This deep learning model is used to detect cars in high-resolution drone or aerial imagery. Car detection can be used for applications such as traffic management and analysis, parking lot utilization, urban planning, and so on. It can also be used as a proxy for deriving economic indicators and estimating retail sales. High-resolution aerial and drone imagery can be used for car detection due to its high spatiotemporal coverage.
To complete this workflow, the following are the license requirements:
- ArcGIS Desktop—ArcGIS Image Analyst extension for ArcGIS Pro
- ArcGIS Enterprise—ArcGIS Image Server
- ArcGIS Online—ArcGIS Image for ArcGIS Online
This model has the following characteristics:
- Input—Raster, mosaic dataset, or image service (5–20-centimeter spatial resolution).
- Output—Feature class containing bounding boxes depicting car locations.
- Compute—This workflow is compute intensive and a GPU with compute capability of 6.0 or higher is recommended.
- Applicable geographies—This model is designed to work well in the United States.
- Architecture—This model uses the MaskRCNN model architecture implemented in ArcGIS API for Python.
- Accuracy metrics—This model has an average precision score of 0.81.
Access and download the model
Download the Car Detection—USA pretrained model from ArcGIS Living Atlas of the World. Alternatively, access the model directly from ArcGIS Pro, or consume it in ArcGIS Image for ArcGIS Online.
- Browse to ArcGIS Living Atlas of the World.
- Sign in with your ArcGIS Online credentials.
- Search for Car Detection—USA and open the item page from the search results.
- Click the Download button to download the model.
You can use the downloaded .dlpk file directly in ArcGIS Pro, or upload and use it in ArcGIS Enterprise. Additionally, you can fine-tune the pretrained model if necessary.
The following are the release notes: