refactor parser

monoloco/eval/eval_activity.py

@@ -81,7 +81,7 @@ class ActivityEvaluator:
                 extension = '.predictions.json'
                 path_pif = os.path.join(self.dir_ann, basename + extension)
                 annotations = open_annotations(path_pif)
-                kk, _ = factory_for_gt(im_size, verbose=False)
+                kk, _ = factory_for_gt(im_size)
 
                 # Collect corresponding gt files (ys_gt: 1 or 0)
                 boxes_gt, ys_gt = parse_gt_collective(self.dir_data, seq, path_pif)

monoloco/eval/generate_kitti.py

@@ -32,14 +32,13 @@ class GenerateKitti:
     def __init__(self, args):
 
         # Load Network
-        self.net = args.net
+        assert args.mode in ('mono', 'stereo'), "mode not recognized"
-        assert args.net in ('monstereo', 'monoloco_pp'), "net not recognized"
+        self.net = 'monstereo' if args.mode == 'mono' else 'monoloco_pp'
-
         use_cuda = torch.cuda.is_available()
         device = torch.device("cuda" if use_cuda else "cpu")
         self.model = Loco(
             model=args.model,
-            net=args.net,
+            mode=args.mode,
             device=device,
             n_dropout=args.n_dropout,
             p_dropout=args.dropout,
@@ -60,7 +59,6 @@ class GenerateKitti:
 
         # Add monocular and stereo baselines (they require monoloco as backbone)
         if args.baselines:
-
             # Load MonoLoco
             self.baselines['mono'] = ['monoloco', 'geometric']
             self.monoloco = Loco(
@@ -72,7 +70,7 @@ class GenerateKitti:
                 linear_size=256
             )
             # Stereo baselines
-            if args.net == 'monstereo':
+            if args.mode == 'stereo':
                 self.baselines['stereo'] = ['pose', 'reid']
                 self.cnt_disparity = defaultdict(int)
                 self.cnt_no_stereo = 0

monoloco/prep/prep_kitti.py

@@ -45,11 +45,12 @@ class PreprocessKitti:
     dic_names = defaultdict(lambda: defaultdict(list))
     dic_std = defaultdict(lambda: defaultdict(list))
 
-    def __init__(self, dir_ann, iou_min, monocular=False):
+    def __init__(self, dir_ann, mode='mono', iou_min=0.3):
 
         self.dir_ann = dir_ann
         self.iou_min = iou_min
-        self.monocular = monocular
+        self.mode = mode
+        assert self.mode in ('mono', 'stereo'), "modality not recognized"
         self.names_gt = tuple(os.listdir(self.dir_gt))
         self.dir_kk = os.path.join('data', 'kitti', 'calib')
         self.list_gt = glob.glob(self.dir_gt + '/*.txt')
@@ -160,7 +161,7 @@ class PreprocessKitti:
                         lab = ys[idx_gt][:-1]
 
                         # Preprocess MonoLoco++
-                        if self.monocular:
+                        if self.mode == 'mono':
                             inp = preprocess_monoloco(keypoint, kk).view(-1).tolist()
                             lab = normalize_hwl(lab)
                             if ys[idx_gt][10] < 0.5:
@@ -270,7 +271,7 @@ class PreprocessKitti:
         print("Ambiguous instances removed: {}".format(cnt_ambiguous))
         print("Extra pairs created with horizontal flipping: {}\n".format(cnt_extra_pair))
 
-        if not self.monocular:
+        if self.mode == 'stereo':
             print('Instances with stereo correspondence: {:.1f}% '.format(100 * cnt_pair / cnt_pair_tot))
             for phase in ['train', 'val']:
                 cnt = cnt_mono[phase] + cnt_stereo[phase]

monoloco/run.py

@@ -62,6 +62,7 @@ def cli():
 
     # Preprocess input data
     prep_parser.add_argument('--dir_ann', help='directory of annotations of 2d joints', required=True)
+    prep_parser.add_argument('--mode', help='mono, stereo', default='mono')
     prep_parser.add_argument('--dataset',
                              help='datasets to preprocess: nuscenes, nuscenes_teaser, nuscenes_mini, kitti',
                              default='kitti')
@@ -69,7 +70,6 @@ def cli():
     prep_parser.add_argument('--iou_min', help='minimum iou to match ground truth', type=float, default=0.3)
     prep_parser.add_argument('--variance', help='new', action='store_true')
     prep_parser.add_argument('--activity', help='new', action='store_true')
-    prep_parser.add_argument('--monocular', help='new', action='store_true')
 
     # Training
     training_parser.add_argument('--joints', help='Json file with input joints', required=True)
@@ -132,7 +132,7 @@ def main():
             prep.run()
         else:
             from .prep.prep_kitti import PreprocessKitti
-            prep = PreprocessKitti(args.dir_ann, args.iou_min, args.monocular)
+            prep = PreprocessKitti(args.dir_ann, mode=args.mode, iou_min=args.iou_min)
             if args.activity:
                 prep.prep_activity()
             else: