use more descriptive script and variable names (#21)

* rename file Signed-off-by: fred@pegasus <[email protected]> * update file name Signed-off-by: fred@pegasus <[email protected]> * update file and model name Signed-off-by: fred@pegasus <[email protected]>
fredzzhang · Dec 5, 2021 · 38cb045 · 38cb045
1 parent 41e58fb
commit 38cb045
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Showing 3 changed files with 8 additions and 8 deletions.
diff --git a/inference.py b/inference.py
@@ -20,7 +20,7 @@
 from mpl_toolkits.axes_grid1 import make_axes_locatable
 
 from utils import DataFactory
-from detector import build_detector
+from upt import build_detector
 
 warnings.filterwarnings("ignore")
 
@@ -133,27 +133,27 @@ def main(args):
     actions = dataset.dataset.verbs if args.dataset == 'hicodet' else \
         dataset.dataset.actions
 
-    detector = build_detector(args, conversion)
-    detector.eval()
+    upt = build_detector(args, conversion)
+    upt.eval()
 
     if os.path.exists(args.resume):
         print(f"=> Continue from saved checkpoint {args.resume}")
         checkpoint = torch.load(args.resume, map_location='cpu')
-        detector.load_state_dict(checkpoint['model_state_dict'])
+        upt.load_state_dict(checkpoint['model_state_dict'])
     else:
         print(f"=> Start from a randomly initialised model")
 
     if args.image_path is None:
         image, _ = dataset[args.index]
-        output = detector([image])
+        output = upt([image])
         image = dataset.dataset.load_image(
             os.path.join(dataset.dataset._root,
                 dataset.dataset.filename(args.index)
         ))
     else:
         image = dataset.dataset.load_image(args.image_path)
         image_tensor, _ = dataset.transforms(image, None)
-        output = detector([image_tensor])
+        output = upt([image_tensor])
 
     visualise_entire_image(image, output[0], actions, args.action, args.action_score_thresh)
 

diff --git a/main.py b/main.py
@@ -19,7 +19,7 @@
 import torch.multiprocessing as mp
 from torch.utils.data import DataLoader, DistributedSampler
 
-from detector import build_detector
+from upt import build_detector
 from utils import custom_collate, CustomisedDLE, DataFactory
 
 warnings.filterwarnings("ignore")

diff --git a/detector.py → upt.py b/detector.py → upt.py
@@ -1,5 +1,5 @@
 """
-Human-object interaction detector
+Unary-pairwise transformer for human-object interaction detection
 
 Fred Zhang <[email protected]>