Pose Estimation

This function block detects human body keypoints and (optionally) draws a skeleton on incoming images. Use it to extract selected body part positions for analytics, logging, or visualization.

📥 Inputs

Image Any The image to analyze (camera frame, loaded image, or preprocessed image).

Show Skeleton Boolean input to enable or disable drawing the skeleton on the output image.

📤 Outputs

Image Any The image with skeleton drawn (if Show Skeleton is enabled) and visual markers for detected keypoints.

Selected Body Part Positions A dictionary-like result mapping selected body part names to their detected positions (x, y). Only the body part groups you choose are returned.

🕹️ Controls

Class Names A selectable list of simplified body-part groups (for example: head, chest, elbow, hand, hip, knee, foot). Check the groups you want the block to report.

Confidence A slider to adjust detection confidence. Increasing value reduces false positives but may miss faint detections; lowering it makes detection more permissive.

⚙️ Running mechanism

• When an image is provided at Image Any, the block analyzes the image and tries to locate human keypoints.

• If Show Skeleton is TRUE, the block overlays the skeleton lines and markers on the output image.

• The block returns the annotated image and a mapping of the selected body part names to their detected positions. If a part is not confidently detected it will be omitted from the mapping.

🎯 Features

• Visual skeleton overlay for quick inspection.

• Selectable body-part groups to limit outputs to only the parts you need.

• Adjustable confidence control to balance sensitivity vs. false detections.

• Real-time friendly for live camera streams when paired with the appropriate image input block.

📝 Usage instructions

1. Provide an image source into Image Any (for example: Camera USB, Load Image, or Stream Reader).

2. Choose which body-part groups to output using Class Names.

3. Adjust detection sensitivity using the Confidence slider.

4. Optionally send a boolean into Show Skeleton to enable/disable skeleton drawing.

5. View the result image with Show Image or save/log positions for downstream use.

💡 Tips and Tricks

• Use Camera USB as a live image source when working with real-time scenes.

• Resize incoming images with Image Resize if the people appear too small — larger person pixels improve keypoint accuracy.

• Run a fast detector first (for example Object Detection) and then crop persons with Image ROI to feed individual person images to this block — this can increase reliability and lower processing cost.

• To preview results in your workspace, connect this block to Show Image.

• Save frames containing detections using Image Logger or export coordinates with Data to JSON or CSV Export for later analysis.

• Combine with Draw Result On Image or Draw Detections to annotate additional status text or bounding boxes together with skeletons.

🛠️ Troubleshooting

• No keypoints detected: try lowering the Confidence value or increase input image size with Image Resize.

• False or jittery keypoints: increase the Confidence slider and improve lighting or sharpness (use Blur carefully only to remove noise).

• People partially out of frame: use an upstream detection/cropping workflow (for example Object Detection → Image ROI) so the subject is centered before running this block.

• Slow performance: reduce input resolution with Image Resize or process cropped person regions instead of full-frame images.

If you need to log or visualize results, use the suggested combinations under Tips and Tricks to build a robust pipeline.