chore(workflow): gres GPU request, ignore runtime dirs, example config

.gitignore

@@ -7,3 +7,5 @@ build/
 site/
 .pytest_cache/
 *.log
+.snakemake/
+.pixi/

workflow/config/config.yaml

@@ -12,7 +12,7 @@ work_dir: "/path/to/results" # everything is written under here
 #   image.zarr/labels/<name>/  — the segmentation (multi-scale), in the image
 
 # ---- conversion -------------------------------------------------------------
-reuse_pyramid: true # for .ims: copy its own pyramid (fast); else rebuild
+reuse_pyramid: false # for .ims: copy its own pyramid (fast); else rebuild
 convert_chunks: null # null → patchworks' bounded auto chunks; or [c,z,y,x]
 shard: false # true → pack chunks into shards (zarr v3; fewer files)
 # Re-running reuses an existing image.zarr automatically (skips conversion).
@@ -30,9 +30,9 @@ empty_threshold: null # null → Otsu; or a number
 
 # ---- segmentation -----------------------------------------------------------
 method: "cellpose" # "cellpose" (GPU) or "threshold" (simple, no GPU; testing)
-label_name: "cellpose"
+label_name: "cellpose_labels"
 cellpose:
-  model: "cyto3"
+  model: "nuclei"
   diameter: 30
   do_3D: true
   gpu: true

workflow/profile/slurm/config.yaml

@@ -33,11 +33,14 @@ set-resources:
     mem_mb: 32000
     runtime: 120
   segment:
-    # one GPU per tile — this is what spreads Cellpose across GPUs
+    # one GPU per tile — this is what spreads Cellpose across GPUs.
+    # Use the plugin's native `gres` resource → emits --gres=gpu:1, which is
+    # how scicore binds a CUDA device. (The `gpu:` resource emits --gpus and
+    # leaves the job without a device.)
     slurm_partition: "rtx4090"
-    gpu: 1
+    gres: "gpu:1"
     qos: "rtx4090-6hours" # scicore: <partition>-<duration> QOS
-    mem_mb: 32000 # plenty — a tile used ~1G; the failure was a Python error
+    mem_mb: 32000 # plenty — a tile used ~1G
     cpus_per_task: 4
     runtime: 360 # 6 hours — must match the QOS, NOT 120 (=2h → killed early)
   merge: