Update explanation.py

paddlex/cv/models/explanation/core/explanation.py

@@ -16,42 +16,6 @@ from .explanation_algorithms import CAM, LIME, NormLIME
 from .normlime_base import precompute_normlime_weights
 
 
-class Explanation(object):
-    """
-    Base class for all explanation algorithms.
-    """
-    def __init__(self, explanation_algorithm_name, predict_fn, **kwargs):
-        supported_algorithms = {
-            'cam': CAM,
-            'lime': LIME,
-            'normlime': NormLIME
-        }
-
-        self.algorithm_name = explanation_algorithm_name.lower()
-        assert self.algorithm_name in supported_algorithms.keys()
-        self.predict_fn = predict_fn
-
-        # initialization for the explanation algorithm.
-        self.explain_algorithm = supported_algorithms[self.algorithm_name](
-            self.predict_fn, **kwargs
-        )#copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
-#
-#Licensed under the Apache License, Version 2.0 (the "License");
-#you may not use this file except in compliance with the License.
-#You may obtain a copy of the License at
-#
-#    http://www.apache.org/licenses/LICENSE-2.0
-#
-#Unless required by applicable law or agreed to in writing, software
-#distributed under the License is distributed on an "AS IS" BASIS,
-#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#See the License for the specific language governing permissions and
-#limitations under the License.
-
-from .explanation_algorithms import CAM, LIME, NormLIME
-from .normlime_base import precompute_normlime_weights
-
-
 class Explanation(object):
     """
     Base class for all explanation algorithms.
@@ -85,18 +49,3 @@ class Explanation(object):
 
         """
         return self.explain_algorithm.explain(data_, visualization, save_to_disk, save_dir)
-
-
-    def explain(self, data_, visualization=True, save_to_disk=True, save_dir='./tmp'):
-        """
-
-        Args:
-            data_: data_ can be a path or numpy.ndarray.
-            visualization: whether to show using matplotlib.
-            save_to_disk: whether to save the figure in local disk.
-            save_dir: dir to save figure if save_to_disk is True.
-
-        Returns:
-
-        """
-        return self.explain_algorithm.explain(data_, visualization, save_to_disk, save_dir)