Model
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PeopleNet Transformer3 class object detection network to detect people in an image.
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| Field | Response |
|---|---|
| Intended Application(s) & Domain(s): | Segmenting people in smart spaces, retail, and industrial applications. |
| Model Type: | Instance segmentation |
| Intended Users: | Developers working in smart spaces, retail, and industrial applications with people. |
| Output: | Bounding Box(es), Category Label(s), Confidence Score(s) |
| Describe how the model works: | Detects and labels bags, faces, and persons within an image and returns bounding box coordinates, labels, and confidence scores for each category. |
| Technical Limitations: | Model should not be used in low-light, low contrast lighting conditions, with warped or motion-induced images, or 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: | This model may fail to properly detect people. |
| Licensing: | https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/ |