Add an option to skip the last striding in mobilenet. The modified network has...

Add an option to skip the last striding in mobilenet. The modified network has nominal output stride 16 instead of 32.

PiperOrigin-RevId: 191932855

research/object_detection/models/faster_rcnn_mobilenet_v1_feature_extractor.py

@@ -22,6 +22,24 @@ from nets import mobilenet_v1
 slim = tf.contrib.slim
 
 
+_MOBILENET_V1_100_CONV_NO_LAST_STRIDE_DEFS = [
+    mobilenet_v1.Conv(kernel=[3, 3], stride=2, depth=32),
+    mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=1, depth=64),
+    mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=2, depth=128),
+    mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=1, depth=128),
+    mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=2, depth=256),
+    mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=1, depth=256),
+    mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=2, depth=512),
+    mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=1, depth=512),
+    mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=1, depth=512),
+    mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=1, depth=512),
+    mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=1, depth=512),
+    mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=1, depth=512),
+    mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=1, depth=1024),
+    mobilenet_v1.DepthSepConv(kernel=[3, 3], stride=1, depth=1024)
+]
+
+
 class FasterRCNNMobilenetV1FeatureExtractor(
     faster_rcnn_meta_arch.FasterRCNNFeatureExtractor):
   """Faster R-CNN Mobilenet V1 feature extractor implementation."""
@@ -33,7 +51,8 @@ class FasterRCNNMobilenetV1FeatureExtractor(
                reuse_weights=None,
                weight_decay=0.0,
                depth_multiplier=1.0,
-               min_depth=16):
+               min_depth=16,
+               skip_last_stride=False):
     """Constructor.
 
     Args:
@@ -44,6 +63,7 @@ class FasterRCNNMobilenetV1FeatureExtractor(
       weight_decay: See base class.
       depth_multiplier: float depth multiplier for feature extractor.
       min_depth: minimum feature extractor depth.
+      skip_last_stride: Skip the last stride if True.
 
     Raises:
       ValueError: If `first_stage_features_stride` is not 8 or 16.
@@ -52,6 +72,7 @@ class FasterRCNNMobilenetV1FeatureExtractor(
       raise ValueError('`first_stage_features_stride` must be 8 or 16.')
     self._depth_multiplier = depth_multiplier
     self._min_depth = min_depth
+    self._skip_last_stride = skip_last_stride
     super(FasterRCNNMobilenetV1FeatureExtractor, self).__init__(
         is_training, first_stage_features_stride, batch_norm_trainable,
         reuse_weights, weight_decay)
@@ -103,12 +124,16 @@ class FasterRCNNMobilenetV1FeatureExtractor(
               weight_decay=self._weight_decay)):
         with tf.variable_scope('MobilenetV1',
                                reuse=self._reuse_weights) as scope:
+          params = {}
+          if self._skip_last_stride:
+            params['conv_defs'] = _MOBILENET_V1_100_CONV_NO_LAST_STRIDE_DEFS
           _, activations = mobilenet_v1.mobilenet_v1_base(
               preprocessed_inputs,
               final_endpoint='Conv2d_11_pointwise',
               min_depth=self._min_depth,
               depth_multiplier=self._depth_multiplier,
-              scope=scope)
+              scope=scope,
+              **params)
     return activations['Conv2d_11_pointwise'], activations
 
   def _extract_box_classifier_features(self, proposal_feature_maps, scope):