Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Annotation format for bbox is not uniform in training set #4

Open
YiweiLi4 opened this issue Apr 22, 2021 · 1 comment
Open

Annotation format for bbox is not uniform in training set #4

YiweiLi4 opened this issue Apr 22, 2021 · 1 comment

Comments

@YiweiLi4
Copy link

Hello,

I found that most bbox annotations are ordered as [x1, y1, width, height], but some images seem to have the annotation like [x1, x2, y1, y2], like "HICO_train2015_00012054.jpg" below. How can I standardize these annotations?

image

Thanks for your time!
@YiweiLi4 YiweiLi4 changed the title Annotation format for bbox are not uniform in training set Annotation format for bbox is not uniform in training set Apr 22, 2021
YiweiLi4 added a commit to YiweiLi4/tensorbay-python-sdk that referenced this issue Apr 22, 2021
@YiweiLi4
fix(opendataset): remove Classification and Box2D label in HalpeFullBody
66b0e89 
the label format of Box2D is not uniform in the dataset
issue link: Fang-Haoshu/Halpe-FullBody#4

annotations for "hoi" in Classification label lack important
information
@YiweiLi4 YiweiLi4 mentioned this issue Apr 22, 2021
Merged
YiweiLi4 added a commit to YiweiLi4/tensorbay-python-sdk that referenced this issue Apr 22, 2021
@YiweiLi4
fix(opendataset): remove Classification and Box2D label in HalpeFullBody
89c7d4f 
the label format of Box2D is not uniform in the dataset
issue link: Fang-Haoshu/Halpe-FullBody#4

annotations for "hoi" in Classification label lack important
information

PR Closed: Graviti-AI#452
YiweiLi4 added a commit to Graviti-AI/tensorbay-python-sdk that referenced this issue Apr 22, 2021
@YiweiLi4
fix(opendataset): remove Classification and Box2D label in HalpeFullBody
14e657e 
the label format of Box2D is not uniform in the dataset
issue link: Fang-Haoshu/Halpe-FullBody#4

annotations for "hoi" in Classification label lack important
information

PR Closed: #452
linjiX pushed a commit to Graviti-AI/tensorbay-python-sdk that referenced this issue Apr 25, 2021
@YiweiLi4 @linjiX
fix(opendataset): remove Classification and Box2D label in HalpeFullBody
4e955f0 
the label format of Box2D is not uniform in the dataset
issue link: Fang-Haoshu/Halpe-FullBody#4

annotations for "hoi" in Classification label lack important
information

PR Closed: #452
linjiX pushed a commit to Graviti-AI/tensorbay-python-sdk that referenced this issue Apr 25, 2021
@YiweiLi4 @linjiX
fix(opendataset): remove Classification and Box2D label in HalpeFullBody
66c59f6 
the label format of Box2D is not uniform in the dataset
issue link: Fang-Haoshu/Halpe-FullBody#4

annotations for "hoi" in Classification label lack important
information

PR Closed: #452
@rex-yue-wu
Copy link

rex-yue-wu commented Mar 21, 2022 •
edited
Loading

Notice the same issue. A quick and dirty fix is to evaluate the quality of the two possible options, namely,

  • IoU(bbox_xywh, keypoint_min_bbox)
  • IoU(bbox_xyxy, keypoint_min_bbox)
    where bbox_xywh and bbox_xyxy are the two possible formats of the given bbox annotation, and keypoint_min_bbox is the minimum bounding box you may infer based on the given keypoints annotation.

Once both scores are computed, you can simply pick the one attaining better quality.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
None yet
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
2 participants
@rex-yue-wu @YiweiLi4