Benchmark Function
Open
enhancement
- Dominant language
- Python
- Stars
- 388
- Forks
- 95
- Avg merge
- 54m
- Merged PRs (30d)
- 3
Description
Write a function to automatically benchmark models on a specific benchmark dataset.
- [] Landmark = 300w
- [] Face Box data = wider
- [] AU = disfa
- [] Emotion = affwild2 (brand new one)
Contributor guide
No contributing guide indexed for this repository
Research direction
Start by locating the existing model evaluation code and dataset loaders for Landmark, Face Box, AU, and Emotion tasks. Determine how each listed dataset is represented and how benchmark results are currently produced. Done means one function can run the requested model benchmarks on those datasets and report comparable results.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100