Open Source Python Realtime Processing Software

The Open Source Computer Vision Library has >2500 algorithms, extensive documentation and sample code for real-time computer vision. It works on Windows, Linux, Mac OS X, Android, iOS in your browser through JavaScript. Languages: C++, Python, Julia, Javascript Homepage: https://opencv.org Q&A forum: https://forum.opencv.org/ Documentation: https://docs.opencv.org Source code: https://github.com/opencv Please pay special attention to our tutorials! https://docs.opencv.org/master Books about the OpenCV are described here: https://opencv.org/books.html

A comprehensive software suite for reading barcodes. Supports EAN/UPC, Code 128, Code 39, Interleaved 2 of 5 and QR Code. Includes libraries and applications for decoding captured barcode images and using a video device (eg, webcam) as a barcode scanner.

This is a constrained global optimization package built upon bayesian inference and gaussian process, that attempts to find the maximum value of an unknown function in as few iterations as possible. This technique is particularly suited for optimization of high cost functions, situations where the balance between exploration and exploitation is important. More detailed information, other advanced features, and tips on usage/implementation can be found in the examples folder. Follow the basic tour notebook to learn how to use the package's most important features. Take a look at the advanced tour notebook to learn how to make the package more flexible, how to deal with categorical parameters, how to use observers, and more. Explore the options exemplifying the balance between exploration and exploitation and how to control it. Explore the domain reduction notebook to learn more about how search can be sped up by dynamically changing parameters' bounds.

LiVES mixes realtime video performance and non-linear editing in one professional quality application. It is designed to be simple to use, yet powerful. It is small in size, yet it has many advanced features. Using LiVES, you can start editing and making video right away, without having to worry about formats, frame sizes, or framerates. It is a very flexible tool which is used by both professional VJ's and video editors - mix and switch clips from the keyboard, use dozens of realtime effects, trim and edit your clips in the clip editor, and bring them together using the multitrack timeline. You can even record your performance in real time, and then edit it further or render it straight away. For the more technically minded, the application is frame and sample accurate, and it can be controlled remotely or scripted for use as a video server. And it supports all of the latest free standards.

PyTorch-NLP is a library for Natural Language Processing (NLP) in Python. It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping. PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out this example code for training on the Stanford Natural Language Inference (SNLI) Corpus. Now you've setup your pipeline, you may want to ensure that some functions run deterministically. Wrap any code that's random, with fork_rng and you'll be good to go. Now that you've computed your vocabulary, you may want to make use of pre-trained word vectors to set your embeddings.

pyTivo is both an HMO and GoBack server. Similar to TiVo Desktop pyTivo loads many standard video compression codecs and outputs mpeg2 video to the TiVo. However, pyTivo is able to load MANY more file types than TiVo Desktop.

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🎥 Effect Screen Recorder Master (ESRM) ESRM es un programa para grabación de pantalla con efectos visuales en tiempo real, hecho 100% con chat GPT, está escrito en python y con interfaz gráfica en Custom Tkinter, se usa FFMPEG para realizar las grabaciones (en cualquier caso, debe instalar FFMPEG y añadirlo al PATH). Está escrito en python v3.12.8, pero está disponible desde las 3.11.6 y superiores. Usa CustomTkinter para una interfaz moderna y ffmpeg para realizar las grabaciones en formato.MP4. Puede ajustar los efectos que requiera los cuales se aplicarán con ayuda de ffmpeg en tiempo real, no necesita de un editor de video externo, puede añadir nitidez, brillo, saturación y demás a la grabación. Este programa también está disponible por medio de el package manager PIP (pypi.org). Ejecute "pip install effect-srm" para instalar, una vez instalado, en CMD y otra terminal, puede ejecutar uno de los siguientes comandos: - srm - esrm - effect-screen-recorder-master

Flipbook is made to flip a sequence of images and allow you to study the resulting animation frame by frame. That's it, pure and simple. I will use Flipbook as the glue between my digital stills camera and a final animation. It will import JPEGs or PNGs

Segmentation models with pre trained backbones. High-level API (just two lines to create a neural network) 9 models architectures for binary and multi class segmentation (including legendary Unet) 124 available encoders (and 500+ encoders from timm) All encoders have pre-trained weights for faster and better convergence. Popular metrics and losses for training routines. All encoders have pretrained weights. Preparing your data the same way as during weights pre-training may give you better results (higher metric score and faster convergence). It is not necessary in case you train the whole model, not only the decoder. Pytorch Image Models (a.k.a. timm) has a lot of pretrained models and interface which allows using these models as encoders in smp, however, not all models are supported. Input channels parameter allows you to create models, which process tensors with an arbitrary number of channels.

This software uses computer vision algorithms for mining sequence data from telemonitoring data with CBRs. We propose an approach which treats the detection of changes in behavior detected with a sensor/video fusion, which occur at radically different time-scales, through a CBR in two levels: low and high level. The system is always updating the database with the daily data.

Python framework for video processing and content analysis using CUDA for acceleration.

Fulguro is an optimized 2D library for image processing with Mathematical Morphology and Linear processing

Simple graphic front-end for ffmpeg/mencoder for resizing most known video files. Written in Python.