> For the complete documentation index, see [llms.txt](https://docs.augelab.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.augelab.com/function-blocks/blocks-reference/ai-blocks/face-detection.md).

# Face Detection

This function block detects human faces in an input image and returns visual and numeric results for downstream processing.

## 📥 Inputs <a href="#inputs" id="inputs"></a>

`Image Any` The image to analyze for faces (color or grayscale). Provide frames from cameras or loaded images.

## 📤 Outputs <a href="#outputs" id="outputs"></a>

`Image Any` Annotated image with detected face boxes drawn.

`Face Area Coordinates` List of rectangle coordinates for each detected face.

`Face Count` Number of faces detected in the input image.

## 🕹️ Controls <a href="#controls" id="controls"></a>

`Confidence Threshold %` A slider to set minimum detection confidence. Increase to reduce false positives, decrease to be more permissive.

## ✨ Features <a href="#features" id="features"></a>

* Real-time face detection suitable for live camera frames or static images.
* Returns both visual feedback (annotated image) and structured data (coordinates and count) for downstream logic.
* Adjustable confidence level to control detection strictness.

## 📝 Usage Instructions <a href="#usage" id="usage"></a>

1. Connect an image-producing block (camera or file loader) to the `Image Any` input.
2. Adjust the `Confidence Threshold %` slider to the desired sensitivity.
3. Use the outputs as needed:
   * Preview the annotated image via a display block.
   * Read `Face Area Coordinates` for ROI processing or tracking.
   * Use `Face Count` for alerts, logging or simple analytics.

## 📊 Evaluation <a href="#evaluation" id="evaluation"></a>

When the block runs, it scans the incoming image for faces above the configured confidence and produces the annotated image, a list of face rectangles, and the detected face count.

## 💡 Tips and Tricks <a href="#tips-and-tricks" id="tips-and-tricks"></a>

* For visual inspection, connect this block output to the `Show Image` block to open the image viewer and inspect detections.
* If you only need to monitor one area (e.g., doorway), crop first with `Image ROI Select` to reduce false positives and speed up processing.
* To reduce CPU usage or increase processing speed, insert `Image Resize` before this block to lower frame size.
* Use `Draw Detections` to combine detection rectangles with custom overlays or status text for clearer on-screen results.
* Save examples of successful or failed detections with `Image Logger` for offline review and tuning.
* Preprocess noisy inputs with `Blur` or a thresholding block (like `Image Threshold`) to improve detection stability in low-quality images.

## 🛠️ Troubleshooting <a href="#troubleshooting" id="troubleshooting"></a>

* No faces detected: Lower the `Confidence Threshold %` and ensure the image contains clear frontal or slightly angled faces. Try increasing image contrast or use `Image Resize` to a sensible working size.
* Too many false positives: Increase `Confidence Threshold %` and crop the scene with `Image ROI Select` to exclude irrelevant areas.
* Performance issues: Reduce input resolution with `Image Resize` or run detection only on selected frames using a control signal or batching strategy.