Add standardized emotion output adapter for facial analysis#17
Open
aadi-joshi wants to merge 1 commit intoruxailab:mainfrom
Open
Add standardized emotion output adapter for facial analysis#17aadi-joshi wants to merge 1 commit intoruxailab:mainfrom
aadi-joshi wants to merge 1 commit intoruxailab:mainfrom
Conversation
This file contains hidden or 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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
This PR adds a small adapter that converts the facial emotion output from this API into the standardized schema proposed in the ruxailab sentiment-analysis-api repository. The facial API currently returns emotion percentages (Happy, Angry, etc). this adapter normalizes those values and produces a consistent structure that can be used alongside the standardized outputs for text and audio sentiment analysis.
Added:
normalization/schema.py
pydantic models for the standardized output structure
normalization/adapter.py
normalize_emotions() helper that converts the existing emotion percentages into the standardized format
tests/test_adapter.py
unit tests covering normalization logic, label mapping, edge cases, and schema validation
docs/standardized_output.md
short explanation of the adapter and example usage
All changes are additive and existing API endpoints are untouched.