Merge pull request #11152 from tensorflow:sineeli-patch-16

PiperOrigin-RevId: 603518825

Author: tensorflower-gardener

docs/vision/semantic_segmentation.ipynb

@@ -39,20 +39,20 @@
       "source": [
         "# Semantic Segmentation with Model Garden\n",
         "\n",
-        "\u003ctable class=\"tfo-notebook-buttons\" align=\"left\"\u003e\n",
-        "  \u003ctd\u003e\n",
-        "    \u003ca target=\"_blank\" href=\"https://www.tensorflow.org/tfmodels/vision/semantic_segmentation\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" /\u003eView on TensorFlow.org\u003c/a\u003e\n",
-        "  \u003c/td\u003e\n",
-        "  \u003ctd\u003e\n",
-        "    \u003ca target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/models/blob/master/docs/vision/semantic_segmentation.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /\u003eRun in Google Colab\u003c/a\u003e\n",
-        "  \u003c/td\u003e\n",
-        "  \u003ctd\u003e\n",
-        "    \u003ca target=\"_blank\" href=\"https://github.com/tensorflow/models/blob/master/docs/vision/semantic_segmentation.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /\u003eView on GitHub\u003c/a\u003e\n",
-        "  \u003c/td\u003e\n",
-        "  \u003ctd\u003e\n",
-        "    \u003ca href=\"https://storage.googleapis.com/tensorflow_docs/models/docs/vision/semantic_segmentation.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/download_logo_32px.png\" /\u003eDownload notebook\u003c/a\u003e\n",
-        "  \u003c/td\u003e\n",
-        "\u003c/table\u003e"
+        "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
+        "  <td>\n",
+        "    <a target=\"_blank\" href=\"https://www.tensorflow.org/tfmodels/vision/semantic_segmentation\"><img src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" />View on TensorFlow.org</a>\n",
+        "  </td>\n",
+        "  <td>\n",
+        "    <a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/models/blob/master/docs/vision/semantic_segmentation.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />Run in Google Colab</a>\n",
+        "  </td>\n",
+        "  <td>\n",
+        "    <a target=\"_blank\" href=\"https://github.com/tensorflow/models/blob/master/docs/vision/semantic_segmentation.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />View on GitHub</a>\n",
+        "  </td>\n",
+        "  <td>\n",
+        "    <a href=\"https://storage.googleapis.com/tensorflow_docs/models/docs/vision/semantic_segmentation.ipynb\"><img src=\"https://www.tensorflow.org/images/download_logo_32px.png\" />Download notebook</a>\n",
+        "  </td>\n",
+        "</table>"
       ]
     },
     {
@@ -95,7 +95,7 @@
       },
       "outputs": [],
       "source": [
-        "!pip install -U -q \"tensorflow\u003e=2.9.2\" \"tf-models-official\""
+        "!pip install -U -q \"tf-models-official\""
       ]
     },
     {
@@ -138,6 +138,7 @@
         "import orbit\n",
         "import tensorflow_models as tfm\n",
         "from official.vision.data import tfrecord_lib\n",
+        "from official.vision.utils import summary_manager\n",
         "from official.vision.serving import export_saved_model_lib\n",
         "from official.vision.utils.object_detection import visualization_utils\n",
         "\n",
@@ -428,7 +429,8 @@
         "exp_config.task.validation_data.output_size = [HEIGHT, WIDTH]\n",
         "exp_config.task.validation_data.preserve_aspect_ratio = False\n",
         "exp_config.task.validation_data.groundtruth_padded_size = [HEIGHT, WIDTH]\n",
-        "exp_config.task.validation_data.seed = 21 # Reproducable Validation Data"
+        "exp_config.task.validation_data.seed = 21 # Reproducable Validation Data\n",
+        "exp_config.task.validation_data.resize_eval_groundtruth = True # To enable validation loss"
       ]
     },
     {
@@ -540,7 +542,7 @@
       "source": [
         "## Create the `Task` object (`tfm.core.base_task.Task`) from the `config_definitions.TaskConfig`.\n",
         "\n",
-        "The `Task` object has all the methods necessary for building the dataset, building the model, and running training \u0026 evaluation. These methods are driven by `tfm.core.train_lib.run_experiment`."
+        "The `Task` object has all the methods necessary for building the dataset, building the model, and running training & evaluation. These methods are driven by `tfm.core.train_lib.run_experiment`."
       ]
     },
     {
@@ -597,7 +599,7 @@
       },
       "outputs": [],
       "source": [
-        "def display(display_list):\n",
+        "def plot_masks(display_list):\n",
         "  plt.figure(figsize=(15, 15))\n",
         "\n",
         "  title = ['Input Image', 'True Mask', 'Predicted Mask']\n",
@@ -636,7 +638,7 @@
         "num_examples = 3\n",
         "\n",
         "for images, masks in task.build_inputs(exp_config.task.train_data).take(num_examples):\n",
-        "  display([images[0], masks['masks'][0]])"
+        "  plot_masks([images[0], masks['masks'][0]])"
       ]
     },
     {
@@ -657,12 +659,15 @@
       },
       "outputs": [],
       "source": [
+        "\n",
         "model, eval_logs = tfm.core.train_lib.run_experiment(\n",
         "    distribution_strategy=distribution_strategy,\n",
         "    task=task,\n",
         "    mode='train_and_eval',\n",
         "    params=exp_config,\n",
         "    model_dir=model_dir,\n",
+        "    eval_summary_manager=summary_manager.maybe_build_eval_summary_manager(\n",
+        "              params=exp_config, model_dir=model_dir),\n",
         "    run_post_eval=True)"
       ]
     },
@@ -764,7 +769,7 @@
         "  image = tf.cast(image, dtype=tf.uint8)\n",
         "  mask = tf.image.resize(record['segmentation_mask'], size=[HEIGHT, WIDTH])\n",
         "  predicted_mask = model_fn(tf.expand_dims(record['image'], axis=0))\n",
-        "  display([image, mask, create_mask(predicted_mask['logits'])])"
+        "  plot_masks([image, mask, create_mask(predicted_mask['logits'])])"
       ]
     }
   ],