Face Detection

This function block allows users to detect faces within an input image using a trained face detection model. It provides outputs such as the modified image with detected faces highlighted, their coordinates, and the total count of detected faces.

📥 Inputs

Image Any The input must be an image in which faces need to be detected.

📤 Outputs

Image Any The output image with detected faces highlighted.

Face Area Coordinates The coordinates of the areas where faces have been detected.

Face Count An output indicating the total number of faces detected in the image.

🕹️ Controls

Confidence Threshold % A slider that allows you to set the confidence level for face detection. Increasing this threshold may result in fewer but more confident detections.

🎨 Features

Real-time Face Detection The block processes the input image to identify and highlight faces dynamically.

Confidence Level Adjustment Users can fine-tune the detection sensitivity by adjusting the confidence threshold.

Output Summary Provides both qualitative (highlighted image) and quantitative (coordinates and count) results of the detection process.

📝 Usage Instructions

1. Input Image: Connect an image source containing the faces you want to detect to the input socket.

2. Set Confidence Level: Use the Confidence Threshold % slider to adjust the sensitivity of the face detection.

3. Evaluate: Run the block to perform face detection on the input image. The result will include the modified image, coordinates of detected faces, and the total count.

📊 Evaluation

The block outputs a new image marked with detected face locations, alongside coordinates and a count of the detected faces within the provided input image.

💡 Tips and Tricks

Increasing Detection Accuracy

To improve detection accuracy, ensure that the input image is of high quality and well-lit. You can preprocess your image to increase its clarity or reduce noise.

Multifaceted Image Source

Using an array of function blocks, such as Camera USB or Load Image, you can dynamically supply images for real-time face detection.

Multiple Faces

The block is capable of detecting multiple faces in the same image. Ensure your confidence threshold is set appropriately to capture all desired faces.

🛠️ Troubleshooting

No Faces Detected

If no faces are detected, try lowering the confidence threshold using the slider to allow for more flexible detections. Ensure the input image is clear and faces are not obscured.

Error Handling

If there are errors related to image input, check that the image data is valid and properly formatted before feeding it into the block.