Human Pose Estimation using OpenCV, Deep Learning and Python

6,000.00

Human Pose Estimation using OpenCV, Deep Learning and Python

100 in stock

SKU: Human Pose Estimation using OpenCV, Deep Learning and Python Categories: ,

Description

Human Pose Estimation using OpenCV, Deep Learning and Python

In this project, we have used Multi-Person Pose Estimation model,

The detection takes place in three stages :

  1. Stage 0: The first 10 layers of the VGGNet are used to create feature maps for the input image.
  2. Stage 1: A 2-branch multi-stage CNN is used where the first branch predicts a set of 2D confidence maps (S) of body part locations ( e.g. elbow, knee etc.). Given below are confidence maps and Affinity maps for the keypoint – Left Shoulder.
  3. Stage 2: The confidence and affinity maps are parsed by greedy inference to produce the 2D keypoints for all people in the image.

Additional information

Weight 1.000000 kg

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