bug fix: missing images during evaluation #2570
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
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Outdated suggestions cannot be applied.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.
During the computation of benchmark scores, the train/test images are loaded from the assemblies file (predictions made by the user) using the train/test indices in the dataset documentation file. This isn't robust, as the order of images passed by the user might be different to the ones in the ground truth file.
This PR updates the code to use the ground truth training dataset file to obtain the paths of the training/test images to use for evaluation, and find those images in the assemblies file. If there are predictions for test images that are missing, a warning is raised a warning and evaluation is made as if no predictions are made for that image.
The same issue happened when computing OKS in DeepLabCut - missing predictions can lead to a shift in the indices. This has been fixed in
deeplabcut/pose_estimation_tensorflow/lib/crossvalutils.py.