Model
Semantic segmentation of persons in an image.
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| Field | Response |
|---|---|
| Intended Application(s) & Domain(s): | Segmenting people in smart spaces, retail, industrial applications and for robotic navigation. |
| Model Type: | Semantic Segmentation |
| Intended Users: | Developers working in smart spaces, retail, and industrial applications with people. |
| Output: | Segmentation Masks |
| Describe how the model works: | Associates object class label for each image pixel. |
| Technical Limitations: | Model should not be used in low-light, low contrast lighting conditions, with warped or motion-induced images, and with very small and very large objects. Model accuracy may vary with occlusion or truncation. |
| Verified to have met prescribed NVIDIA standards: | Yes |
| Performance Metrics: | Accuracy, Intersection over Union(IoU), Precision, Recall |
| Potential Known Risks: | Inaccurate segmentation for robotic navigation could lead to collisions. Not recommended for life-critical use cases. |
| Licensing: | https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/ |