt file, extract bootstrap (IP.BIN) file and more. This project can be used in standalone mode, in interactive mode or as a library in another Python program (check the 'addons' folder to learn how). For your convenience, you can use the gditools.py GUI program supplied in the Files section (optional). -
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LuninuxOS
LuninuxOS is a Debian/Ubuntu based Linux distribution.
A Linux operating system, designed and developed to be beautiful, simple, fast, and stable on many computer hardware. -
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QtiPlot is a user-friendly, platform independent data analysis and visualization application similar to the non-free Windows program Origin.
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Image Super-Resolution (ISR)
Super-scale your images and run experiments with Residual Dense
...This can be controlled by the loss weights argument. The weights used to produce these images are available directly when creating the model object. ISR is compatible with Python 3.6 and is distributed under the Apache 2.0 license. -
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VGGFace2
VGGFace2 Dataset for Face Recognition
VGGFace2 is a large-scale face recognition dataset developed to support research on facial recognition across variations in pose, age, illumination, and identity. It consists of 3.31 million images covering 9,131 subjects, with an average of over 360 images per subject. The dataset was collected from Google Image Search, ensuring a wide diversity in ethnicity, profession, and real-world conditions. It is split into a training set with 8,631 identities and a test set with 500 identities,... -
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PixelCNN
Code for the paper "PixelCNN++: A PixelCNN Implementation..."
PixelCNN is the official implementation from OpenAI of the autoregressive generative model described in the paper Conditional Image Generation with PixelCNN Decoders. It provides code for training and evaluating PixelCNN models on image datasets, focusing on conditional image modeling where pixels are generated sequentially based on the values of previously generated pixels. The repository demonstrates how to apply masked convolutions to enforce autoregressive dependencies and achieve... -
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imgaug
Image augmentation for machine learning experiments
imgaug is a library for image augmentation in machine learning experiments. It supports a wide range of augmentation techniques, allows to easily combine these and to execute them in random order or on multiple CPU cores, has a simple yet powerful stochastic interface and can not only augment images but also key points/landmarks, bounding boxes, heatmaps and segmentation maps. Affine transformations, perspective transformations, contrast changes, gaussian noise, dropout of regions,... -
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Ouroboros
Automatically update running docker containers
Ouroboros will monitor (all or specified) running docker containers and update them to the (latest or tagged) available image in the remote registry. The updated container uses the same tag and parameters that were used when the container was first created such as volume/bind mounts, docker network connections, environment variables, restart policies, entrypoints, commands, etc. Push your image to your registry and simply wait your defined interval for ouroboros to find the new image and... -
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The GUIDOLib provides a powerful engine for the graphic rendering of music scores, based on the Guido Music Notation format. It supports Linux, Mac OS X, Windows, Android and iOS operating systems. A Java JNI interface is available as well as a Javascript version of the library. A Web API has also been designed, allowing to deploy the engine as a Web service.
