code: complete eval pipeline (7 metrics + per-class + Wilcoxon) + Swin-UNet/TransUNet networks; remove backups/obsolete
1a18f22 verified | # Cache the dataset from the slow JuiceFS share to local RAID /data/temp for fast | |
| # training reads. Parallel per-dataset cp -a (preserves pannuke hard links), overlaps | |
| # JuiceFS small-file read latency. Run detached; log to /tmp/cache_data.log. | |
| SRC=/mnt/tidal-alsh-share2/dataset/qinshengqian/research/c3/NPJ-ACM/Data | |
| DST=/data/temp/NPJ-ACM/Data | |
| mkdir -p "$DST" | |
| echo "[start] $(date +%T)" | |
| for d in acdc_png busi cvc_clinicdb fives idridd_segmentation kvasir_seg \ | |
| medsegdb_isic2018 medsegdb_kits19 pannuke_semantic refuge2; do | |
| ( cp -a "$SRC/$d" "$DST/" && echo "done $d $(date +%T)" ) & | |
| done | |
| wait | |
| echo "CACHE_DONE $(date +%T)" | |