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Typos fixed in instance_segmentation.ipynb #11489

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LakshmiKalaKadali merged 1 commit into from
Jan 10, 2025
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Typos fixed in instance_segmentation.ipynb #11489

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10 changes: 5 additions & 5 deletions docs/vision/instance_segmentation.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -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",
Expand Down Expand Up @@ -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"
]
},
{
Expand All @@ -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."
]
},
{
Expand Down Expand Up @@ -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"
]
},
{
Expand Down