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John Charankattu (johncf)

johncf

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John Charankattu's starred repositories

delvewheel

Self-contained Python wheels for Windows

Language:PythonLicense:MITStargazers:120Issues:0Issues:0

hlg-tools

Tools for converting from HDR10 to HLG

Language:RustLicense:MPL-2.0Stargazers:85Issues:0Issues:0

heif-hdrgainmap-decode

Convert HDR photos taken by iPhone 12 (or later) to regular HDR images

Language:PythonStargazers:43Issues:0Issues:0

cryptomator

Multi-platform transparent client-side encryption of your files in the cloud

Language:JavaLicense:GPL-3.0Stargazers:11653Issues:0Issues:0

DisTrO

Distributed Training Over-The-Internet

Stargazers:637Issues:0Issues:0

parler-tts

Inference and training library for high-quality TTS models.

Language:PythonLicense:Apache-2.0Stargazers:4331Issues:0Issues:0

instaloader

Download pictures (or videos) along with their captions and other metadata from Instagram.

Language:PythonLicense:MITStargazers:8645Issues:0Issues:0

open_clip

An open source implementation of CLIP.

Language:PythonLicense:NOASSERTIONStargazers:9974Issues:0Issues:0

stable-fast-3d

SF3D: Stable Fast 3D Mesh Reconstruction with UV-unwrapping and Illumination Disentanglement

Language:PythonLicense:NOASSERTIONStargazers:1067Issues:0Issues:0

ONNX-SAM2-Segment-Anything

Python scripts for the Segment Anythin 2 (SAM2) model in ONNX

Language:PythonLicense:MITStargazers:141Issues:0Issues:0

sam2

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:11468Issues:0Issues:0

MLAlgorithms

Minimal and clean examples of machine learning algorithms implementations

Language:PythonLicense:MITStargazers:10715Issues:0Issues:0

ray

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Language:PythonLicense:Apache-2.0Stargazers:33368Issues:0Issues:0

Great-Deep-Learning-Tutorials

A Great Collection of Deep Learning Tutorials and Repositories

License:MITStargazers:202Issues:0Issues:0

tortoise-tts

A multi-voice TTS system trained with an emphasis on quality

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:13042Issues:0Issues:0

open-speech-corpora

💎 A list of accessible speech corpora for ASR, TTS, and other Speech Technologies

License:MITStargazers:1268Issues:0Issues:0

jupyterlite

Wasm powered Jupyter running in the browser 💡

Language:TypeScriptLicense:BSD-3-ClauseStargazers:3864Issues:0Issues:0

LLM101n

LLM101n: Let's build a Storyteller

Stargazers:29259Issues:0Issues:0

Depth-Anything-V2

[NeurIPS 2024] Depth Anything V2. A More Capable Foundation Model for Monocular Depth Estimation

Language:PythonLicense:Apache-2.0Stargazers:3478Issues:0Issues:0

tailscale

The easiest, most secure way to use WireGuard and 2FA.

Language:GoLicense:BSD-3-ClauseStargazers:18888Issues:0Issues:0

restic

Fast, secure, efficient backup program

Language:GoLicense:BSD-2-ClauseStargazers:26058Issues:0Issues:0

mypyc

Compile type annotated Python to fast C extensions

Stargazers:1746Issues:0Issues:0

tagspaces

TagSpaces is an offline, open source, document manager with tagging support

Language:TypeScriptLicense:AGPL-3.0Stargazers:3696Issues:0Issues:0

etherpad-lite

Etherpad: A modern really-real-time collaborative document editor.

Language:TypeScriptLicense:Apache-2.0Stargazers:16543Issues:0Issues:0

dora

DORA (Dataflow-Oriented Robotic Architecture) is middleware designed to streamline and simplify the creation of AI-based robotic applications. It offers low latency, composable, and distributed dataflow capabilities. Applications are modeled as directed graphs, also referred to as pipelines.

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lerobot

🤗 LeRobot: Making AI for Robotics more accessible with end-to-end learning

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NoiseTorch

Real-time microphone noise suppression on Linux.

Language:GoLicense:NOASSERTIONStargazers:9276Issues:0Issues:0

notebooks

Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.

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cosmic-epoch

Next generation Cosmic desktop environment

Language:JustStargazers:2962Issues:0Issues:0

marker

Convert PDF to markdown quickly with high accuracy

Language:PythonLicense:GPL-3.0Stargazers:16903Issues:0Issues:0