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DisplayCAL
Display Calibration and Characterization powered by Argyll CMS
DisplayCAL (formerly known as dispcalGUI) is a graphical user interface for the display calibration and profiling tools of Argyll CMS, an open source color management system. Calibrate and characterize your display devices using one of the many supported measurement instruments, with support for multi-display setups and a variety of available settings like customizable whitepoint, luminance, tone response curve as well as the option to create accurate look-up-table ICC profiles as well as... -
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WebExKit
An HTML/CSS/JavaScript editor with preview window
The Web Experimentation Kit allows you to enter HTML, CSS and JavaScript and see the results immediately in a browser frame side-by-side with the editor. If you've seen the W3Schools Tryit Editor, JSFiddle or CodePen then this should be familiar to you. The difference between WebExKit and these other applications is that WebExKit is a stand-alone application that runs on your desktop and it allows you to save (and reload) files to your own disk drive. The editor shows a properly formed... -
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Django_blog
A blog application made with Django and bootstrap
A blog application made on Django. -
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NiftyNet
An open-source convolutional neural networks platform for research
An open-source convolutional neural networks platform for medical image analysis and image-guided therapy. NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging... -
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imgFlasher
Flash OS images to sdcards and usb drives
imgFlasher has been built specifically for Embedded and IoT developers in order to flash OS images on SD cards and USB drives. Made primarily for Raspbian, Ubuntu, Debian, Yocto-based images but works with any kind of Linux distribution. imgFlasher is a portable software that doesn't require any installation. The process of flashing OS with imgFlasher is super simple and requires just 3 steps. (1) Choose img/zip file. (2) Choose drive to flash on. (3) Click on... -
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ewi4000s-editor
Patch editor for the Akai EWI 4000s electronic wind instrument
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Torchreid
Deep learning person re-identification in PyTorch
Torchreid is a library for deep-learning person re-identification, written in PyTorch and developed for our ICCV’19 project, Omni-Scale Feature Learning for Person Re-Identification. In "deep-person-reid/scripts/", we provide a unified interface to train and test a model. See "scripts/main.py" and "scripts/default_config.py" for more details. The folder "configs/" contains some predefined configs which you can use as a starting point. The code will automatically (download and) load the... -
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sublime-jekyll
A Sublime Text package for Jekyll static sites
This package is aimed at streamlining the process of managing and creating new Jekyll posts. It does this by providing quick and easy access to new post and draft commands, snippets and completions for Liquid template tags and filters, as well as some handy commands for adding dates and upload links to your posts. -
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Team Purple
Common stuff for Imprudence and Kokua open source metaverse viewers.
The Imprudence and Kokua open source metaverse viewers are developed by Team Purple. This project is for the common stuff that is shared between the two viewers. -
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SimpleITK: a simplified layer build on top of the Insight Toolkit (ITK), intended to facilitate its use in rapid prototyping, education and interpreted languages.
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DCVGAN
DCVGAN: Depth Conditional Video Generation, ICIP 2019.
This paper proposes a new GAN architecture for video generation with depth videos and color videos. The proposed model explicitly uses the information of depth in a video sequence as additional information for a GAN-based video generation scheme to make the model understands scene dynamics more accurately. The model uses pairs of color video and depth video for training and generates a video using the two steps. Generate the depth video to model the scene dynamics based on the geometrical... -
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WALKOFF
A flexible, easy to use, automation framework
...Act faster with WALKOFF by integrating the capabilities you already own to dynamically respond on your terms to your fast-moving environment. Drag and drop workflow editor. Sharable apps and workflows. Deploy on Windows or Linux. Python 2.7 and 3.4+. Scale to your needs. Plug-and-play integration of almost anything with easy-to-develop apps. Send workflow data to custom visual interfaces to act with confidence. Harness the power of automation on your terms. An active community is essential for our success. ... -
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Pydicom by examples
Basic and intermediate examples of DICOM library with Jupyter
Basic and intermediate examples to read, modify and write DICOM files with Python code using Jupyter - To install Jupyter - https://jupyter.org/install ====== All examples are based on Pydicom. An open source library - https://pydicom.github.io/ -
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2D Structural Analysis
Determine the bending moments, shear forces, axial forces and displace
2D Structural Analysis in Python by Ritchie Vink A collection examples of 2D Finite Element Analysis (FEA) made with Jupyter Notebook Lab - https://jupyter.org/ To install Jupyter - https://jupyter.org/install ===== App is available on Play Store -> https://play.google.com/store/apps/details?id=com.ulm.struct If you want to download a python editor for your android smartphone follow this link -> https://play.google.com/store/apps/details? -
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nonechucks
Deal with bad samples in your dataset dynamically
nonechucks is a library that provides wrappers for PyTorch's datasets, samplers and transforms to allow for dropping unwanted or invalid samples dynamically. What if you have a dataset of 1000s of images, out of which a few dozen images are unreadable because the image files are corrupted? Or what if your dataset is a folder full of scanned PDFs that you have to OCRize, and then run a language detector on the resulting text, because you want only the ones that are in English? Or maybe you...
