Delete eval.sh

eval.sh

@@ -1,70 +0,0 @@
-#!/bin/bash
-#SBATCH --job-name=frozenseg_eval
-#SBATCH --output=output/slurm/%j.run.out
-#SBATCH --error=output/slurm/%j.run.err
-#SBATCH --partition=gpu-a100
-#SBATCH --gres=gpu:1
-#SBATCH --cpus-per-task=16
-#SBATCH --comment=yhx_team
-export MODULEPATH="/opt/app/spack/share/spack/modules/linux-centos7-haswell:/opt/app/spack/share/spack/modules/linux-centos7-cascadelake:/usr/share/Modules/modulefiles:/etc/modulefiles:/opt/app/modulefiles"
-source /users/cx_xchen/.bashrc_12.1
-export DETECTRON2_DATASETS=/users/cx_xchen/DATASETS/
-export TORCH_DISTRIBUTED_DEBUG=DETAIL
-export OMP_NUM_THREADS=1
-export USE_SIMPLE_THREADED_LEVEL3=1
-conda activate frozenseg
-
-configs=(
-    # "configs/coco/frozenseg/convnext_large_eval_a847.yaml"
-    # "configs/coco/frozenseg/convnext_large_eval_ade20k.yaml"
-    # "configs/coco/frozenseg/convnext_large_eval_lvis.yaml"
-    # "configs/coco/frozenseg/convnext_large_eval_pas21.yaml"
-    "configs/coco/frozenseg/convnext_large_eval_pc459.yaml"
-    # "configs/coco/frozenseg/convnext_large_eval_cityscapes.yaml"
-    # "configs/coco/frozenseg/convnext_large_eval_coco.yaml"
-    # "configs/coco/frozenseg/convnext_large_eval_mapillary_vistas.yaml"
-    # configs/coco/frozenseg/convnext_large_eval_bdd_panop.yaml
-    # configs/coco/frozenseg/convnext_large_eval_bdd_sem.yaml
-)
-port=$((10000 + RANDOM % 50000))
-sam=vit_b
-path=output/ConvNext-L_${sam}_1x
-for config in "${configs[@]}"; do
-    python train_net.py --eval-only --num-gpus 1 --dist-url tcp://127.0.0.1:$port \
-        --config-file $config \
-        OUTPUT_DIR $path/$(basename "$config" .yaml) \
-        MODEL.WEIGHTS modified_model.pth \
-        MODEL.SAM_NAME vit_b \
-        MODEL.FROZEN_SEG.CLIP_PRETRAINED_WEIGHTS pretrained_checkpoint/models--laion--CLIP-convnext_large_d_320.laion2B-s29B-b131K-ft-soup/open_clip_pytorch_model.bin \
-        TEST.USE_SAM_MASKS False \
-        MODEL.FROZEN_SEG.GEOMETRIC_ENSEMBLE_BETA 0.6
-done
-
-########## with mask ensemble ########
-# for config in "${configs[@]}"; do
-#     python train_net.py --eval-only --num-gpus 1 --dist-url tcp://127.0.0.1:$port \
-#         --config-file $config \
-#         OUTPUT_DIR $path/w_maskEnsemble/$(basename "$config" .yaml) \
-#         MODEL.WEIGHTS $path/model_final.pth \
-#         MODEL.MASK_FORMER.SAM_QUERY_FUSE_LAYER 2 \
-#         MODEL.MASK_FORMER.SAM_FEATURE_FUSE_LAYER 0 \
-#         MODEL.SAM_NAME vit_b \
-#         MODEL.FROZEN_SEG.CLIP_PRETRAINED_WEIGHTS pretrained_checkpoint/models--laion--CLIP-convnext_large_d_320.laion2B-s29B-b131K-ft-soup/open_clip_pytorch_model.bin \
-#         TEST.USE_SAM_MASKS True \
-#         TEST.PKL_SAM_MODEL_NAME vit_h
-# done
-
-
-########### test recall ############
-# path=output/Sam_query/ConvNext-L_vit_b_1x
-# for config in "${configs[@]}"; do
-#     srun python train_net.py --eval-only --num-gpus 4 --dist-url tcp://127.0.0.1:$port \
-#         --config-file $config \
-#         OUTPUT_DIR "output/Ablation/recall_withEverything/$(basename "$config" .yaml)" \
-#         MODEL.WEIGHTS "$path/model_final.pth" \
-#         TEST.USE_SAM_MASKS True \
-#         MODEL.MASK_FORMER.TEST.RECALL_ON True \
-#         MODEL.MASK_FORMER.TEST.SEMANTIC_ON False \
-#         MODEL.MASK_FORMER.TEST.INSTANCE_ON False \
-#         MODEL.MASK_FORMER.TEST.PANOPTIC_ON False \
-# done