Conflicting Instructions Between Tutorial and Journal Article
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Assessment
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Newbie friendliness
- 45/100
- Issue type
- Documentation
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- python
- Domain
- computer-vision, machine-learning
Research direction
Start by comparing the tutorial's mpp handling with the journal article's preprocessing statement. Determine which guidance applies to imaging mass cytometry inputs, then update the relevant tutorial or documentation so the required preprocessing and mpp parameter usage are unambiguous; done means users can follow one consistent workflow.
Written by the indexing model from the issue text.
Description
Read Me:
Image preprocessing: See the paper for details.
Journal article:
all datasets were resampled to 0.5 microns per pixel (
mpp) using nearest-neighbor interpolation and without anti-aliasing.
Tutorial:
mpp = ds["image"].attrs["mpp"]
deepcell_types.predict(img, mask, chnames, mpp, model_name=model, device_num=device, num_workers=num_data_loader_threads)
So, should one up-sample their imaging mass cytometry image or should they specify mpp as a parameter? Surely not both.
- Dominant language
- Python
- Stars
- 10
- Forks
- 4
- PR merge metrics
- No merged PRs in 30d
Getting set up
- Ships a Dockerfile or Docker Compose file
- No pull request template
- No contributing 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.
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