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Pose Estimation

Pose Estimation Node Documentation
The Pose Estimation node in AugeLab Studio is used to detect and estimate poses in input image data. It uses a pre-trained pose estimation model to detect various body parts and their positions in the image.
Node Overview
The Pose Estimation node detects poses in the input image and provides the positions of selected body parts. It supports visualization of the detected poses by drawing skeletons connecting the body parts. You can select the body parts to detect and visualize by enabling the corresponding checkboxes in the node's user interface.
Node Interaction
1.Drag and drop the Pose Estimation node from the node library onto the canvas in AugeLab Studio.
2.Connect the input image data to the node's input socket.
3.Optionally, connect a boolean value to the Show Skeleton input socket to control whether to show the skeleton overlay on the image.
4.Configure the node by selecting the desired body parts to detect and visualize from the available checkboxes in the node's user interface.
5.Run the pipeline or execute the node to process the input image and detect poses.
6.View the output image with the detected poses and visualize the selected body parts.
7.Retrieve the positions of the selected body parts from the Selected Body Part Positions output socket for further processing or analysis.
Implementation Details
The Pose Estimation node uses the OpenCV library for pose estimation. It loads a pre-trained model that is capable of detecting multiple body parts in an image. The node's implementation involves the following steps:
1.Initialization:
The node initializes the pose estimation model by loading the model files.
The node defines the number of body parts and the connections between them to form a skeleton.
The node sets up the network for pose estimation and configures its parameters.
2.User Interface:
The node provides a table view widget that displays the available body parts for detection and visualization.
The user can select the desired body parts by enabling the corresponding checkboxes in the table view.
The user can adjust the confidence threshold for pose detection using a slider widget.
3.Pose Estimation:
The node receives an input image and performs pose estimation using the pre-trained model.
It processes the image and generates a set of confidence maps for each body part.
It extracts the keypoints with high confidence from the confidence maps and maps them to the corresponding positions in the original image.
4.Skeleton Visualization:
The node draws skeletons connecting the selected body parts on the input image.
It uses the pre-defined connections between body parts to determine which lines to draw.
The user can control whether to show the skeleton overlay on the image by connecting a boolean value to the Show Skeleton input socket.
5.Output:
The node outputs the image with the detected poses and the positions of the selected body parts as a dictionary.
The dictionary maps each selected body part to its corresponding position in the image.
Usage
1.Drag and drop the Pose Estimation node from the node library onto the canvas in AugeLab Studio.
2.Connect the input image data to the node's input socket.
3.Optionally, connect a boolean value to the Show Skeleton input socket to control whether to show the skeleton overlay on the image.
4.Configure the node by selecting the desired body parts to detect and visualize from the available checkboxes in the node's user interface.
5.Run the pipeline or execute the node to process the input image and detect poses.
6.View the output image with the detected poses and visualize the selected body parts.
7.Retrieve the positions of the selected body parts from the Selected Body Part Positions output socket for further processing or analysis.
Notes
The Pose Estimation node provides a convenient way to detect and estimate poses in input image data.
The node uses a pre-trained model for pose estimation and supports detection of multiple body parts.
You can select the body parts to detect and visualize by enabling the corresponding checkboxes in the node's user interface.
The node outputs the image with the detected poses and the positions of the selected body parts.
You can adjust the confidence threshold for pose detection using the provided slider widget.
The node supports the visualization of detected poses by drawing skeletons connecting the body parts.
You can control whether to show the skeleton overlay on the image by connecting a boolean value to the Show Skeleton input socket.
The Pose Estimation node utilizes the OpenCV library for pose estimation and provides an interface for easy integration into AugeLab Studio pipelines.
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