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English | 简体中文
Sedna is an edge-cloud synergy AI project incubated in KubeEdge SIG AI. Benefiting from the edge-cloud synergy capabilities provided by KubeEdge, Sedna can implement across edge-cloud collaborative training and collaborative inference capabilities, such as joint inference, incremental learning, federated learning, and lifelong learning. Sedna supports popular AI frameworks, such as TensorFlow, Pytorch, PaddlePaddle, MindSpore.
Sedna can simply enable edge-cloud synergy capabilities to existing training and inference scripts, bringing the benefits of reducing costs, improving model performance, and protecting data privacy.
Sedna has the following features:
Provide the edge-cloud synergy AI framework.
Provide edge-cloud synergy training and inference frameworks.
Compatibility
Sedna consists of the following components:
Documentation is located on readthedoc.io. These documents can help you understand Sedna better.
Follow the Sedna installation document to install Sedna.
Example1:Using Joint Inference Service in Helmet Detection Scenario.
Example2:Using Incremental Learning Job in Helmet Detection Scenario.
Example3:Using Federated Learning Job in Surface Defect Detection Scenario.
Example4:Using Federated Learning Job in YoLov5-based Object Detection.
Example5:Using Lifelong Learning Job in Thermal Comfort Prediction Scenario.
Example6:Using MultiEdge Inference Service to Track an Infected COVID-19 Carrier in Pandemic Scenarios.
Regular Community Meeting:
Resources:
If you have questions, feel free to reach out to us in the following ways:
If you're interested in being a contributor and want to get involved in developing the Sedna code, please see CONTRIBUTING for details on submitting patches and the contribution workflow.
Sedna is under the Apache 2.0 license. See the LICENSE file for details.
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