tech4ai/t4ai-signature-detect-server

This project provides a pipeline for deploying and performing inference with the YOLOv8 object detection model using the Triton Inference Server. It supports integration with local systems, Docker-based setups, or Google Cloud’s Vertex AI. The repository includes scripts for automated deployment, benchmarks and GUI inference.

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Emerging

This project helps MLOps engineers, data scientists, and machine learning developers efficiently deploy and run object detection models like YOLOv8. It takes raw images as input and outputs identified objects within those images, complete with bounding boxes. You'd use this to move trained object detection models from development into a production environment, ensuring fast and scalable inference.

No commits in the last 6 months.

Use this if you need to deploy an object detection model for high-performance inference, whether on your local system, via Docker, or on Google Cloud's Vertex AI.

Not ideal if you are looking for a tool to train new object detection models or if your primary goal is basic, low-volume inference without scalability needs.

machine-learning-deployment object-detection model-serving computer-vision MLOps
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 14 / 25

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Stars

22

Forks

4

Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Oct 10, 2025

Commits (30d)

0

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