Search Results for "weight scale software" - Page 5
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Showing 179 open source projects for "weight scale software"
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FuzzBench
FuzzBench - Fuzzer benchmarking as a service
FuzzBench is a large-scale, open research platform developed by Google to evaluate and benchmark fuzzers — automated software testing tools that detect vulnerabilities through randomized input generation. It provides a standardized, reproducible environment for comparing the performance and effectiveness of different fuzzing algorithms on real-world software targets. -
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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... -
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FairScale
PyTorch extensions for high performance and large scale training
FairScale is a collection of PyTorch performance and scaling primitives that pioneered many of the ideas now used for large-model training. It introduced Fully Sharded Data Parallel (FSDP) style techniques that shard model parameters, gradients, and optimizer states across ranks to fit bigger models into the same memory budget. The library also provides pipeline parallelism, activation checkpointing, mixed precision, optimizer state sharding (OSS), and auto-wrapping policies that reduce... -
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UnionML
Build and deploy machine learning microservices
Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine... -
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Rocketry
Modern scheduling library for Python
Scheduler to power your Python apps. Rocketry is a modern statement-based scheduling framework for Python. It is simple, clean and extensive. It is suitable for small and big projects. Unlike the alternatives, Rocketry's scheduler is statement-based. Rocketry natively supports the same scheduling strategies as the other options, including cron and task pipelining, but it can also be arbitrarily extended using custom scheduling statements. Rocketry is suitable for quick automation projects... -
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ECS Deploy
Powerful CLI tool to simplify Amazon ECS deployments, rollbacks, etc.
ecs-deploy simplifies deployments on Amazon ECS by providing a convenience CLI tool for complex actions, which are executed pretty often. Support for complex task definitions (e.g. multiple containers & task role), easily redeploy the current task definition (including docker pull of eventually updated images), deploy new versions/tags or all containers or just a single container in your task definition, scale up or down by adjusting the desired count of running tasks, add or adjust... -
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Jraph
A Graph Neural Network Library in Jax
Jraph (pronounced “giraffe”) is a lightweight JAX library developed by Google DeepMind for building and experimenting with graph neural networks (GNNs). It provides an efficient and flexible framework for representing, manipulating, and training models on graph-structured data. The core of Jraph is the GraphsTuple data structure, which enables users to define graphs with arbitrary node, edge, and global attributes, and to batch variable-sized graphs efficiently for JAX’s just-in-time... -
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DeepLabv3 Plus
Encoder-Decoder with Atrous Separable Convolution
DeepLabv3 Plus is a PyTorch implementation of DeepLabv3+ for semantic segmentation. It implements the encoder-decoder architecture with atrous separable convolution and provides a practical workflow for training, prediction, and mIoU evaluation. The repository supports VOC-style segmentation datasets and includes utilities for annotation generation, JSON dataset conversion, model summary inspection, prediction, and metric calculation. It provides pretrained weight workflows for MobileNetV2... -
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AWS Step Functions Data Science SDK
For building machine learning (ML) workflows and pipelines on AWS
The AWS Step Functions Data Science SDK is an open-source library that allows data scientists to easily create workflows that process and publish machine learning models using Amazon SageMaker and AWS Step Functions. You can create machine learning workflows in Python that orchestrate AWS infrastructure at scale, without having to provision and integrate the AWS services separately. The best way to quickly review how the AWS Step Functions Data Science SDK works is to review the related... -
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Zenoss Community Edition
Zenoss - Intelligent IT Operations Management
Zenoss provides software-defined IT operations for the world’s largest organizations. We deliver the ultimate level of IT service health with simplicity by providing the most granular and intelligent IT service modeling possible, at any scale, and sharing these unique insights with other IT operations management (ITOM) tools to make them more efficient. -
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Nameko
Python framework for building microservices
Write regular Python methods and classes to implement your service. Nameko will manage connections, transports, and concurrency for you. Spin up multiple service instances to easily scale out. Nameko gives you effortless concurrency by yielding workers when they wait for I/O, leaving you free to handle many requests without the worry of threading. Nameko is compatible with almost any protocol, transport or database. Simply use the built-in extensions, build your own or leverage the... -
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Battery Life Saver
Battery Life Saver can extend the life span of laptop batteries.
