jolibrain/deepdetect

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

2551 stars · 546 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

DeepDetect is an open-source deep learning runtime, CLI, and REST server written in C++ for training and inference across images, text, tabular data, and time series. It supports PyTorch, TensorRT, and other backends, with a web platform UI and Docker-based deployment for CPU and GPU.

Use cases

• serve object detection models over a REST API
• train and run image segmentation models
• deploy deep learning inference on GPU with TensorRT
• classify images and text via a single API
• run predictions on tabular CSV and time-series data
• manage model training jobs and repositories from a CLI
• self-host a deep learning server with Docker

When to choose

• you need a production-ready REST server for model training and inference
• you want one API surface for detection, segmentation, classification, and tabular tasks
• you need GPU-accelerated serving with TensorRT or PyTorch on Linux
• you prefer a self-hosted, C++-fast alternative to managed ML serving

When to avoid

• you need a pure Python training framework with full ecosystem flexibility
• you only want lightweight experimentation in notebooks without a server
• you require Windows-native GPU serving or non-Linux production targets
• you need the latest cutting-edge model architectures immediately after release

Facets

service · maturity active

machine-learning deep-learning llm-inference image-processing http-server api-framework cli gpu-computing deep-learning machine-learning computer-vision apis developer-tools python cpp cross-platform self-hosted rest-api object-detection image-segmentation image-classification tensorrt pytorch model-serving training inference time-series ocr natural-language-processing linux docker gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="jolibrain/deepdetect")