Object detection changes: (#7208)

257914648  by lzc:

    Internal changes

--
257525973  by Zhichao Lu:

    Fixes bug that silently prevents checkpoints from loading when training w/ eager + functions. Also sets up scripts to run training.

--
257296614  by Zhichao Lu:

    Adding detection_features to model outputs

--
257234565  by Zhichao Lu:

    Fix wrong order of `classes_with_max_scores` in class-agnostic NMS caused by
    sorting in partitioned-NMS.

--
257232002  by ronnyvotel:

    Supporting `filter_nonoverlapping` option in np_box_list_ops.clip_to_window().

--
257198282  by Zhichao Lu:

    Adding the focal loss and l1 loss from the Objects as Points paper.

--
257089535  by Zhichao Lu:

    Create Keras based ssd + resnetv1 + fpn.

--
257087407  by Zhichao Lu:

    Make object_detection/data_decoders Python3-compatible.

--
257004582  by Zhichao Lu:

    Updates _decode_raw_data_into_masks_and_boxes to the latest binary masks-to-string encoding fo...

research/object_detection/utils/config_util.py

@@ -14,6 +14,10 @@
 # ==============================================================================
 """Functions for reading and updating configuration files."""
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import os
 import tensorflow as tf
 

research/object_detection/utils/config_util_test.py

@@ -14,8 +14,13 @@
 # ==============================================================================
 """Tests for object_detection.utils.config_util."""
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import os
 
+from six.moves import range
 import tensorflow as tf
 
 from google.protobuf import text_format

research/object_detection/utils/context_manager.py

@@ -37,4 +37,3 @@ class IdentityContextManager(object):
     del exec_value
     del traceback
     return False
-

research/object_detection/utils/dataset_util.py

@@ -15,6 +15,10 @@
 
 """Utility functions for creating TFRecord data sets."""
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import tensorflow as tf
 
 
@@ -84,5 +88,3 @@ def recursive_parse_xml_to_dict(xml):
         result[child.tag] = []
       result[child.tag].append(child_result[child.tag])
   return {xml.tag: result}
-
-

research/object_detection/utils/dataset_util_test.py

@@ -15,6 +15,10 @@
 
 """Tests for object_detection.utils.dataset_util."""
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import os
 import tensorflow as tf
 

research/object_detection/utils/label_map_util.py

@@ -14,8 +14,13 @@
 # ==============================================================================
 """Label map utility functions."""
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import logging
 
+from six.moves import range
 import tensorflow as tf
 from google.protobuf import text_format
 from object_detection.protos import string_int_label_map_pb2

research/object_detection/utils/label_map_util_test.py

@@ -14,7 +14,12 @@
 # ==============================================================================
 """Tests for object_detection.utils.label_map_util."""
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import os
+from six.moves import range
 import tensorflow as tf
 
 from google.protobuf import text_format

research/object_detection/utils/learning_schedules.py

@@ -14,7 +14,12 @@
 # ==============================================================================
 """Library of common learning rate schedules."""
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
 import numpy as np
+from six.moves import range
+from six.moves import zip
 import tensorflow as tf
 
 
@@ -191,7 +196,7 @@ def manual_stepping(global_step, boundaries, rates, warmup=False):
 
   if warmup and boundaries:
     slope = (rates[1] - rates[0]) * 1.0 / boundaries[0]
-    warmup_steps = range(boundaries[0])
+    warmup_steps = list(range(boundaries[0]))
     warmup_rates = [rates[0] + slope * step for step in warmup_steps]
     boundaries = warmup_steps + boundaries
     rates = warmup_rates + rates[1:]

research/object_detection/utils/learning_schedules_test.py

@@ -14,7 +14,12 @@
 # ==============================================================================
 
 """Tests for object_detection.utils.learning_schedules."""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import numpy as np
+from six.moves import range
 import tensorflow as tf
 
 from object_detection.utils import learning_schedules

research/object_detection/utils/metrics.py

@@ -13,9 +13,12 @@
 # limitations under the License.
 # ==============================================================================
 """Functions for computing metrics like precision, recall, CorLoc and etc."""
+from __future__ import absolute_import
 from __future__ import division
+from __future__ import print_function
 
 import numpy as np
+from six.moves import range
 
 
 def compute_precision_recall(scores, labels, num_gt):

research/object_detection/utils/metrics_test.py

@@ -14,6 +14,10 @@
 # ==============================================================================
 """Tests for object_detection.metrics."""
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import numpy as np
 import tensorflow as tf
 

research/object_detection/utils/model_util.py

@@ -15,6 +15,10 @@
 
 """Utility functions for manipulating Keras models."""
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import tensorflow as tf
 
