Fix the bugs related to the change

ActiveVisionLab · Nov 17, 2020 · a158453 · a158453
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commit a158453
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Showing 4 changed files with 6 additions and 12 deletions.
diff --git a/HPatches/eval_hpatches.py b/HPatches/eval_hpatches.py
@@ -39,7 +39,6 @@
 parser.add_argument('--image_size', type=int, default=1600, help='image size used')
 parser.add_argument('--Npts', type=int, default=2000, help='how many matches selected')
 parser.add_argument('--iter_step', type=int, default=1000)
-parser.add_argument('--selection', type=str, default='partial')
 parser.add_argument('--im_fe_ratio', type=int, default=16)
 parser.add_argument('--device', type=int, default=0, help='which gpu should the experiment be run on')
 parser.add_argument('--benchmark', type=bool, default=False, help='whether to benchmark the speed. If does, it will use the first image for 20 times')
@@ -51,8 +50,8 @@
 matcher = tools.ImgMatcher(use_cuda=use_cuda, half_precision=half_precision, checkpoint=args.checkpoint, postprocess_device=feature_extractor_device, im_fe_ratio=args.im_fe_ratio)
 
 if not args.benchmark:
-    experiment_name = '%s_%d_%d_%s' % (args.experiment_name, args.image_size, args.Npts, args.selection)
-    output_name = 'hpatches_%s_%d_%d_%s.txt' % (args.experiment_name, args.image_size, args.Npts, args.selection)
+    experiment_name = '%s_%d_%d' % (args.experiment_name, args.image_size, args.Npts)
+    output_name = 'hpatches_%s_%d_%d.txt' % (args.experiment_name, args.image_size, args.Npts)
     out = open(output_name, 'w')
     print(output_name)
 
@@ -109,7 +108,7 @@
             batch['target_image'] = ref_im.cuda()
 
             start = time.time()
-            matches, score, _ = matcher(batch, num_pts=args.Npts, central_align=True, iter_step=args.iter_step, selection=args.selection)
+            matches, score, _ = matcher(batch, num_pts=args.Npts, central_align=True, iter_step=args.iter_step)
             end = time.time()
 
             if args.benchmark:

diff --git a/aachen_day_and_night/eval_aachen_extract.py b/aachen_day_and_night/eval_aachen_extract.py
@@ -28,7 +28,6 @@
 parser.add_argument('--Npts', type=int, default=8000)
 parser.add_argument('--image_pairs', type=str, default='all')
 parser.add_argument('--iter_step', type=int, default=1000)
-parser.add_argument('--selection', type=str, default='partial')
 parser.add_argument('--device', type=int, default=0)
 parser.add_argument('--benchmark', type=bool, default=False)
 args = parser.parse_args()
@@ -87,7 +86,7 @@
     hB_,wB_=tgt.shape[-2:]
 
     with torch.no_grad():
-        result, scores, features = matcher({'source_image':src, 'target_image':tgt}, num_pts=args.Npts, central_align=False, iter_step=args.iter_step, selection=args.selection, args=args)
+        result, scores, features = matcher({'source_image':src, 'target_image':tgt}, num_pts=args.Npts, central_align=False, iter_step=args.iter_step, args=args)
         # pdb.set_trace()
         corr4d, featureA_0, featureB_0 = features
         fs1, fs2 = featureA_0.shape[2:]

diff --git a/inloc/eval_inloc_extract.py b/inloc/eval_inloc_extract.py
@@ -31,7 +31,6 @@
 parser.add_argument('--n_queries', type=int, default=356)
 parser.add_argument('--n_panos', type=int, default=10)
 parser.add_argument('--iter_step', type=int, default=1000)
-parser.add_argument('--selection', type=str, default='partial')
 parser.add_argument('--im_fe_ratio', type=int, default=16)
 parser.add_argument('--device', type=int, default=0)
 parser.add_argument('--benchmark', type=bool, default=False)
@@ -47,7 +46,7 @@
 model = tools.ImgMatcher(use_cuda=use_cuda, half_precision=half_precision, checkpoint=args.checkpoint, postprocess_device=feature_extractor_device, im_fe_ratio=args.im_fe_ratio)
 
 # Generate output folder path
-output_folder = args.experiment_name + '_'+ args.selection
+output_folder = args.experiment_name
 print('Output matches folder: '+output_folder)
 
 scale_factor = 0.0625
@@ -103,7 +102,7 @@
             hB,wB=tgt.shape[-2:]
             tgt=resize(normalize(tgt), args.image_size, scale_factor)
             hB_,wB_=tgt.shape[-2:]
-            result, scores, _ = model({'source_image': src, 'target_image': tgt}, num_pts=args.Npts, central_align=True, iter_step=args.iter_step, selection=args.selection, args=args)
+            result, scores, _ = model({'source_image': src, 'target_image': tgt}, num_pts=args.Npts, central_align=True, iter_step=args.iter_step, args=args)
             H_src, W_src = src.shape[-2:]
             H_tgt, W_tgt = tgt.shape[-2:]
 

diff --git a/train.py b/train.py
@@ -1,6 +1,3 @@
-'''
-Train ncnet with strong loss
-'''
 import os
 import numpy as np
 import numpy.random