fix: 删除dataset相关的日志中令人迷惑的csv format

fastreid/data/datasets/bases.py

@@ -161,7 +161,7 @@ class ImageDataset(Dataset):
             headers=headers,
             numalign="left",
         )
-        logger.info(f"=> Loaded {self.__class__.__name__} in csv format: \n" + colored(table, "cyan"))
+        logger.info(f"=> Loaded {self.__class__.__name__}: \n" + colored(table, "cyan"))
 
     def show_test(self):
         num_query_pids, num_query_cams = self.parse_data(self.query)
@@ -180,4 +180,4 @@ class ImageDataset(Dataset):
             headers=headers,
             numalign="left",
         )
-        logger.info(f"=> Loaded {self.__class__.__name__} in csv format: \n" + colored(table, "cyan"))
+        logger.info(f"=> Loaded {self.__class__.__name__}: \n" + colored(table, "cyan"))

fastreid/engine/defaults.py

@@ -445,7 +445,7 @@ class DefaultTrainer(TrainerBase):
                 ), "Evaluator must return a dict on the main process. Got {} instead.".format(
                     results
                 )
-                logger.info("Evaluation results for {} in csv format:".format(dataset_name))
+                logger.info("Evaluation results for {}:".format(dataset_name))
                 results_i['dataset'] = dataset_name
                 print_csv_format(results_i)
 

fastreid/evaluation/testing.py

@@ -32,7 +32,7 @@ def print_csv_format(results):
         headers=metrics,
         numalign="left",
     )
-    logger.info("Evaluation results in csv format: \n" + colored(table, "cyan"))
+    logger.info("Evaluation results: \n" + colored(table, "cyan"))
 
     # show acc precision, recall and f1 under given threshold
     metrics = [k for k, v in results.items() if isinstance(v, (list, np.ndarray))]
@@ -47,7 +47,7 @@ def print_csv_format(results):
         headers=metrics,
         numalign="left",
     )
-    logger.info("Evaluation results in csv format: \n" + colored(table, "cyan"))
+    logger.info("Evaluation results: \n" + colored(table, "cyan"))
 
 
 def verify_results(cfg, results):

projects/FastAttr/fastattr/datasets/bases.py

@@ -102,7 +102,7 @@ class Dataset(object):
             headers=headers,
             numalign="left",
         )
-        logger.info(f"=> Loaded {self.__class__.__name__} in csv format: \n" + colored(table, "cyan"))
+        logger.info(f"=> Loaded {self.__class__.__name__}: \n" + colored(table, "cyan"))
         logger.info("attributes:")
         for label, attr in self.attr_dict.items():
             logger.info('{:3d}: {}'.format(label, attr))
@@ -124,4 +124,4 @@ class Dataset(object):
             headers=headers,
             numalign="left",
         )
-        logger.info(f"=> Loaded {self.__class__.__name__} in csv format: \n" + colored(table, "cyan"))
+        logger.info(f"=> Loaded {self.__class__.__name__}: \n" + colored(table, "cyan"))

projects/FastShoe/fastshoe/data/excel_dataset.py

@@ -71,4 +71,4 @@ class ExcelDataset(ImageDataset):
             headers=headers,
             numalign="left",
         )
-        self._logger.info(f"=> Loaded {self.__class__.__name__} in csv format: \n" + colored(table, "cyan"))
+        self._logger.info(f"=> Loaded {self.__class__.__name__}: \n" + colored(table, "cyan"))

projects/FastShoe/fastshoe/data/pair_dataset.py

@@ -111,7 +111,7 @@ class PairDataset(ImageDataset):
             numalign="left",
         )
 
-        self._logger.info(f"=> Loaded {self.__class__.__name__} in csv format: \n" + colored(table, "cyan"))
+        self._logger.info(f"=> Loaded {self.__class__.__name__}: \n" + colored(table, "cyan"))
 
     def show_train(self):
         return self.describe()

projects/FastShoe/fastshoe/trainer.py

@@ -27,11 +27,12 @@ class PairTrainer(DefaultTrainer):
         cls._logger.info("Prepare training set")
 
         transforms = build_transforms(cfg, is_train=True)
+        img_root=os.path.join(_root, 'shoe_crop_all_images')
+        anno_path=os.path.join(_root, 'labels/1019/1019_clean_train.json')
+
         datasets = []
         for d in cfg.DATASETS.NAMES:
-            dataset = DATASET_REGISTRY.get(d)(img_root=os.path.join(_root, 'shoe_crop_all_images'),
+            dataset = DATASET_REGISTRY.get(d)(img_root=img_root, anno_path=anno_path, transform=transforms, mode='train')
-                                           anno_path=os.path.join(_root, 'labels/1019/1019_clean_train.json'),
-                                           transform=transforms, mode='train')
             if comm.is_main_process():
                 dataset.show_train()
             datasets.append(dataset)
@@ -42,6 +43,8 @@ class PairTrainer(DefaultTrainer):
 
     @classmethod
     def build_test_loader(cls, cfg, dataset_name):
+        cls._logger.info("Prepare {} set".format('test' if cfg.eval_only else 'validation'))
+
         transforms = build_transforms(cfg, is_train=False)
         if dataset_name == 'PairDataset':
             img_root = os.path.join(_root, 'shoe_crop_all_images')
@@ -75,8 +78,7 @@ class PairTrainer(DefaultTrainer):
                 test_set = DATASET_REGISTRY.get(dataset_name)(img_root=img_root_0908, anno_path=val_csv_0908, transform=transforms)
                 test_set.show_test()
         else:
-            cls._logger.error("Undefined Dataset!!!")
+            raise ValueError("Undefined Dataset!!!")
-            exit(-1)
                 
         data_loader, _ = build_reid_test_loader(cfg, test_set=test_set)
         return data_loader