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Human action classification system with pose-based (MediaPipe) and video-based (3D CNN) models. Features 100+ architectures for real-time pose classification and temporal models pretrained on UCF-101/HMDB51. Applications include autonomous vehicles, video surveillance, and action recognition research.
Yoga Pose Detection using GANs and Real-Time Pose Estimation is a computer vision project that detects and classifies yoga poses from static images or webcam feeds. It uses GANs for data augmentation, keypoint detection models like OpenPose and PoseNet, and machine learning classifiers to evaluate pose accuracy and provide real-time feedback.