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Problem on data preparation #5
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Hi! Thanks for your interest! Since the procedure of data preparation is a little complicated, we still need some time to release the final document. We provide the draft here, hope it is helpful for you. Welcome for your feedback, which can be helpful for us to improve the document! Before preparing your own data, you should checkout the dataset module carefully. Overall, you need to place your data with the following structure and create a corresponding config file.
ImagesYou should place RGB images in Intrinsic parametersSave the Camera posesYou can solve camera poses with COLMAP or other tools you like. Then you need to normalize the camera poses and modify some configs to ensure that:
Save the normalized poses as COLMAP depth mapsYou need to run sparse and dense reconstruction of COLMAP first. Please refer to this instruction if you want to use known camera poses. After dense reconstruction, you can obtain depth prediction for each view. However, the depth predictions can be noisy, so we recommend you to run fusion first to filter out most noises. Since original COLMAP does not have fusion mask for each view, you need to compile and run this customized version, which is used in NerfingMVS. Semantic predictionsYou need to run 2D semantic segmentations to generate semantic predictions from images. We will upload our trained model and inference code soon. |
Thanks for your reply. |
We just extract them from |
Thank you very much! |
Hi, thanks for your wonderful work!
I woud like to train on the new recorded sequences. so I wonder when the 'Data preparation' will be published?
Looking forward to your early reply.
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