Search Results for "objects"
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Showing 125 open source projects for "objects"
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CO3D (Common Objects in 3D)
Tooling for the Common Objects In 3D dataset
CO3Dv2 (Common Objects in 3D, version 2) is a large-scale 3D computer vision dataset and toolkit from Facebook Research designed for training and evaluating category-level 3D reconstruction methods using real-world data. It builds upon the original CO3Dv1 dataset, expanding both scale and quality—featuring 2× more sequences and 4× more frames, with improved image fidelity, more accurate segmentation masks, and enhanced annotations for object-centric 3D reconstruction. -
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spyder
The scientific Python development environment
Spyder is a free and open source scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts. It features a unique combination of the advanced editing, analysis, debugging, and profiling functionality of a comprehensive development tool with the data exploration, interactive execution, deep inspection, and beautiful visualization capabilities of a scientific package. Spyder’s multi-language Editor integrates a number of powerful tools... -
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objection
Objection - runtime mobile exploration
objection is a runtime mobile exploration toolkit, powered by Frida, built to help you assess the security posture of your mobile applications, without needing a jailbreak. Perform memory-related tasks, such as dumping & patching. Explore and manipulate objects on the heap. Installation is simply a matter of pip3 install objection. This will give you the objection command. You can update an existing objection installation with pip3 install --upgrade objection. A file system listing of the iOS applications main bundle. A file system listing of the Android applications bundle. -
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Django Notebook
Django + shell_plus + Jupyter notebooks made easy
Django + shell_plus + Jupyter notebooks made easy. A Jupyter notebook with access to objects from the Django ORM is a powerful tool to introspect data and run ad-hoc queries. Built-in integration with the imported objects from django-extensions shell_plus. Saves the state between sessions so you don't need to remember what you did. Inheritance diagrams on any object, including ORM models. -
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UCO3D
Uncommon Objects in 3D dataset
uCO3D is a large-scale 3D vision dataset and toolkit centered on turn-table videos of everyday objects drawn from the LVIS taxonomy. It provides about 170,000 full videos per object instance rather than still frames, along with per-video annotations including object masks, calibrated camera poses, and multiple flavors of point clouds. Each sequence also ships with a precomputed 3D Gaussian Splat reconstruction, enabling fast, differentiable rendering workflows and modern implicit/point-based modeling experiments. ... -
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NSync
nsync is a C library that exports various synchronization primitives
...This approach simplifies concurrency management and often improves readability and maintainability of multithreaded code. The library emphasizes efficiency, with locks and condition variables occupying minimal memory and supporting cancellation mechanisms through nsync_note objects rather than thread-level cancellation. Designed with portability and performance in mind, nsync can be compiled on Unix-like systems and Windows using a C90 compiler. -
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Haiku
JAX-based neural network library
...It preserves Sonnet’s module-based programming model for state management while retaining access to JAX’s function transformations. Haiku can be expected to compose with other libraries and work well with the rest of JAX. Similar to Sonnet modules, Haiku modules are Python objects that hold references to their own parameters, other modules, and methods that apply functions on user inputs. -
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Hy
A dialect of Lisp that's embedded in Python
...As in other Lisps, the value of a simplistic syntax is that it facilitates Lisp’s signature feature, metaprogramming through macros, which are functions that manipulate code objects at compile-time to produce new code objects, which are then executed as if they had been part of the original code. -
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dateutil
Useful extensions to the standard Python datetime features
The dateutil module provides powerful extensions to the standard date time module, available in Python. dateutil can be installed from PyPI using pip (note that the package name is different from the importable name). -
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django-prometheus
Export Django monitoring metrics for Prometheus.io
...This is safe to do on existing models (it does not require a migration). Note that the exported metrics are counters of creations, modifications and deletions done in the current process. They are not gauges of the number of objects in the model. -
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PyExcelerate
Accelerated Excel XLSX Writing Library for Python 2/3
Accelerated Excel XLSX writing library for Python. PyExcelerate is a Python for writing Excel-compatible XLSX spreadsheet files, with an emphasis on speed. -
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Kubernetes Operator Pythonic Framework
A Python framework to write Kubernetes operators in just a few lines
Kopf —Kubernetes Operator Pythonic Framework— is a framework and a library to make Kubernetes operator's development easier, just in a few lines of Python code. The main goal is to bring the Domain-Driven Design to the infrastructure level, with Kubernetes being an orchestrator/database of the domain objects (custom resources), and the operators containing the domain logic (with no or minimal infrastructure logic). The project was originally started as zalando-incubator/kopf in March 2019, and then forked as nolar/kopf in August 2020: but it is the same codebase, the same packages, the same developer(s). A full-featured operator in just 2 files: a Dockerfile + a Python file (*). ... -
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Werkzeug
The comprehensive WSGI web application library
...Includes an interactive debugger that allows inspecting stack traces and source code in the browser with an interactive interpreter for any frame in the stack. Includes a full-featured request object with objects to interact with headers, query args, form data, files, and cookies. Includes a response object that can wrap other WSGI applications and handle streaming data. Includes a routing system for matching URLs to endpoints and generating URLs for endpoints, with an extensible system for capturing variables from URLs. Includes HTTP utilities to handle entity tags, cache control, dates, user agents, cookies, files, and more. -
