fix: 删除dataset相关的日志中令人迷惑的csv format

This commit is contained in:
zuchen.wang 2021-11-10 17:00:50 +08:00
parent a080930464
commit f8ae876c8c
7 changed files with 16 additions and 14 deletions

View File

@ -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"))

View File

@ -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)

View File

@ -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):

View File

@ -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"))

View File

@ -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"))

View File

@ -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()

View File

@ -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'),
anno_path=os.path.join(_root, 'labels/1019/1019_clean_train.json'),
transform=transforms, mode='train')
dataset = DATASET_REGISTRY.get(d)(img_root=img_root, anno_path=anno_path, 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!!!")
exit(-1)
raise ValueError("Undefined Dataset!!!")
data_loader, _ = build_reid_test_loader(cfg, test_set=test_set)
return data_loader