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An opinionated list of awesome Python frameworks, libraries, software and resources.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
A natural language interface for computers
Streamlit — A faster way to build and share data apps.
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Python packaging and dependency management made easy
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
The fundamental package for scientific computing with Python.
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Faster Whisper transcription with CTranslate2
A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support
FauxPilot - an open-source alternative to GitHub Copilot server
Python GUIs for Humans! PySimpleGUI is the top-rated Python application development environment. Launched in 2018 and actively developed, maintained, and supported in 2024. Transforms tkinter, Qt, …
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image …
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
Lark is a parsing toolkit for Python, built with a focus on ergonomics, performance and modularity.
Simple Python style checker in one Python file
Automated CI toolchain to produce precompiled opencv-python, opencv-python-headless, opencv-contrib-python and opencv-contrib-python-headless packages.
Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.
Console user interface library for Python (official repo)
ETL, Analytics, Versioning for Unstructured Data
CUDA integration for Python, plus shiny features
A unified library of state-of-the-art model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. It compresses deep learning models for downstream deployment…