refine script and config.

PaddleCV/video/config.py

@@ -61,7 +61,10 @@ def merge_configs(cfg, sec, args_dict):
     return cfg
 
 
-def print_configs(cfg):
-    import pprint
-    logger.info('Training with config:')
-    logger.info(pprint.pformat(cfg))
+def print_configs(cfg, mode):
+    logger.info("---------------- {:>5} Arguments ----------------".format(mode))
+    for sec, sec_items in cfg.items():
+        logger.info("{}:".format(sec))
+        for k, v in sec_items.items():
+            logger.info("    {}:{}".format(k, v))
+    logger.info("-------------------------------------------------")

PaddleCV/video/infer.py

@@ -83,8 +83,7 @@ def infer(args):
     # parse config
     config = parse_config(args.config)
     infer_config = merge_configs(config, 'infer', vars(args))
-    logger.info("############### infer config ###############")
-    print_configs(infer_config)
+    print_configs(infer_config, "Infer")
     infer_model = models.get_model(args.model_name, infer_config, mode='infer')
     infer_model.build_input(use_pyreader=False)
     infer_model.build_model()

PaddleCV/video/scripts/infer/infer_attention_cluster.sh

 python infer.py --model_name="AttentionCluster" --config=./configs/attention_cluster.txt \
-                --filelist=./data/youtube8m/infer.list \
+                --filelist=./dataset/youtube8m/infer.list \
                 --weights=./checkpoints/AttentionCluster_epoch0 \
                 --save_dir="./save"

PaddleCV/video/scripts/infer/infer_attention_lstm.sh

 python infer.py --model_name="AttentionLSTM" --config=./configs/attention_lstm.txt \
-                --filelist=./data/youtube8m/infer.list \
+                --filelist=./dataset/youtube8m/infer.list \
                 --weights=./checkpoints/AttentionLSTM_epoch0 \
                 --save_dir="./save"

PaddleCV/video/scripts/infer/infer_nextvlad.sh

-python infer.py --model_name="NEXTVLAD" --config=./configs/nextvlad.txt --filelist=./data/youtube8m/infer.list \
+python infer.py --model_name="NEXTVLAD" --config=./configs/nextvlad.txt --filelist=./dataset/youtube8m/infer.list \
                 --weights=./checkpoints/NEXTVLAD_epoch0 \
                 --save_dir="./save"

PaddleCV/video/scripts/infer/infer_stnet.sh

-python infer.py --model_name="STNET" --config=./configs/stnet.txt --filelist=./data/kinetics/infer.list \
+python infer.py --model_name="STNET" --config=./configs/stnet.txt --filelist=./dataset/kinetics/infer.list \
                 --log_interval=10 --weights=./checkpoints/STNET_epoch0 --save_dir=./save

PaddleCV/video/scripts/infer/infer_tsm.sh

-python infer.py --model_name="TSM" --config=./configs/tsm.txt --filelist=./data/kinetics/infer.list \
+python infer.py --model_name="TSM" --config=./configs/tsm.txt --filelist=./dataset/kinetics/infer.list \
                 --log_interval=10 --weights=./checkpoints/TSM_epoch0 --save_dir=./save

PaddleCV/video/scripts/infer/infer_tsn.sh

-python infer.py --model_name="TSN" --config=./configs/tsn.txt --filelist=./data/kinetics/infer.list \
+python infer.py --model_name="TSN" --config=./configs/tsn.txt --filelist=./dataset/kinetics/infer.list \
                 --log_interval=10 --weights=./checkpoints/TSN_epoch0 --save_dir=./save

PaddleCV/video/test.py

@@ -68,8 +68,7 @@ def test(args):
     # parse config
     config = parse_config(args.config)
     test_config = merge_configs(config, 'test', vars(args))
-    logger.info("############### test config ###############")
-    print_configs(test_config)
+    print_configs(test_config, "Test")
 
     # build model
     test_model = models.get_model(args.model_name, test_config, mode='test')

PaddleCV/video/train.py

@@ -107,8 +107,7 @@ def train(args):
     config = parse_config(args.config)
     train_config = merge_configs(config, 'train', vars(args))
     valid_config = merge_configs(config, 'valid', vars(args))
-    logger.info("############### train config ###############")
-    print_configs(train_config)
+    print_configs(train_config, 'Train')
     train_model = models.get_model(args.model_name, train_config, mode='train')
     valid_model = models.get_model(args.model_name, valid_config, mode='valid')