Python package built to ease deep learning on graph, on top of existing DL frameworks.
- deep-learning
- graph-neural-networks
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Python package built to ease deep learning on graph, on top of existing DL frameworks.
Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
Automated CI toolchain to produce precompiled opencv-python, opencv-python-headless, opencv-contrib-python and opencv-contrib-python-headless packages.
Stop configuring your AI stack. Start using it. One command brings a complete pre-wired LLM stack with hundreds of services to explore.
This package contains deep learning models and related scripts for RoseTTAFold
Earth observation processing framework for machine learning in Python
Python package for graph statistics
Python package for graph neural networks in chemistry and biology
ROS package for dynamic obstacle avoidance for ground robots trained with deep RL
Python package for stacking (machine learning technique)
Light-weight camera LiDAR calibration package for ROS using OpenCV and PCL (PnP + LM optimization)
Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch
ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark Suite
把 Codex imagegen 的工作流与提示词库带到任意智能体;支持 npm/pnpm 一键安装、配套 skill、独立 API 与 Qwen-Image 兼容网关。
Python package implementing ML feature engineering and pre-processing for polars or pandas dataframes.
HistoClean is a tool for the preprocessing and augmentation of images used in deep learning models. This easy to use application brings together the most popular image processing packages from across the python universe, meaning no more looking at documentation! HistoClean provides real time feedback to augmentations and preprocessing options. This allows users to evaluate their steps before implementation.
A lightweight Python package for teaching computational methods through art history. Extract and analyze artist-specific works from WikiArt with built-in visualizations. Designed for digital humanities and computational design courses. Features genre/style analysis, matplotlib integration, and pedagogical clarity over algorithmic complexity.