Navigating the intricate world of computer vision can be daunting. With a plethora of tools available, such as DeepStream, OpenVino, PyTorch, and OpenCV, how do you decide which is the best fit for your project? Enter Savant, a game-changer in the realm of computer vision.
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Here’s a breakdown of why Savant should be on your radar:
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Performance Prowess: Savant, built on the foundation of DeepStream, offers speed that rivals it. While it might not be as swift as a custom-built solution on DeepStream, it’s certainly faster than a basic OpenCV or PyTorch setup.
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Universal Application: Whether you’re working on an edge device, a workstation, or in a data center, Savant’s pipelines function seamlessly across all platforms.
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Pythonic Approach: Savant offers a Python-first API, making it a breeze for developers familiar with Python tools and libraries.
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API-Centric with Ready Interfaces: Savant operates as an API-driven inference server, equipped with a versatile streaming protocol and an array of data adapters.
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Geared for Production: With its architecture rooted in containerization, Savant ensures smooth deployment in various environments. Plus, it comes with built-in OpenTelemetry support.
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Developer-Friendly Tools: Savant is crafted with developers in mind. From Docker integration to OpenTelemetry, it offers a suite of tools to streamline the development process.
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Effortless Integration: Savant’s adapters and protocols make it easy to integrate third-party tools and systems.
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OpenCV CUDA Support: Savant allows developers to perform operations on GPU-allocated images using OpenCV CUDA, eliminating the need to transfer frames to CPU memory.
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Comprehensive Samples: Savant’s repository is rich with samples and demos, providing a solid foundation for developers to build upon.
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Engaged Developer Community: With an active Discord community, Savant ensures that developers have a platform to share insights, seek help, and contribute to the ecosystem.
Read the full article in the Savant blog.