bugfixed: use val for validation, support eval mode

tools/train_and_eval.py

@@ -99,7 +99,7 @@ def train_one_epoch(model, train_loader, optimizer, epoch, lr_scheduler, total_i
     return total_it
 
 
-def eval_one_epoch(model, eval_loader, epoch, tb_log, log_f=None):
+def eval_one_epoch(model, eval_loader, epoch, tb_log=None, log_f=None):
     model.train()
     log_print('===============EVAL EPOCH %d================' % epoch, log_f=log_f)
 
@@ -123,7 +123,8 @@ def eval_one_epoch(model, eval_loader, epoch, tb_log, log_f=None):
 
     iou_list = np.array(iou_list)
     avg_iou = iou_list.mean()
-    tb_log.log_value('eval_fg_iou', avg_iou, epoch)
+    if tb_log is not None:
+        tb_log.log_value('eval_fg_iou', avg_iou, epoch)
 
     log_print('\nEpoch %d: Average IoU (samples=%d): %.6f' % (epoch, iou_list.__len__(), avg_iou), log_f=log_f)
     return avg_iou
@@ -182,12 +183,12 @@ def lr_lbmd(cur_epoch):
     MODEL = importlib.import_module(args.net)  # import network module
     model = MODEL.get_model(input_channels=0)
 
-    eval_set = KittiDataset(root_dir='./data', mode='EVAL')
+    eval_set = KittiDataset(root_dir='./data', mode='EVAL', split='val')
     eval_loader = DataLoader(eval_set, batch_size=args.batch_size, shuffle=False, pin_memory=True,
                              num_workers=args.workers, collate_fn=eval_set.collate_batch)
 
     if args.mode == 'train':
-        train_set = KittiDataset(root_dir='./data', mode='TRAIN')
+        train_set = KittiDataset(root_dir='./data', mode='TRAIN', split='train')
         train_loader = DataLoader(train_set, batch_size=args.batch_size, shuffle=True, pin_memory=True,
                                   num_workers=args.workers, collate_fn=train_set.collate_batch)
         # output dir config
@@ -210,7 +211,7 @@ def lr_lbmd(cur_epoch):
         epoch = load_checkpoint(model, args.ckpt)
         model.cuda()
         with torch.no_grad():
-            avg_iou = eval_one_epoch(model, eval_loader, epoch, log_f)
+            avg_iou = eval_one_epoch(model, eval_loader, epoch)
     else:
         raise NotImplementedError