Merge pull request #11489 from tensorflow:LakshmiKalaKadali-patch-1

PiperOrigin-RevId: 714042436

Author: tensorflower-gardener

Diff for: docs/vision/instance_segmentation.ipynb

@@ -479,9 +479,9 @@
         "\n",
         "Use the `retinanet_mobilenet_coco` experiment configuration, as defined by `tfm.vision.configs.maskrcnn.maskrcnn_mobilenet_coco`.\n",
         "\n",
-        "Please find all the registered experiements [here](https://www.tensorflow.org/api_docs/python/tfm/core/exp_factory/get_exp_config)\n",
+        "Please find all the registered experiments [here](https://www.tensorflow.org/api_docs/python/tfm/core/exp_factory/get_exp_config)\n",
         "\n",
-        "The configuration defines an experiment to train a Mask R-CNN model with mobilenet as backbone and FPN as decoder. Default Congiguration is trained on [COCO](https://cocodataset.org/) train2017 and evaluated on [COCO](https://cocodataset.org/) val2017.\n",
+        "The configuration defines an experiment to train a Mask R-CNN model with mobilenet as backbone and FPN as decoder. Default Configuration is trained on [COCO](https://cocodataset.org/) train2017 and evaluated on [COCO](https://cocodataset.org/) val2017.\n",
         "\n",
         "There are also other alternative experiments available such as\n",
         "`maskrcnn_resnetfpn_coco`,\n",
@@ -713,7 +713,7 @@
         "id": "dLcSHWjqgl66"
       },
       "source": [
-        "### Create Category Index Dictionary to map the labels to coressponding label names"
+        "### Create Category Index Dictionary to map the labels to corresponding label names"
       ]
     },
     {
@@ -734,7 +734,7 @@
       },
       "source": [
         "### Helper Function for Visualizing the results from TFRecords\n",
-        "Use `visualize_boxes_and_labels_on_image_array` from `visualization_utils` to draw boudning boxes on the image."
+        "Use `visualize_boxes_and_labels_on_image_array` from `visualization_utils` to draw bounding boxes on the image."
       ]
     },
     {
@@ -786,7 +786,7 @@
         "  2. Percentage of match between predicted and ground truth bounding boxes.\n",
         "  3. Instance Segmentation Mask\n",
         "\n",
-        "**Note**: The reason of everything is 100% is because we are visualising the groundtruth"
+        "**Note**: The reason of everything is 100% is because we are visualizing the groundtruth"
       ]
     },
     {