Run_Instructions.txt

To run the python files:

Insure you have these minimum packages installed:
	-Install pytorch and torchvision
	-pip install -r requirements.txt
These are the minimum requirements. We ran on higher versions with no issues.

Insure you have the datasets installed and saved somewhere locally. The folders should have the following format:
├── Data
    ├── NTU-Fi_HAR
    │   ├── test_amp
    │   ├── train_amp
    ├── NTU-Fi-HumanID
    │   ├── test_amp
    │   ├── train_amp
    ├── UT_HAR
    │   ├── data
    │   ├── label
    ├── Widardata
    │   ├── test
    │   ├── train

To run the code use the following command: python run.py --model [model name] --dataset [dataset name]

where [model name] is:
MLP
LeNet
ResNet18
ResNet50
ResNet101
RNN
GRU
LSTM
BiLSTM
CNN+GRU
ViT

and [dataset name] is:
UT_HAR_data
NTU-Fi-HumanID
NTU-Fi_HAR
Widar


Review the code if you are planning to downsample, the run.py, dataset.py, and whichever dataset_model.py file you are using i.e. if using NTU-Fi_HAR make the necessary edits to the NTU_Fi_model.py file. The code has been commented with where to edit depending on the input matrix size.




To run the matlab file:
Download the .m file and the dataset that can be found in the source document. In matlab pass the following command:
>>load('dataset_lab_276_dl.mat')
>>[net_info, perf] = signfi_cnn_example(csid_lab,label_lab)

Code has been commented with where to edit to downsample.

For additional help, contact Emmanuel Magana Mendez (emagana6622@ucla.edu) or Pooya Aghanoury (aghanoury@g.ucla.edu).