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Simple, Elegant, Typed Argument Parsing with argparse
WinBtrfs - an open-source btrfs driver for Windows
Machine Learning-Enabled ROS Docker Images
Official code for the paper Graph-level Representation Learning with Joint-Embedding Predictive Architectures published in Transactions on Machine Learning Research (TMLR)
Network-wide ads & trackers blocking DNS server
View HTTP/HTTPS requests made by any Linux program
Real-time, Fully Local Speech-to-Text and Speaker Diarization. FastAPI Server & Web Interface
Tiled scrollable window management for GNOME Shell
💾 Unstorage provides an async Key-Value storage API with conventional features like multi driver mounting, watching and working with metadata, dozens of built-in drivers and a tiny core.
Moonlight port for Xbox One/Series Family of Console
PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)
Convert raster and vector geospatial data to various formats and coordinate systems entirely in the browser.
Count lines of code in a GitHub repository
Telegram bot nodes for node-red.
PyTorch implementation of Graph Matching Networks, e.g., Graph Matching with Bi-level Noisy Correspondence (COMMON, ICCV 2023), Graph Matching Networks for Learning the Similarity of Graph Structur…
Depth Pro: Sharp Monocular Metric Depth in Less Than a Second.
VSCode extension for simple XPath queries
A middleware that reads, converts and publishes metrics from various sources to various targets
A scikit-learn compatible neural network library that wraps PyTorch
Zigbee 🐝 to MQTT bridge 🌉, get rid of your proprietary Zigbee bridges 🔨
A Github-contributions like visualisation for Strava activities
Hello eBPF world! Hello Java world! Let's discover eBPF together and write Java user-land library along the way.
GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats.
Berechnung mehrere Kritikalitätsmetriken zur Bewertung von Szenen und Szenarien.
Implementation of the Paper "Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning" by Robin Winter, Frank Noe and Djork-Arne Clevert.