Battery Life Saver can extend the life span of laptop batteries. Using a Laptop Battery continuously by overcharging above 90% or by below 15%, reduces its life span. This light-weight .exe program, Battery Life Saver will alarm, on excess charging or discharging. Set the desired Battery Limit Percentage using the slider, say 50% and allow the Battery Life Saver to give alarm. It automatically detects, charging and battery status. For more advanced options, contact the... -
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Ligaturizer
Programming Fonts with Ligatures added
...The font-weight will be inherited from the original file; the font name will be replaced with whatever you specified in --output-name. You can also use --prefix instead, in which case the original name will be preserved and whatever you put in --prefix will be prepended to it. -
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PyTorchVideo
A deep learning library for video understanding research
PyTorchVideo is a deep learning library for video understanding, providing modular components and pretrained models for tasks like action recognition, video classification, detection, and self-supervised learning. It is tightly integrated with PyTorch and PyTorch Lightning, offering flexible APIs for building and training spatiotemporal networks. The library includes efficient implementations of state-of-the-art architectures such as SlowFast, X3D, and MViT, optimized for both research... -
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HistogramsApp
Application that generates KDE-PDP plots from geochronological data
HistogramsApp is a Python 3.6 application that generates (KDE and PDP) from geochronological data .HistogramsApp allows to interactively setup plot parameters such as the bandwidth and the peak detection sensibility. To cite the application please refer to: 1) https://www.tandfonline.com/doi/abs/10.1080/00206814.2021.1954556?journalCode=tigr20 Rodriguez-Corcho, A. F., Rojas-Agramonte, Y., Barrera-Gonzalez, J. A., Marroquin-Gomez, M. P., Bonilla-Correa, S., Izquierdo-Camacho, D.,... -
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summer
Summer is light weight Python 3 application framework
Summer is light weight Python 3 application framework to support generic application development. It provides support for business object management, ORM (mapping, declarative transactions), LDAP and localization. Inspired by famous Java Spring application framework. Since 0.5.2 Python 3 is required. -
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Opyrator
Turns your machine learning code into microservices with web API
Instantly turn your Python functions into production-ready microservices. Deploy and access your services via HTTP API or interactive UI. Seamlessly export your services into portable, shareable, and executable files or Docker images. Opyrator builds on open standards - OpenAPI, JSON Schema, and Python type hints - and is powered by FastAPI, Streamlit, and Pydantic. It cuts out all the pain for productizing and sharing your Python code - or anything you can wrap into a single Python... -
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BudgetML
Deploy a ML inference service on a budget in 10 lines of code
Deploy a ML inference service on a budget in less than 10 lines of code. BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end. We built BudgetML because it's hard to find a simple way to get a model in production fast and cheaply. Deploying from scratch involves learning too many different concepts like SSL certificate generation, Docker, REST,... -
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medical image analysis
Libraries and command line tools for medical image processing.
This software provides libraries and command line tools for the processing and analysis of gray scale medical images. -
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Nebula-Python-SDK
A python SDK for managing Nebula container orchestrator
A python SDK for managing Nebula container orchestrator. First, get NebulaPythonSDK onto your machine, now use it in your code. Nebula container orchestrator aims to help devs and ops treat IoT devices just like distributed Dockerized apps. It aim is to act as Docker orchestrator for IoT devices as well as for distributed services such as CDN or edge computing that can span thousands (possibly even millions) of devices worldwide and it does it all while being open-source and completely free.... -
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Makani
Makani was developed a commercial-scale airborne wind turbine
Makani was an ambitious Google X project that sought to harness wind energy using airborne wind turbines — autonomous kites capable of generating power while flying in crosswind patterns. This open-source repository contains the complete software stack that powered Makani’s research and flight systems, including the flight simulator, autopilot controller, avionics firmware, visualization tools, and ground control software. The software enables simulation, control, and analysis of the Makani... -
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Sparse Attention
"Generating Long Sequences with Sparse Transformers" examples
Sparse Attention is OpenAI’s code release for the Sparse Transformer model, introduced in the paper Generating Long Sequences with Sparse Transformers. It explores how modifying the self-attention mechanism with sparse patterns can reduce the quadratic scaling of standard transformers, making it possible to model much longer sequences efficiently. The repository provides implementations of sparse attention layers, training code, and evaluation scripts for benchmark datasets. It highlights... -
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Ansible Examples
A few starter examples of ansible playbooks, to show features
This repository collects practical, real-world examples of using Ansible to automate infrastructure, deployments, and configurations. Each directory demonstrates a specific use case—ranging from setting up web servers, load balancers, and databases to orchestrating multi-tier applications in cloud environments. The examples highlight common Ansible practices such as organizing inventories, writing reusable playbooks, using roles, and handling variables and templates. They’re designed to be... -
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AdaNet
Fast and flexible AutoML with learning guarantees
AdaNet is a TensorFlow framework for fast and flexible AutoML with learning guarantees. AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet builds on recent AutoML efforts to be fast and flexible while providing learning guarantees. Importantly, AdaNet provides a general framework for not only learning a neural network architecture but also for learning to the ensemble to obtain even better models. At each... -
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PyText
A natural language modeling framework based on PyTorch
PyText is a deep-learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapid experimentation and of serving models at scale. It achieves this by providing simple and extensible interfaces and abstractions for model components, and by using PyTorch’s capabilities of exporting models for inference via the optimized Caffe2 execution engine. We use PyText at Facebook to iterate quickly on new modeling ideas and then seamlessly...
