Update explanation.py

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

@@ -34,6 +34,42 @@ class Explanation(object):
         # 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.
+    """
+    def __init__(self, explanation_algorithm_name, predict_fn, label_names, **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, label_names, **kwargs
         )
 
     def explain(self, data_, visualization=True, save_to_disk=True, save_dir='./tmp'):
@@ -49,3 +85,18 @@ 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)