Parskatt / RoMa

[CVPR 2024] RoMa: Robust Dense Feature Matching; RoMa is the robust dense feature matcher capable of estimating pixel-dense warps and reliable certainties for almost any image pair.
https://parskatt.github.io/RoMa/
MIT License
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How many steps to train roma_outdoor? #87

Closed Zhimin00 closed 4 days ago

Zhimin00 commented 4 days ago

I notice the length of megadepth_train is 9,903,321, and the number of total training steps is (32*250,000) = 8,000,000

megadepth_train1 = mega.build_scenes( split="train_loftr", min_overlap=0.01, shake_t=32, use_horizontal_flip_aug = use_horizontal_flip_aug, rot_prob = rot_prob, ht=h,wt=w, ) megadepth_train2 = mega.build_scenes( split="train_loftr", min_overlap=0.35, shake_t=32, use_horizontal_flip_aug = use_horizontal_flip_aug, rot_prob = rot_prob, ht=h,wt=w, ) megadepth_train = ConcatDataset(megadepth_train1 + megadepth_train2)

Parskatt commented 4 days ago

Yes, that's correct.

Zhimin00 commented 4 days ago

Why do you use less steps than the whole training dataset?

Parskatt commented 4 days ago

Yes, it doesnt matter much, as dataset is pairs, not images.

Zhimin00 commented 4 days ago

Thank you for your reply.