[fix] Deduplicate labels and recover from malformed bboxes #75
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Outdated suggestions cannot be applied.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.
Description
I was having some trouble importing my full dataset due to malformed bboxes so I added an exception handler to skip and move to the next image. Also, I noticed that duplicate bboxes were not being removed, so I added code to remove duplicates.
Type of Change
Bug fix (non-breaking change which fixes an issue)
New feature (non-breaking change which adds functionality)
Checklist:
The code follows the Python style guide.
Code and files are well organized.
All tests pass.
Licensing:
By submitting this pull request, I confirm that:
My contribution is made under the MIT License.
I have not included any code from questionable or non-compliant sources (GPL, AGPL, ... etc).
I understand that all contributions to this repository must comply with the MIT License, and I promise that my contributions do not violate this license.
I have not used any code or content from sources that conflict with the MIT License or are otherwise legally questionable.