Comments (1)
hi,The shape of rgb (srcvec) I entered is (1024,3), and the shape of gt (tar_vec) is also (1024,3). I used the parameter M=10 (repeat_time=10), patch_ Height=32, patch_ Width=32. My understanding is to transform the rgb predicted by my network into an image and gt into an image. After 10 for loops, each loop is in a random order, and the shape of both images is (1, 3, 32,320). Then, calculate s3im based on these two images? Is my understanding correct?
Yes, that is how S3IM works.
from s3im-neural-fields.
Related Issues (12)
- How do batch size come into play in the S3IM formulation HOT 4
- How to make sure s3im input matching the patch size HOT 2
- How can I obtain data?if I use my images how can I configure them?
- Unable to converge
- Issue when trying to run DVGO train_replica HOT 4
- About the virtual patch HOT 2
- About the use of S3IM. HOT 1
- how to use the s3im function on other training processes HOT 3
- How should I set the weights?? HOT 3
- Reproducing results HOT 3
- Scenarios for the use of s3im loss HOT 3
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from s3im-neural-fields.