1.datalab-to / indra
1M param OCR model - runs on CPU, 15x faster than tesseract, close to 1B+ param models in accuracy
Ranked by Attention Score: stars gained over the last 7 complete days
21 repositories by Attention Score · Oct 27, 2026 – Nov 2, 2026 (UTC)
1M param OCR model - runs on CPU, 15x faster than tesseract, close to 1B+ param models in accuracy
Speech-to-text, text-to-speech, speaker diarization, speech enhancement, source separation, and VAD using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android, iOS, HarmonyOS, Raspberry Pi, RISC-V, RK NPU, Axera NPU, Ascend NPU, x86_64 servers, websocket server/client, support 12 programming languages
Learn to sing the songs you love. A free, open-source singing trainer for Mac that listens to the music you play.
Open source real-time translation app for Android that runs locally
Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.
LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot.
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Visualizer for neural network, deep learning and machine learning models
Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
ncnn is a high-performance neural network inference framework optimized for the mobile platform
Open standard for machine learning interoperability
免選字的注音輸入法:在本機用 Transformer 看前文選字。支援 Linux(Fcitx5/IBus)、macOS、Windows。
Fast and accurate AI powered file content types detection
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.
Simple and Distributed Machine Learning Python Library porting ML algorithms for Spark
Go package for computer vision using OpenCV 4 and beyond. Includes support for DNN, CUDA, OpenCV Contrib, and OpenVINO.
Unified framework for building enterprise RAG pipelines with small, specialized models
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
onnx-go gives the ability to import a pre-trained neural network within Go without being linked to a framework or library.
PyTorch to Keras model convertor