Provide groundtruth masks and keypoints in the evaluator.

PiperOrigin-RevId: 189929413

research/object_detection/evaluator.py

@@ -94,14 +94,24 @@ def _extract_predictions_and_losses(model,
     if fields.InputDataFields.groundtruth_group_of in input_dict:
       groundtruth[fields.InputDataFields.groundtruth_group_of] = (
           input_dict[fields.InputDataFields.groundtruth_group_of])
+    groundtruth_masks_list = None
     if fields.DetectionResultFields.detection_masks in detections:
       groundtruth[fields.InputDataFields.groundtruth_instance_masks] = (
           input_dict[fields.InputDataFields.groundtruth_instance_masks])
+      groundtruth_masks_list = [
+          input_dict[fields.InputDataFields.groundtruth_instance_masks]]
+    groundtruth_keypoints_list = None
+    if fields.DetectionResultFields.detection_keypoints in detections:
+      groundtruth[fields.InputDataFields.groundtruth_keypoints] = (
+          input_dict[fields.InputDataFields.groundtruth_keypoints])
+      groundtruth_keypoints_list = [
+          input_dict[fields.InputDataFields.groundtruth_keypoints]]
     label_id_offset = 1
     model.provide_groundtruth(
         [input_dict[fields.InputDataFields.groundtruth_boxes]],
         [tf.one_hot(input_dict[fields.InputDataFields.groundtruth_classes]
-                    - label_id_offset, depth=model.num_classes)])
+                    - label_id_offset, depth=model.num_classes)],
+        groundtruth_masks_list, groundtruth_keypoints_list)
     losses_dict.update(model.loss(prediction_dict, true_image_shapes))
 
   result_dict = eval_util.result_dict_for_single_example(