Stars
DSPy: The framework for programming—not prompting—language models
A tool for retrieving gacha history link on Android devices
Multi-platform, free open source software for visualization and image computing.
idiap / coqui-ai-TTS
Forked from coqui-ai/TTS🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
Huawei UniVPN Client Docker Container with VNC/SOCKS/HTTP Access. 华为 UniVPN 客户端 Docker 容器 (带 VNC/SOCKS/HTTP 访问)
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
《Hello 算法》：动画图解、一键运行的数据结构与算法教程。支持简中、繁中、English、日本語，提供 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 等代码实现
Simultaneous Nuclear Instance Segmentation and Classification in H&E Histology Images.
QuPath extension for Segment Anything Model (SAM)
Large (GB and above) scale microscopic image computing using 3D Slicer
A playbook for systematically maximizing the performance of deep learning models.
Tool for robust segmentation of >100 important anatomical structures in CT and MR images
TODS: An Automated Time-series Outlier Detection System
A curated list of temporal action localization/detection and related area (e.g. temporal action proposal) resources.
[TIP 2022] End-to-end Temporal Action Detection with Transformer
Real-time video and audio processing on Streamlit
🐸STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
Many studies have shown that the performance on deep learning is significantly affected by volume of training data. The MedicalNet project provides a series of 3D-ResNet pre-trained models and rela…
SOTA medical image segmentation methods based on various challenges
Learnable Oriented-Derivative Network for Polyp Segmentation
MICCAI 2020 : Adaptive Context Selection for Polyp Segmentation (Pytorch implementation).
Review in Deep Learning for Polyp Detection and Classification in Colonoscopy (https://doi.org/10.1016/j.neucom.2020.02.123).
Codes for MICCAI2021 paper "Shallow Attention Network for Polyp Segmentation"