perf: rm sys.path.append() & only in CLI will print_info() be call

paddleclas.py

@@ -13,10 +13,6 @@
 # limitations under the License.
 
 import os
-import sys
-__dir__ = os.path.dirname(__file__)
-sys.path.append(os.path.join(__dir__, ""))
-
 from typing import Union, Generator
 import argparse
 import shutil
@@ -32,16 +28,16 @@ from tqdm import tqdm
 from prettytable import PrettyTable
 import paddle
 
-import ppcls.arch.backbone as backbone
-from ppcls.utils import logger
+from .ppcls.arch import backbone
+from .ppcls.utils import logger
 
-from deploy.python.predict_cls import ClsPredictor
-from deploy.utils.get_image_list import get_image_list
-from deploy.utils import config
+from .deploy.python.predict_cls import ClsPredictor
+from .deploy.utils.get_image_list import get_image_list
+from .deploy.utils import config
 
-# for the PaddleClas Project to import
-import deploy
-import ppcls
+# for the PaddleClas Project
+from . import deploy
+from . import ppcls
 
 # for building model with loading pretrained weights from backbone
 logger.init_logger()
@@ -205,6 +201,7 @@ class InputModelError(Exception):
 def init_config(model_type, model_name, inference_model_dir, **kwargs):
 
     cfg_path = f"deploy/configs/PULC/{model_name}/inference_{model_name}.yaml" if model_type == "pulc" else "deploy/configs/inference_cls.yaml"
+    __dir__ = os.path.dirname(__file__)
     cfg_path = os.path.join(__dir__, cfg_path)
     cfg = config.get_config(cfg_path, show=False)
 
@@ -456,10 +453,6 @@ class PaddleClas(object):
     """PaddleClas.
     """
 
-    if not os.environ.get('ppcls', False):
-        os.environ.setdefault('ppcls', 'True')
-        print_info()
-
     def __init__(self,
                  model_name: str=None,
                  inference_model_dir: str=None,
@@ -474,6 +467,7 @@ class PaddleClas(object):
             topk (int, optional): Return the top k prediction results with the highest score. Defaults to 5.
         """
         super().__init__()
+
         self.model_type, inference_model_dir = self._check_input_model(
             model_name, inference_model_dir)
         self._config = init_config(self.model_type, model_name,
@@ -598,6 +592,7 @@ class PaddleClas(object):
 def main():
     """Function API used for commad line.
     """
+    print_info()
     cfg = args_cfg()
     clas_engine = PaddleClas(**cfg)
     res = clas_engine.predict(cfg["infer_imgs"], print_pred=True)