AllenNeuralDynamics / AllenNeuralDynamics/aind_data_outreach
compile training-relevant exaspim datasets
- 主要语言
- Python
- 星标
- 0
- 派生
- 0
- PR 合并指标
- 30 天内没有已合并 PR
描述
To better coordinate work on training models for reconstruction correction predictions, we want to create combined data assets and/or DocDB queries that point to all available samples with complete reconstructions from the v2 scope (and possibly also the v1 scope separately). This will likely involve some updates to the metadata, and will need support from Peter and maybe Anna.
not strictly for the NMCP but that's the closest milestone.
贡献指南
这个仓库没有索引到贡献指南
调研方向
Start by reviewing the available DocDB queries and metadata for complete reconstructions in the v2 scope, then check whether v1 should be handled separately. Coordinate with Peter and possibly Anna on the required metadata and training assets; done means all in-scope samples are discoverable through combined assets and/or queries.
由索引模型根据 Issue 内容生成。
评估
- 技术栈
- python
- 领域
- data-engineering, databases
- Issue 类型
- 功能
- 难度
- 5/5
- 预计耗时
- 一周以上
- 活跃度
- 活跃
- 描述清晰度
- 需要澄清
- 新手友好度
- 25/100