Share a deep learning model package

A deep learning model package (.dlpk) contains the files and data required to run deep learning inferencing tools for object detection or image classification. The package can be uploaded to your portal as a DLPK item and used as the input to deep learning raster analysis tools.

Deep learning model packages must contain an Esri model definition file (.emd) and a trained model file. The trained model file extension depends on the framework you used to train the model. For example, if you trained your model using TensorFlow, the model file will be a .pb file, while a model trained using Keras will generate an .h5 file. Depending on the model framework and options you used to train your model, you may need to include a Python Raster Function (.py) or additional files. You can include multiple trained model files in a single deep learning model package.

Create a deep learning model package

1. In the Package group on the Share tab, click Deep Learning.

   The Share As Deep Learning Package pane appears.

2. Specify where to save your package, either to your online account or as a file on disk.
3. Provide the name and, if saving the package to a file, the location for your new package on disk.
4. Complete the Summary and Tags fields.

   You can enter a maximum of 128 tags.

5. Provide the path to the .emd file for Model Definition.
6. Add the required items to include in Input.

   These can be files or folders, and must include the path to the trained model file (.pb, .h5, .pkl, and so on) at a minimum.

7. Click Analyze to check for errors and issues.

   Potential issues can include incorrect file paths, an invalid .emd file, and so on.

8. Once the inputs are validated, click Package to create the deep learning model package.

Deep learning model packages can be saved locally or stored on your portal as a DLPK item. You can use the local .dlpk file as the input to deep learning tools in ArcGIS Pro. You can use the DLPK item in your portal to run the raster analysis deep learning tools in Map Viewer Classic, ArcGIS API for Python, ArcGIS REST API, and ArcGIS Pro.