Search Results for "anpr using python" - Page 4
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Showing 737 open source projects for "anpr using python"
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JupyterLite
Wasm powered Jupyter running in the browser
JupyterLite is a browser-based distribution of the Jupyter ecosystem that enables interactive computing entirely within a web browser without requiring a backend server. Built using JupyterLab components and powered by WebAssembly technologies, it allows users to run Python and other language kernels directly in the browser through tools like Pyodide or Xeus. This architecture eliminates the need for installation or server infrastructure, making it highly accessible for education, demonstrations, and lightweight data science workflows. ... -
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py-spy
Sampling profiler for Python programs
py-spy is a sampling profiler for Python programs. It lets you visualize what your Python program is spending time on without restarting the program or modifying the code in any way. py-spy is extremely low overhead: it is written in Rust for speed and doesn't run in the same process as the profiled Python program. This means py-spy is safe to use against production Python code. py-spy works from the command line and takes either the PID of the program you want to sample from or the command line of the python program you want to run. py-spy has three subcommands record, top and dump. py-spy supports recording profiles to a file using the record command. ... -
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PyFCM
Python client for FCM - Firebase Cloud Messaging
Python client for FCM - Firebase Cloud Messaging (Android, iOS and Web) Firebase Cloud Messaging (FCM) is the new version of GCM. It inherits the reliable and scalable GCM infrastructure, plus new features. GCM users are strongly recommended to upgrade to FCM. Using FCM, you can notify a client app that new email or other data is available to sync. -
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Airtest
UI Automation Framework for Games and Apps
...Airtest uses image recognition technology to locate UI elements so that you can automate games and apps without injecting any code. Airtest cases can be easily run on large device farms, using the command line or python API. HTML reports with detailed info and screen recording allow you to quickly locate failure points. NetEase builds Airlab on top of the Airtest Project. AirtestIDE is an out-of-the-box GUI tool that helps to create and run cases in a user-friendly way. AirtestIDE supports a complete automation workflow. ... -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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I hate money
A simple shared budget manager web application
I hate money is a web application made to ease shared budget management. It keeps track of who bought what, when, and for whom; and helps to settle the bills. I hate money is written in python, using the flask framework. It’s developed with ease of use in mind and is trying to keep things simple. Hope you (will) like it! The code is distributed under a BSD beerware derivative: if you meet the people in person and you want to pay them a craft beer, you are highly encouraged to do so. -
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nbmake
Pytest plugin for testing notebooks
Pytest plugin for testing and releasing notebook documentation. To raise the quality of scientific material through better automation. Research/Machine Learning Software Engineers who maintain packages/teaching materials with documentation written in notebooks. -
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ComfyUI
The most powerful and modular diffusion model GUI, api and backend
The most powerful and modular diffusion model is GUI and backend. This UI will let you design and execute advanced stable diffusion pipelines using a graph/nodes/flowchart-based interface. We are a team dedicated to iterating and improving ComfyUI, supporting the ComfyUI ecosystem with tools like node manager, node registry, cli, automated testing, and public documentation. Open source AI models will win in the long run against closed models and we are only at the beginning. Our core mission... -
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Patchwork
Automate code reviews, patching and documentation
Patchwork automates development gruntwork like PR reviews, bug fixing, security patching, and more using a self-hosted CLI agent and your preferred LLMs. -
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Barfi
A Python visual Flow Based Programming library
A Python visual Flow-Based Programming library that integrates into your existing workflow. Barfi is a Flow-Based Programming environment that provides a graphical programming interface. It is integratable into your existing Python workflows. A schema is built using barfi.Blocks. Then the schema is executed with barfi.ComputeEngine. Each barfi.Block has some properties that enable the FBP and schema building. -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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ggshield
Detect and validate 500+ types of hardcoded secrets
...It scans source code, configuration files, commit history, and other artifacts to automatically detect hundreds of different secret types — such as API keys, tokens, and passwords — helping prevent accidental leaks before they reach version control or production environments. ggshield can be used interactively on a developer’s machine, integrated as a pre-commit or pre-push git hook, and run as part of automated build or merge workflows to enforce security policies consistently across teams. It works across major operating systems using Python, and offers standalone packaged binaries for environments where Python isn’t available, making it adaptable to a wide range of developer setups. -
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ipytest
Pytest in IPython notebooks
ipytest allows you to run Pytest in Jupyter notebooks. ipytest aims to give access to the full pytest experience and to make it easy to transfer tests out of notebooks into separate test files. -
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SageMaker Training Toolkit
Train machine learning models within Docker containers
Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and... -
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Cookiecutter Django
