added panoptic fpn results in separate subsection

official/vision/beta/projects/panoptic_maskrcnn/README.md

@@ -5,7 +5,7 @@
 Panoptic Segmentation combines the two distinct vision tasks - semantic
 segmentation and instance segmentation. These tasks are unified such that, each
 pixel in the image is assigned the label of the class it belongs to, and also
-the instance identifier of the object it a part of.
+the instance identifier of the object it is a part of.
 
 ## Environment setup
 The code can be run on multiple GPUs or TPUs with different distribution
@@ -73,8 +73,9 @@ $ python3 train.py \
   --model_dir $MODEL_DIR \
   --params_override=$OVERRIDES
 ```
-**Note**: The [PanopticSegmentationGenerator](https://github.com/tensorflow/models/blob/ac7f9e7f2d0508913947242bad3e23ef7cae5a43/official/vision/beta/projects/panoptic_maskrcnn/modeling/layers/panoptic_segmentation_generator.py#L22) layer uses dynamic shapes and hence generating panoptic masks is not supported on Cloud TPUs. Running evaluation on Cloud TPUs is not supported for the same reason. However, training is both supported on Cloud TPUs and GPUs.
+**Note**: The [PanopticSegmentationGenerator](https://github.com/tensorflow/models/blob/ac7f9e7f2d0508913947242bad3e23ef7cae5a43/official/vision/beta/projects/panoptic_maskrcnn/modeling/layers/panoptic_segmentation_generator.py#L22) layer uses dynamic shapes and hence generating panoptic masks is not supported on Cloud TPUs. Running evaluation on Cloud TPUs is not supported for the same reason. However, training is supported on both Cloud TPUs and GPUs.
 ## Pretrained Models
+### Panoptic FPN
 Backbone     | Schedule     | Experiment name             | Box mAP |  Mask mAP  | Overall PQ | Things PQ | Stuff PQ | Checkpoints
 :------------| :----------- | :---------------------------| ------- | ---------- | ---------- | --------- | -------- | ------------:
 ResNet-50    | 1x           | `panoptic_fpn_coco`         | 38.19   |   34.25    |   39.14    |  45.42    |  29.65   | [ckpt]()