This repository has been archived by the owner on Jul 1, 2024. It is now read-only.
Implement resize and train XRayVideo A/V with only resizing #796
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Summary:
We want to check whether training XRayVideo with simply video resizing (in addition to other existing transformation like horizontal flipping and normalization) without random corp is sufficient.
The resize dimension is used as 224*224.
workflow: f362077622 (Note: in the workflow
fcc_mvit_dataset_v4p2_arkc.yaml
is used which I renamed tofcc_mvit_dataset_v4p2_onlyresize.yaml
in this diff.)As can be seen, the validation MAP goes to around .422 as opposed to 0.46 when random resized crop is used (f355567669) and rest of the configuration is kept the same. Hence, it is better to keep random resized crop.
Differential Revision: D38522980