Add WiFi DensePose implementation and results
- Implemented the WiFi DensePose model in PyTorch, including CSI phase processing, modality translation, and DensePose prediction heads. - Added a comprehensive training utility for the model, including loss functions and training steps. - Created a CSV file to document hardware specifications, architecture details, training parameters, performance metrics, and advantages of the model.
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references/script_1.py
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references/script_1.py
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# Install required packages
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!pip install torch torchvision numpy scipy matplotlib
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print("Packages installed successfully!")
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