> For the complete documentation index, see [llms.txt](https://nx.docs.scailable.net/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://nx.docs.scailable.net/ai-manager-v6.1.4/ai-models-support/default-models/people-low.md).

# People (Low)

This AI model, based on Yolov4, is trained to detect people in a given image. It runs at a lower input resolution than the [High Accuracy variant](/ai-manager-v6.1.4/ai-models-support/default-models/people-high.md), trading detection accuracy for lower compute requirements. Use this model when frame rate or hardware resources matter more than catching every person, especially small or distant ones.

## Input

The input tensor dimension for this model is 320 wide by 320 high.

This model accepts the following extra input information:

* Mask: excludes or includes a specific region of the camera view.
* Sensitivity threshold: NMS sensitivity.

## Output

Each detected person is identified using a bounding box represented by a vector: \[x1, y1, x2, y2, score, class]. The object bounding boxes contain the following information:

* Position and size coordinates, to be used as a rectangular bounding box.
* A confidence score, which helps retain only the most confident and accurate detections while suppressing weaker or redundant ones.
* Class, in this case always "Person".

The following image shows an example of this model's output:

<figure><img src="/files/A2WVn03p9Wv2Jf0EYBgq" alt="Camera view with bounding boxes labeling four people"><figcaption><p>Example people detection output in the desktop client</p></figcaption></figure>

## Postprocessors

This model's detections can be combined with any of the built-in postprocessors, for example:

* [Loitering Detection](/ai-manager-v6.1.4/ai-manager-plugin/configure-the-plugin/postprocessors/loitering-detection.md): detect when an object stays in frame longer than a configured time threshold.
* [Left Behind Object Detection](/ai-manager-v6.1.4/ai-manager-plugin/configure-the-plugin/postprocessors/left-behind-object-detection.md): detect objects left behind or removed compared to a reference frame.
* [Line Crossing Detection](/ai-manager-v6.1.4/ai-manager-plugin/configure-the-plugin/postprocessors/line-crossing-detection.md): detect or count objects that cross a defined line, and generate an event.
* [Object Counting](/ai-manager-v6.1.4/ai-manager-plugin/configure-the-plugin/postprocessors/object-counting.md): count bounding boxes per class and generate a counting event.

See [Postprocessors](/ai-manager-v6.1.4/ai-manager-plugin/configure-the-plugin/postprocessors.md) for the full list and configuration details.