changes made based on suggestions by Suraj
"cell_type": "markdown",
"metadata": {},
"source": [
- "Deep learning based Object Detection models in arcgis.learn can be used to detect objects of interest. The [Object detection with arcgis.learn](https://developers.arcgis.com/python/guide/object-detection/) guide details how we can train such models and use them for detecting objects. Deep learning based Object Tracking models in arcgis.learn can be used to track objects, given the location of the target object in the first frame of the sequence. The [Track Objects using SiamMask]() guide details how we can train such models and use them for tracking objects. This guide describes the usage of ObjectTracker class in arcgis.learn which pairs Object Detection models and Object Tracking models to enable Deep Learning powered multi-object tracking. "
+ "Deep learning based Object Detection models in arcgis.learn can be used to detect objects of interest. The [Object detection with arcgis.learn](https://developers.arcgis.com/python/guide/object-detection/) guide details how we can train such models and use them to detect objects. Deep learning based Object Tracking models in arcgis.learn can be used to track objects, given the location of the target object in the first frame of the sequence. The [Track Objects using SiamMask]() guide details how we can train such models and use them to track objects. \n",
+ "This guide describes the usage of **ObjectTracker** class in arcgis.learn which pairs Object Detection models and Object Tracking models to enable Deep Learning powered multi-object tracking. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Depending on the use-case, we select the appropriate object detection model from the list of models available in arcgis.learn. We follow the steps outlined in [Object detection with arcgis.learn](https://developers.arcgis.com/python/guide/object-detection/) guide to train a model for the targeted use-case."
+ "Based on the use-case, we select the appropriate object detection model from the list of models available in arcgis.learn. The steps outlined in the [Object detection with arcgis.learn](https://developers.arcgis.com/python/guide/object-detection/) guide are followed to train a model for the targeted use-case."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "***Step 3*** Init/Use ObjectTracker"
+ "***Step 3*** Initialize and track objects using **ObjectTracker**"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "ObjectTracker class helps us use Object Detector model trained in Step 1 and Object Tracking model trained in Step 2 together. We can load the trained models using the respective model classes and use the model instances to create ObjectTracker instance. To use the ObjectTracker instance, initialize the required/optional parameters and call the init/update methods as described below."
+ "The ObjectTracker class lets us use Object Detector model trained in *Step 1* and Object Tracking model trained in *Step 2* together.\n",
+ "We can load the trained models using their respective model classes and use the model instances to create an ObjectTracker instance. To use the ObjectTracker instance, initialize the required/optional parameters and call the init/update methods as described below."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Import the Object Detection Model class and from Object Tracking Model class from arcgis.learn module."
+ "Import the Object Detection model class and Object Tracking model class from arcgis.learn module."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Tracker Options refers to a set of parameters which can be initialized to values based on the specific application. If not initialized, the parameters take default values. Following are the parameters: "
+ "*Tracker Options* refers to a set of parameters which can be initialized to values based on the specific application. If not initialized, the parameters are set to default values."
]
},
{
"\n",
"The method returns list of initialized tracks\n",
" \n",
- "**Note** Whenever detections and labels are passed, the length of detections should match the length of labels"
+ "**Note:** Each time detections and labels are passed, the length of the detections must match to the length of the tags."
]
},
{
