UMass-Rescue / UMass-Rescue/RescueBox
Benchmarking age_and_gender detection plugin on larger dataset + exploring fine-tuning
Open
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 6
- Forks
- 15
- Avg merge
- 14h 42m
- Merged PRs (30d)
- 7
Description
This issue will comprise of:
- Creating a script to scrape and pull images of various edge cases: adults with neurodevelopmental disorders that look like children, children with with precocious puberty who develop secondary sex characteristics much earlier, etc. that might be missing from typical datasets but important in this scenario to fine tune the model specifically.
- Creating a CSV with links to each image and creating a structured test folder
- Testing on existing endpoint: age_and_gender_detection and documenting the baseline results
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the existing age_and_gender_detection endpoint and the repository's current dataset or test structure. Create a scraping script for the specified edge cases, a CSV of image links, and a structured test folder; run the endpoint on the larger dataset and document the baseline results. The issue does not name specific files, data sources, or evaluation criteria.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning, testing-qa
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 30/100