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v0.2.0

08 Aug 01:54
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What's Changed

This version of Ianvs supports the following functions of unstructured lifelong learning:

  • Support lifelong learning throughout the entire lifecycle, including task definition, task assignment, unknown task recognition, and unknown task handling, among other modules, with each module being decoupled.
    • Support unknown task recognition and provide corresponding usage examples based on semantic segmentation tasks in this example.
    • Support multi-task joint inference and provide corresponding usage examples based on object detection tasks in this example.
  • Provide classic lifelong learning testing metrics, and support for visualizing test results.
    • Support lifelong learning system metrics such as BWT and FWT.
    • Support visualization of lifelong learning results.
  • Provide real-world datasets and rich examples for lifelong learning testing, to better evaluate the effectiveness of lifelong learning algorithms in real environments.
    • Provide cloud-robotics datasets in this website.
    • Provide cloud-robotics semantic segmentation examples in this example.

The detailed pull requests are as follows:

  • Lifelong learning feature and example by @JimmyYang20 in #28
  • Edge Intelligence Benchmark for Edge-Cloud Collaborative Lifelong Detection by @iszhyang in #39
  • Unknown Task Recognition Algorithm Reproduction by @Frank-lilinjie in #42
  • Multi-task Joint Inference by @shifan-Z in #44
  • Cloud-Robotic AI Benchmarking for Edge-cloud Collaborative Lifelong Learning by @hsj576 in #65
  • Lifelong learning system metrics BWT and FWT by @hsj576 in #67
  • Proposal for Cloud-robotics dataset by @hsj576 in #69

New Contributors

Full Changelog: v0.1.0...v0.2.0

Ianvs v0.1.0 release

12 Jul 08:33
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Release the Ianvs distributed synergy AI benchmarking framework.

  • Release test environment management and configuration.
  • Release test case management and configuration.
  • Release test story management and configuration.
  • Release the open-source test case generation tool: Use hyperparameter enumeration to fill in one configuration file to generate multiple test cases.

Release the PCB-AoI public dataset.

  • Release the PCB-AoI public dataset, its corresponding preprocessing, and baseline algorithm projects. Ianvs is the first open-source site for that dataset.

Support two new paradigms in test environments and test cases.

  • Test environments and test cases that support the single-task learning paradigm.
  • Test environments and test cases that support the incremental learning paradigm.

Release PCB-AoI benchmark cases based on the two new paradigms.

  • Release PCB-AoI benchmark cases based on single-task learning, including leaderboards and test reports.
  • Release PCB-AoI benchmark cases based on incremental learning, including leaderboards and test reports.

Details as following

  • Add ianvs core code by @JimmyYang20 in #1
  • Add Ianvs examples and comments. by @jaypume in #2
  • Add documentations by @MooreZheng in #3
  • Revise key docs like the home page, setup and contribution by @MooreZheng in #9
  • Add fossa analysis in the github workflow by @JimmyYang20 in #10
  • Modify the hyperlinks of ci and license scan by @JimmyYang20 in #11
  • Add templates of lifelong learning and mutli-edge-inference by @JimmyYang20 in #12
  • Add a deploy ianvs method in quick-start.md by @JimmyYang20 in #31
  • Add Proposal for Edge Intelligence Benchmark for Edge-Cloud Collaborative Lifelong Detection by @iszhyang in #35
  • Add codes of Edge Intelligence Benchmark for Edge-Cloud Collaborative Lifelong Detection by @iszhyang in #39
  • Add pedestrian tracking example. by @yqhok1 in #36
  • Modify workflow platform by @luosiqi in #46
  • Add new application of singletasklearning: segmentation of cityscapes by @luosiqi in #47
  • Fix document and example resources by @JimmyYang20 in #5
  • Fix hyperlinks in documentation by @JimmyYang20 in #6
  • Fix quick start doc by @JimmyYang20 in #7

New Contributors

Full Changelog: https://github.com/kubeedge/ianvs/commits/v0.1.0