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[upgrade] Cellpose: identify current Wave-container version pin vs upstream v4.1.1 #166

Description

@an-altosian

Current state

  • Pinned: container community.wave.seqera.io/library/python_pip_cellpose:fdf7a8c3a305a26e at modules/nf-core/cellpose/main.nf:9
  • Modules: modules/nf-core/cellpose
  • Pipeline modes: image (when --method cellpose, the default)

Latest upstream

Investigation needed

  1. What cellpose version is fdf7a8c3a305a26e? The Wave container hash doesn't reveal the underlying pip-installed cellpose version. Need to either:
    • Decode by pulling the container and running cellpose --version
    • Look at the Wave build manifest, or
    • Trace the original Seqera Wave recipe
  2. Are we on v3 or v4? v3 → v4 had architectural changes (single-model cyto3 instead of separate models). If we're on v3, this is a substantial test surface; if already v4, a minor bump.
  3. Behavioral compatibility of our existing args (--flow_threshold 0, --batch_size 1) at the latest version.

Migration plan

  • Decode the Wave container to determine the current cellpose version
  • Review v4.1.1 changelog for behavioral changes affecting --flow_threshold / --batch_size / model selection
  • If a minor bump (within v4.x), update the Wave container; if v3 → v4, plan a model-switch and re-benchmark
  • Re-run image-mode tests on a Xenium v1 bundle to confirm segmentation quality matches

Risks

  • v3 → v4 architectural change is a notable test surface (different default models, different argument defaults)
  • GPU container variant: nf-core/cellpose may have separate CPU/GPU containers — bump consistently
  • Atera relevance: image mode is touched by Atera workflow but blocked by XR (out of scope per user direction); this upgrade primarily helps Xenium v1 image mode

Cross-links

  • Triggered by: Atera compatibility session 2026-05-28 (broader tool inventory check).

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