Framework for jumpstarting production-ready Django projects quickly
...Send emails via Anymail (using Mailgun by default or Amazon SES if AWS is selected cloud provider, but switchable). Media storage using Amazon S3 or Google Cloud Storage. Docker support using docker-compose for development and production (using Traefik with LetsEncrypt support). Procfile for deploying to Heroku. Provides instructions for deploying to PythonAnywhere. -
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Lightly
A python library for self-supervised learning on images
...This allows selecting the best core set of samples for model training through advanced filtering. We provide PyTorch, PyTorch Lightning and PyTorch Lightning distributed examples for each of the models to kickstart your project. Lightly requires Python 3.6+ but we recommend using Python 3.7+. We recommend installing Lightly in a Linux or OSX environment. With lightly, you can use the latest self-supervised learning methods in a modular way using the full power of PyTorch. Experiment with different backbones, models, and loss functions. -
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wxPython Project Phoenix
wxPython's Project Phoenix. A new implementation of wxPython
wxPython, the cross-platform GUI toolkit for the Python language. With wxPython software developers can create truly native user interfaces for their Python applications, that run with little or no modifications on Windows, Macs and Linux or other Unix-like systems. Welcome to wxPython's Project Phoenix! Phoenix is the improved next-generation wxPython, "better, stronger, faster than he was before." This new implementation is focused on improving speed, maintainability and extensibility.... -
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Transcrypt
Python 3.7 to JavaScript compiler
...In combination with the use of source maps, this enables efficient debugging. Also, code can be tested from the command prompt using stubs. Lightning-fast JavaScript 6 code: call caching, for-loop optimization, in-line JavaScript etc. Integrated static typechecking and minification at the tip of a command-line switch. Also runs on top of node.js. Extensive documentation with many code examples. Apache 2.0 license. Pip-install and go! Seamless integration with the universe of high-quality web-oriented JavaScript libraries, rather than the desktop-oriented Python ones. -
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Raglite
RAGLite is a Python toolkit for Retrieval-Augmented Generation
Raglite is a lightweight framework for building Retrieval-Augmented Generation (RAG) pipelines with minimal configuration. It connects large language models to vector databases for context-aware responses, enabling developers to prototype and deploy RAG systems quickly. Raglite focuses on simplicity and modularity for fast experimentation. -
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mypy-baseline
Integrate mypy in seconds with existing codebase
A CLI tool for painless integration of mypy with an existing Python project. When you run it for the first time, it will remember all types of errors that you already have in the project (generate “baseline”). All consecutive runs will ignore these errors and report only the ones that you introduced after that. -
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troposphere
Python library to create AWS CloudFormation descriptions
The troposphere library allows for easier creation of the AWS CloudFormation JSON by writing Python code to describe the AWS resources. troposphere also includes some basic support for OpenStack resources via Heat. To facilitate catching CloudFormation or JSON errors early the library has property and type checking built into the classes. -
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Rio
WebApps in pure Python. No JavaScript, HTML and CSS needed
Rio is a Python framework designed to build web applications without the need for HTML, CSS, or JavaScript. Inspired by frameworks like Flutter and React, Rio offers a declarative interface and reusable components, enabling developers to create dynamic web apps entirely in Python. It streamlines the development process by managing both frontend and backend seamlessly. -
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PaaSTA
An open, distributed platform as a service
PaaSTA is a highly-available, distributed system for building, deploying, and running services using containers and Kubernetes. PaaSTA has been running production services at Yelp since 2016. It was originally designed to run on top of Apache Mesos but has subsequently been updated to use Kubernetes. Over time the features and functionality that PaaSTA provides have increased but the principal design remains the same. PaaSTA aims to take a declarative description of the services that teams... -
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AWS Toolkit for JetBrains
A plugin for interacting with AWS from JetBrains IDEs
...Supports Java, Python, Node.js, and .NET Core. -
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SageMaker Spark Container
Docker image used to run data processing workloads
...The container images in this repository are used to build the pre-built container images that are used when running Spark jobs on Amazon SageMaker using the SageMaker Python SDK. The pre-built images are available in the Amazon Elastic Container Registry (Amazon ECR), and this repository serves as a reference for those wishing to build their own customized Spark containers for use in Amazon SageMaker. -
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Docker-OSX
Run macOS VM in a Docker! Run near native OSX-KVM in Docker
Run Mac OS X in Docker with near-native performance! X11 Forwarding. iMessage security research! iPhone USB working! macOS in a Docker container. -
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Gigi
Framework for rapid prototyping and development of real-time rendering
Gigi is software designed for rapid prototyping and rapid development of real-time rendering techniques. It is meant for use by professionals, researchers, students, and hobbyists. The goal is to allow work at the speed of thought, and then easily use what was created in real applications using various APIs or engines. Gigi is being actively used and developed but is young software. You may hit bugs or missing features. Please report these so we can improve Gigi and push forward in the most...
