modelscope / modelscope/ms-swift
关于多图 grounding 的任务
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Description
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- I have searched existing issues, and this is a new question or discussion topic. / 我已经搜索过现有的 issues,确认这是一个新的问题与讨论。
Question Description / 问题描述
说明文档中有 关于 多图grounding任务数据 训练结构 的说明如下:
image_id: 通常用于多图grounding任务。该参数只有当bbox_type为'real'时生效,代表bbox对应的图片是第几张,用于缩放bbox。索引从0开始,默认全为第0张。image_id的数量需要和bbox的数量一致。例如:若bbox的长度为10,images的长度为2,那么image_id的长度需要是10,其值需要在{0, 1}集合内。
有2个问题:
1. 这个image_id 在给到模型训练的时候是怎么根据 id 0,1,2 和原始的图像列表 进行的对应
2. 推理的时候怎样正确解析。或者可以将每个box 和具体 输入的多张图的具体哪一张对应
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the multi-image grounding data documentation referenced in the issue, then trace how image_id is consumed during training and inference. Document how indices map to the input image list and how each bounding box is associated with its image; done means both questions have an unambiguous, reproducible answer.
Written by the indexing model from the issue text.
Assessment
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100