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Turn WiFi signals into real-time human pose estimation and detection
...It is designed to showcase the emerging field of RF-based sensing, where machine learning models interpret wireless channel data to reconstruct human movement and posture. The repository includes components for data processing, model inference, and real-time visualization, making it suitable for research and experimental deployments. Its architecture emphasizes performance and reproducibility, allowing developers to explore non-visual motion capture systems using accessible hardware. Overall, WiFi DensePose functions as an advanced research-grade toolkit for WiFi-based human sensing and pose estimation.
...It supports services such as ipfingerprints, spiderip, standingtech, viewdns, and yougetsignal. scanless can return raw scan output as well as parsed results that include port, state, service, and protocol details. The repository is archived and no longer maintained, so it is best treated as a legacy utility for authorized testing, research, or reference use.
...The receptive field of the TCN can be calculated. Once keras-tcn is installed as a package, you can take a glimpse of what is possible to do with TCNs. Some tasks examples are available in the repository for this purpose.