draft for get_box_classifier_feature_extractor_model

research/object_detection/models/faster_rcnn_resnet_v1_fpn_keras_feature_extractor.py

@@ -289,7 +289,30 @@ class FasterRCNNResnetV1FPNKerasFeatureExtractor(
   #       return feature_maps
 
   def get_box_classifier_feature_extractor_model(self, name=None):
+    """Returns a model that extracts second stage box classifier features.
 
+    TODO: doc
+
+    Args:
+      name: A scope name to construct all variables within.
+
+    Returns:
+      A Keras model that takes proposal_feature_maps:
+        A 4-D float tensor with shape
+        [batch_size * self.max_num_proposals, crop_height, crop_width, depth]
+        representing the feature map cropped to each proposal.
+      And returns proposal_classifier_features:
+        A 4-D float tensor with shape
+        [batch_size * self.max_num_proposals, height, width, depth]
+        representing box classifier features for each proposal.
+    """
+    with tf.name_scope(name):
+      with tf.name_scope('ResnetV1FPN'):
+        feature_extractor_model = tf.keras.models.Sequential([
+          Dense(unit=1024, activation='ReLU'),
+          Dense(unit=1024, activation='ReLU')
+        ])
+        return feature_extractor_model
 
 
 class FasterRCNNResnet50FPNKerasFeatureExtractor(
@@ -428,4 +451,4 @@ class FasterRCNNResnet152FPNKerasFeatureExtractor(
         fpn_min_level=fpn_min_level,
         fpn_max_level=fpn_max_level,
         additional_layer_depth=additional_layer_depth,
-        override_base_feature_extractor_hyperparams=override_base_feature_extractor_hyperparams)
+        override_base_feature_extractor_hyperparams=override_base_feature_extractor_hyperparams)
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