experiments_finetune

configs/fpn_neck.py

@@ -12,7 +12,7 @@
     samples_per_gpu=3,
     workers_per_gpu=2,
     val=dict(split='ImageSets/SegmentationContext/tiny_val.txt',),
-    test=dict(split='ImageSets/SegmentationContext/val.txt',),
+    test=dict(split='ImageSets/SegmentationContext/tiny_val.txt',),
 )
 
 checkpoint_config = dict(interval=2000,)

configs/linear_neck.py

@@ -8,7 +8,7 @@
     samples_per_gpu=32,
     workers_per_gpu=2,
     val=dict(split='ImageSets/SegmentationContext/tiny_val.txt',),
-    test=dict(split='ImageSets/SegmentationContext/val.txt',),
+    test=dict(split='ImageSets/SegmentationContext/tiny_val.txt',),
 )
 
 checkpoint_config = dict(interval=2000,)

configs/sfp_neck.py

@@ -13,7 +13,7 @@
     samples_per_gpu=3,
     workers_per_gpu=2,
     val=dict(split='ImageSets/SegmentationContext/tiny_val.txt',),
-    test=dict(split='ImageSets/SegmentationContext/val.txt',),
+    test=dict(split='ImageSets/SegmentationContext/tiny_val.txt',),
 )
 
 checkpoint_config = dict(interval=2000,)

test.py

@@ -146,7 +146,6 @@ def main():
     cfg.data.test.test_mode = True
     if args.gpu_id is not None:
         cfg.gpu_ids = [args.gpu_id]
-
     # init distributed env first, since logger depends on the dist info.
     if args.launcher == 'none':
         cfg.gpu_ids = [args.gpu_id]
@@ -166,10 +165,10 @@ def main():
         mmcv.mkdir_or_exist(osp.abspath(args.work_dir))
         timestamp = time.strftime('%Y%m%d_%H%M%S', time.localtime())
         if args.aug_test:
-            json_file = osp.join(args.work_dir,
+            json_file = osp.join(args.work_dir.replace("/hy-tmp/", ""),
                                  f'eval_multi_scale_{timestamp}.json')
         else:
-            json_file = osp.join(args.work_dir,
+            json_file = osp.join(args.work_dir.replace("/hy-tmp/", ""),
                                  f'eval_single_scale_{timestamp}.json')
     elif rank == 0:
         work_dir = osp.join('./work_dirs',

test.sh

@@ -2,10 +2,10 @@
 
 GPU=0
 NAME="eva2_segmenter"
-CONFIGS="configs/Hyper_Control.py"
-CKPT="workbench/eva2_segmenter/train/finetune_1/iter_14000.pth"
-WORK_DIR="workbench/${NAME}/eval/"
-SHOW_DIR="workbench/${NAME}/eval/inference/"
+CONFIGS="configs/linear_neck.py"
+CKPT="/hy-tmp/workbench/eva2_segmenter/train/neck_linear_finetune_0/iter_22000.pth"
+WORK_DIR="/hy-tmp/workbench/${NAME}/eval/"
+SHOW_DIR="/hy-tmp/workbench/${NAME}/eval/inference/"
 
 python test.py --eval mIoU --gpu-id ${GPU} \
  --config ${CONFIGS} \
@@ -14,4 +14,3 @@ python test.py --eval mIoU --gpu-id ${GPU} \
  --show-dir ${SHOW_DIR} \
 #  --no-validate
 #  --load-from ${LOAD}
-

train.py

@@ -212,11 +212,12 @@ def main(args, info, verbose=False):
 
     # create work_dir
     mmcv.mkdir_or_exist(osp.abspath(cfg.work_dir))
+    mmcv.mkdir_or_exist(osp.abspath(cfg.work_dir.replace("/hy-tmp/", "")))
     # dump config
-    cfg.dump(osp.join(cfg.work_dir, osp.basename(config)))
+    cfg.dump(osp.join(cfg.work_dir.replace("/hy-tmp/", ""), osp.basename(config)))
     # init the logger before other steps
     timestamp = time.strftime('%Y%m%d_%H%M%S', time.localtime())
-    log_file = osp.join(cfg.work_dir, f'{timestamp}.log')
+    log_file = osp.join(cfg.work_dir.replace("/hy-tmp/", ""), f'{timestamp}.log')
     logger = get_root_logger(log_file=log_file, log_level=cfg.log_level)
 
     # init the meta dict to record some important information such as
@@ -280,10 +281,10 @@ def main(args, info, verbose=False):
 
 if __name__ == '__main__':
     args = parse_args()
-    neck_choices = ["linear", "fpn", "sfp"][:1]
+    neck_choices = ["linear", "fpn", "sfp"]
     for n in neck_choices:
         hyper_info = {
-            "finetune_code": 0,
+            "finetune_code": 1,
             "config_neck": n,
         }
         main(args, hyper_info)

train.sh

@@ -2,13 +2,12 @@
 
 GPU=0
 NAME="eva2_segmenter"
-WORK_DIR="workbench/${NAME}/train/"
-RESUME="workbench/${NAME}/train/finetune_1/iter_14000.pth"
+WORK_DIR="/hy-tmp/workbench/${NAME}/train/"
+RESUME="/hy-tmp/neck_linear_finetune_0/iter_6000.pth"
 LOAD=""
 
 python train.py --seed 0 --deterministic --gpu-ids ${GPU} \
  --work-dir ${WORK_DIR} \
 #  --resume-from ${RESUME} \
 #  --no-validate
 #  --load-from ${LOAD}
-