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Positron
Positron, a next-generation data science IDE
Positron is a next-generation integrated development environment (IDE) created by Posit PBC (formerly RStudio Inc) specifically tailored for data science workflows in Python, R, and multi-language ecosystems. It aims to unify exploratory data analysis, production code, and data-app authoring in a single environment so that data scientists move from “question → insight → application” without switching tools. Built on the open-source Code-OSS foundation, Positron provides a familiar coding... -
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The Falcon Web Framework
The no-nonsense REST API and microservices framework
...Falcon cuts to the chase with a clean design that embraces HTTP and the REST architectural style. Highly optimized, extensible code base. Easy access to headers and bodies through request and response objects. DRY request processing via middleware components and hooks. Strict adherence to RFCs. Idiomatic HTTP error responses. Straightforward exception handling. Snappy testing with WSGI/ASGI helpers and mocks. CPython 3.5+ and PyPy 3.5+ support. No reliance on magic globals for routing and state management. Stable interfaces with an emphasis on backward compatibility. ... -
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pydantic
Data parsing and validation using Python type hints
...Strings, bytes or floats will be coerced to ints if possible; otherwise an exception will be raised. name is inferred as a string from the provided default; because it has a default, it is not required. signup_ts is a datetime field which is not required (and takes the value None if it's not supplied). pydantic will process either a unix timestamp int (e.g. 1496498400) or a string representing the date & time. friends uses python's typing system, and requires a list of integers. As with id, integer-like objects will be converted to integers. -
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Flama
Fire up your models with the flame
Flama is a python library which establishes a standard framework for development and deployment of APIs with special focus on machine learning (ML). The main aim of the framework is to make ridiculously simple the deployment of ML APIs, simplifying (when possible) the entire process to a single line of code. The library builds on Starlette, and provides an easy-to-learn philosophy to speed up the building of highly performant GraphQL, REST and ML APIs. Besides, it comprises an ideal solution... -
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AWX
A web-based user interface built on top of Ansible
...To the extent possible, auto-detects API versions, available endpoints, and feature support across multiple versions of AWX. Potential uses include configuring and launching jobs/playbooks, checking on the status and output of job runs, and managing objects like organizations, users, teams, etc. -
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Python Fire
Automatically generate CLIs from absolutely any Python object
...It’s a really simple and easy way to create CLI in Python, and can also enable you to explore existing code or turn other people’s code into a CLI. Python Fire lets you call Fire on any Python object: be it functions, classes, objects, modules, lists-- you name it! It will help you develop as well as debug Python code, and make transitioning between Bash and Python a whole lot easier. -
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Superduper
Superduper: Integrate AI models and machine learning workflows
...It supports the latest technologies and techniques, including LLMs, vector-search, RAG, and multimodality as well as classical AI and ML paradigms. Developers may leverage Superduper by building compositional and declarative objects that out-source the details of deployment, orchestration versioning, and more to the Superduper engine. This allows developers to completely avoid implementing MLOps, ETL pipelines, model deployment, data migration, and synchronization. Using Superduper is simply "CAPE": Connect to your data, apply arbitrary AI to that data, package and reuse the application on arbitrary data, and execute AI-database queries and predictions on the resulting AI outputs and data. -
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Django Rules
Awesome Django authorization, without the database
...It can also be used as a standalone library in other contexts and frameworks. Versatile. Decorate callables to build complex graphs of predicates. Predicates can be any type of callable -- simple functions, lambdas, methods, callable class objects, partial functions, decorated functions, anything really. A good Django citizen. Seamless integration with Django views, templates and the Admin for testing for object-level permissions. Efficient and smart. No need to mess around with a database to figure out whether John really wrote that book. Simple. Dive in the code. You'll need 10 minutes to figure out how it works. ... -
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Graphene-Django
Integrate GraphQL into your Django project
...Graphene Django has a number of additional features that are designed to make working with Django easy. Our primary focus in this tutorial is to give a good understanding of how to connect models from Django ORM to Graphene object types. GraphQL presents your objects to the world as a graph structure rather than a more hierarchical structure to which you may be accustomed. In order to create this representation, Graphene needs to know about each type of object which will appear in the graph. -
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Unofficial TikTok API in Python
The Unofficial TikTok API Wrapper In Python
...On a video, this may look like this, although TikTok changes its structure from time to time so it's worth investigating the structure of the dictionary when you use this package. You'll probably need to use this beyond just for legacy support since not all attributes are parsed out and attached to the different objects. -
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Darts
A python library for easy manipulation and forecasting of time series
darts is a Python library for easy manipulation and forecasting of time series. It contains a variety of models, from classics such as ARIMA to deep neural networks. The models can all be used in the same way, using fit() and predict() functions, similar to scikit-learn. The library also makes it easy to backtest models, combine the predictions of several models, and take external data into account. Darts supports both univariate and multivariate time series and models. The ML-based models... -
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Union Pandera
Light-weight, flexible, expressive statistical data testing library
...Identify the critical points in your data pipeline, and validate data going in and out of them. Build confidence in the quality of your data by defining schemas for complex data objects.
