Adding panoptic evaluation tools and update internal changes. (#6320)

* Internal changes

PiperOrigin-RevId: 237183552

* update readme

PiperOrigin-RevId: 237184584

research/deeplab/export_model.py

@@ -129,10 +129,10 @@ def main(unused_argv):
           model_options=model_options,
           eval_scales=FLAGS.inference_scales,
           add_flipped_images=FLAGS.add_flipped_images)
-
-    predictions = tf.cast(predictions[common.OUTPUT_TYPE], tf.float32)
+    raw_predictions = tf.identity(
+        tf.cast(predictions[common.OUTPUT_TYPE], tf.float32),
+        _RAW_OUTPUT_NAME)
     # Crop the valid regions from the predictions.
-    raw_predictions = tf.identity(predictions, _RAW_OUTPUT_NAME)
     semantic_predictions = tf.slice(
         raw_predictions,
         [0, 0, 0],

research/deeplab/g3doc/installation.md

@@ -26,8 +26,9 @@ The remaining libraries can be installed on Ubuntu 14.04 using via apt-get:
 
 ```bash
 sudo apt-get install python-pil python-numpy
-sudo pip install jupyter
-sudo pip install matplotlib
+pip install --user jupyter
+pip install --user matplotlib
+pip install --user PrettyTable
 ```
 
 ## Add Libraries to PYTHONPATH
@@ -38,7 +39,13 @@ tensorflow/models/research/:
 
 ```bash
 # From tensorflow/models/research/
-export PYTHONPATH=$PYTHONPATH:`pwd`
+export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim
+
+# [Optional] for panoptic evaluation, you might need panopticapi:
+# https://github.com/cocodataset/panopticapi
+# Please clone it to a local directory ${PANOPTICAPI_DIR}
+touch ${PANOPTICAPI_DIR}/panopticapi/__init__.py
+export PYTHONPATH=$PYTHONPATH:${PANOPTICAPI_DIR}/panopticapi
 ```
 
 Note: This command needs to run from every new terminal you start. If you wish

research/deeplab/train.py

@@ -485,6 +485,7 @@ def main(unused_argv):
             config=session_config,
             scaffold=scaffold,
             checkpoint_dir=FLAGS.train_logdir,
+            summary_dir=FLAGS.train_logdir,
             log_step_count_steps=FLAGS.log_steps,
             save_summaries_steps=FLAGS.save_summaries_secs,
             save_checkpoint_secs=FLAGS.save_interval_secs,