![]() ![]() The Train Point Cloud Classification Model tool trains a deep learning model for point cloud classification. A number of model types and arguments are available to configure the training process. The Train Deep Learning Model tool trains a deep learning model for imagery workflows using prepared training data. For more information on preparing and training point cloud data, see Train a deep learning model for point cloud classification. This tool creates many overlapping blocks of uncompressed HDF5 files used to train a point cloud. ![]() The Prepare Point Cloud Training Data tool creates data for training and validatingĪ convolutional neural network for point cloud classification. If you have existing labeled vector or raster data, you can use the Export Training Data For Deep Learning geoprocessing tool to generate the training data needed for the next step. You can interactively identify and label objects in an image, and export the training data as the image chips, labels, and statistics required to train a model. The Label Objects for Deep Learning pane is used to collect and generate labeled imagery datasets to train a deep learning model for imagery workflows. ![]() ![]() You must collect and provide training samples and input data, and then train the model so that it learns to recognize those features or objects. Training a deep learning model involves many of the same steps as training a traditional machine learning classification model. Model trainingīefore a deep learning model can be used to identify features or objects in an image, point cloud, or other dataset, it must first be trained to recognize those objects. Deep learning capabilities are available in ArcGIS Pro for imagery and point clouds through several tools and capabilities. ![]()
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