MediaPipe-Pose-Estimation
Detect and track human face, hand, and torso in real‑time images and video streams.
The MediaPipe Pose Landmark Detector is a machine learning pipeline that predicts bounding boxes and pose skeletons of the face, hands, and torso in an image.
Not supported
This model is currently not supported on any IoT chipset.
To see performance metrics for this model on other chipsets, click the button below.
View for other chipsetsTechnical Details
Input resolution:256x256
Number of parameters (pose_detector):815K
Model size (pose_detector) (float):3.14 MB
Number of parameters (pose_landmark_detector):3.36M
Model size (pose_landmark_detector) (float):12.9 MB
Applicable Scenarios
- Accessibility
- Augmented Reality
- ARVR
License
Model:APACHE-2.0
Tags
- real-time
Supported IoT Devices
- Dragonwing IQ-9075 EVK
- Dragonwing IQ-X5121
- Dragonwing IQ-X7181
- Dragonwing Q-6690 MTP
- Dragonwing Q-7790
- Dragonwing Q-8750
- Dragonwing RB3 Gen 2 Vision Kit
- QCS8275 (Proxy)
- QCS8550 (Proxy)
Supported IoT Chipsets
- Qualcomm® QCM6690
- Qualcomm® QCS6490
- Qualcomm® QCS8275 (Proxy)
- Qualcomm® QCS8550 (Proxy)
- Qualcomm® QCS9075
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