drivendataorg / drivendataorg/zamba
Attach image transforms to model
- Dominant language
- Python
- Stars
- 163
- Forks
- 40
- PR merge metrics
- No merged PRs in 30d
Description
Right now, some of the image transforms are hard coded. The transform configuration should be attached to the model, so model-dependent things like normalization come through with the model itself.
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_Copied from [drivendataorg/zamba-wildlabs #67](https://github.com/drivendataorg/zamba-wildlabs/issues/67)_
Contributor guide
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Research direction
Start by locating the hard-coded image transforms and the model construction or configuration entry points. Trace how normalization and other model-dependent settings are currently selected. Done means the transform configuration travels with the model rather than being maintained separately, with existing image-processing behavior preserved.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Refactor
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100