About dataset
hongh0 opened this issue · comments
Thanks for your great work.
I would like to test GaussianObject with our own dataset. Can you provide a script to handle our own dataset?
Thank you for this magnificent masterpiece.
Currently, the datasets fed into this project are all massive, with each dataset being approximately 2GB or more.
However, according to the paper, only four images should be utilized.
The original intention of this paper was to simplify the input process, yet there is a lack of corresponding scripts for the preliminary data preparation and processing.
I am eagerly looking forward to the open-sourcing of these components.
Sorry for the delayed response to your issue, and appreciate your patience. To handle your own data, we recommend using COLMAP for generating poses. For estimating object masks, you can refer to SegAnyGAussians or SegmentAnything. Please let us know if you need further assistance or have more questions.
@GaussianObject Hi there I was wondering，if I have four images, those images are pretty sparse, and could not generate a pose estimation by COLMAP/SFM, how should I do in such situation.
Sorry for the delayed response to your issue, and appreciate your patience. To handle your own data, we recommend using COLMAP for generating poses. For estimating object masks, you can refer to SegAnyGAussians or SegmentAnything. Please let us know if you need further assistance or have more questions.
The article claims that a geometric shape (GS) can be generated with just four images, but in actual operation, to create a sparse point cloud, I only have photos from four perspectives. How can I use COLMAP to generate a .sparse file with such a limited number of images? Isn't this contradictory to the title of the article? The point clouds in the dataset are all generated from a multitude of photographs. I am hoping for some guidance on how to use this project with only a few images