Available with Image Analyst license.
The Deep Learning toolset contains tools to detect specific features in an image or to classify pixels in a raster dataset.
Deep learning is a type of machine learning artificial intelligence that detects features in imagery using multiple layers in neural networks where each layer is capable of extracting one or more unique features in the image. The tools in the Deep Learning toolset take advantage of GPU processing to perform analysis in a timely manner.
These ArcGIS Pro tools consume the models that have been trained to detect specific features in third-party deep learning frameworks—such as TensorFlow, CNTK, and PyTorch—and output features or class maps.
The following table lists the available deep learning tools and provides a brief description of each:
Runs a trained deep learning model on an input raster and an optional feature class to produce a feature class or table in which each input object has an assigned class label.
Runs a trained deep learning model on an input raster to produce a classified raster, with each valid pixel having an assigned class label.
Runs a trained deep learning model on an input raster to produce a feature class containing the objects it finds. The features can be bounding boxes or polygons around the objects found, or points at the centers of the objects.
The trained deep learning model package consists of an Esri model definition JSON file (.emd). It contains the path to the Python raster function to be called to process each raster tile and the path to the trained binary deep learning model file created from third-party training software such as TensorFlow or PyTorch.
Uses a remote sensing image to convert labeled vector or raster data into deep learning training datasets. The output is a folder of image chips and a folder of metadata files in the specified format.
Identifies duplicate features from the output of the Detect Objects Using Deep Learning tool as a postprocessing step and creates a new output with no duplicate features. The Detect Objects Using Deep Learning tool can return more than one bounding box or polygon for the same object, especially as a tiling side effect. If two features overlap more than a given maximum ratio, the feature with the lower confidence value will be removed.
Trains a deep learning model using the output from the Export Training Data For Deep Learning tool.