How to parse the heatmap output for the pose estimation tflite model?

Written by- Aionlinecourse798 times views

The output of a heatmap for pose estimation can be parsed by first understanding the structure of the heatmap and the layout of the body joints it represents.

A heatmap is a 2D array of values that represent the confidence of a particular body joint being at each point in the image. The heatmap is typically normalized so that the maximum value corresponds to the most confident location for the joint.

To parse the heatmap, you will need to locate the maximum value in the heatmap for each body joint. This can be done using the argmax function in Python or by manually searching through the heatmap for the maximum value. Once the maximum value has been found, the (x, y) coordinates of the point can be extracted and used to estimate the location of the body joint in the image.

It may also be necessary to apply some post-processing to the heatmap to refine the location of the body joints. This can include techniques such as peak suppression and joint interpolation.

It's also important to note that the output of the heatmap will depend on the specific architecture and training of the pose estimation model. It's always a good idea to refer to the documentation for the specific model you are using to understand the structure and layout of the heatmap output.