Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes
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Why the annotated keypoints are sometimes very small or huge? #78
As described here, I think the "keypoints.point_2d.x" or "keypoints.point_2d.y" should be in the range of 0 to 1 if x/y are inside the image.
However, I observe that sometimes those are extremely small or huge.
For example,
"~/bike/batch-11/5/annotation.pbdata"
has
https://github.com/google-research-datasets/Objectron/blob/c06a65165a18396e1e00091981fd1652875c97b5/objectron/dataset/graphics.py#L34-L40
As described here, I think the "keypoints.point_2d.x" or "keypoints.point_2d.y" should be in the range of 0 to 1 if x/y are inside the image. However, I observe that sometimes those are extremely small or huge.
For example,
"~/bike/batch-11/5/annotation.pbdata"
haswith extremely small x and y.