 

research/object_detection/utils/model_util_test.py

@@ -15,6 +15,10 @@
 
 """Test utility functions for manipulating Keras models."""
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import tensorflow as tf
 
 from object_detection.utils import model_util

research/object_detection/utils/np_box_list.py

@@ -15,7 +15,11 @@
 
 """Numpy BoxList classes and functions."""
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
 import numpy as np
+from six.moves import range
 
 
 class BoxList(object):

research/object_detection/utils/np_box_list_ops.py

@@ -19,7 +19,12 @@ Example box operations that are supported:
   * Areas: compute bounding box areas
   * IOU: pairwise intersection-over-union scores
 """
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import numpy as np
+from six.moves import range
 
 from object_detection.utils import np_box_list
 from object_detection.utils import np_box_ops
@@ -331,7 +336,7 @@ def scale(boxlist, y_scale, x_scale):
   return scaled_boxlist
 
 
-def clip_to_window(boxlist, window):
+def clip_to_window(boxlist, window, filter_nonoverlapping=True):
   """Clip bounding boxes to a window.
 
   This op clips input bounding boxes (represented by bounding box
@@ -343,6 +348,8 @@ def clip_to_window(boxlist, window):
     window: a numpy array of shape [4] representing the
             [y_min, x_min, y_max, x_max] window to which the op
             should clip boxes.
+    filter_nonoverlapping: whether to filter out boxes that do not overlap at
+      all with the window.
 
   Returns:
     a BoxList holding M_out boxes where M_out <= M_in
@@ -359,10 +366,12 @@ def clip_to_window(boxlist, window):
   clipped = np_box_list.BoxList(
       np.hstack([y_min_clipped, x_min_clipped, y_max_clipped, x_max_clipped]))
   clipped = _copy_extra_fields(clipped, boxlist)
+  if filter_nonoverlapping:
     areas = area(clipped)
-  nonzero_area_indices = np.reshape(np.nonzero(np.greater(areas, 0.0)),
-                                    [-1]).astype(np.int32)
-  return gather(clipped, nonzero_area_indices)
+    nonzero_area_indices = np.reshape(
+        np.nonzero(np.greater(areas, 0.0)), [-1]).astype(np.int32)
+    clipped = gather(clipped, nonzero_area_indices)
+  return clipped
 
 
 def prune_non_overlapping_boxes(boxlist1, boxlist2, minoverlap=0.0):

research/object_detection/utils/np_box_list_ops_test.py

@@ -15,6 +15,10 @@
 
 """Tests for object_detection.utils.np_box_list_ops."""
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import numpy as np
 import tensorflow as tf
 

research/object_detection/utils/np_box_list_test.py

@@ -15,6 +15,10 @@
 
 """Tests for object_detection.utils.np_box_list_test."""
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import numpy as np
 import tensorflow as tf
 

research/object_detection/utils/np_box_mask_list.py

@@ -15,6 +15,10 @@
 
 """Numpy BoxMaskList classes and functions."""
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import numpy as np
 from object_detection.utils import np_box_list
 
@@ -60,4 +64,3 @@ class BoxMaskList(np_box_list.BoxList):
       a numpy array of shape [N, height, width] representing masks
     """
     return self.get_field('masks')
-

research/object_detection/utils/np_box_mask_list_ops.py

@@ -19,7 +19,12 @@ Example box operations that are supported:
   * Areas: compute bounding box areas
   * IOU: pairwise intersection-over-union scores
 """
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import numpy as np
+from six.moves import range
 
 from object_detection.utils import np_box_list_ops
 from object_detection.utils import np_box_mask_list

research/object_detection/utils/np_box_mask_list_ops_test.py

@@ -15,6 +15,10 @@
 
 """Tests for object_detection.utils.np_box_mask_list_ops."""
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import numpy as np
 import tensorflow as tf