Welcome to ECE-GY-9313-Telecom-Network course project

Datasets: AWF, DF, DC, USTC, CSTNet-tls

Openset methods

• K-LND methods
• OpenMax
• Background class

Using guide

First, clone the git repo and install the requirements.

git clone https://github.com/zhanglejun02/ECE-GY-9313-Telecom-Network.git
cd ECE-GY-9313-Telecom-Network
pip install -r requirements.txt

Next, download the dataset and place it in the data directory.

gdown https://drive.google.com/uc?id=1-MVfxyHdQeUguBmYrIIw1jhMVSqxXQgO
unzip data.zip 

Then, preprocess the dataset you want to train and evaluate. Here, the dataset name should be DF, AWF, DC, USTC, or CSTNet.

python3 data_preprocess.py --data_path ./data --dataset <dataset_name>

To train the model, run the suitable code for the dataset:

python3 train.py --max_len 1024 --batch_size 12 --epochs 3 --num_labels 60  --dataset DF
python3 train.py --max_len 1024 --batch_size 12 --epochs 3 --num_labels 200  --dataset AWF
python3 train.py --max_len 1024 --batch_size 12 --epochs 3 --num_labels 4  --dataset DC
python3 train.py --max_len 1024 --batch_size 12 --epochs 3 --num_labels 12  --dataset USTC
python3 train.py --max_len 1024 --batch_size 12 --epochs 3 --num_labels 75  --dataset CSTNet

To evaluate, run the suitable code for the dataset:

python3 evaluate.py --max_len 1024 --batch_size 12 --epochs 3 --num_labels 60 --K_number 30 --TH_value 0.8 --dataset DF
python3 evaluate.py --max_len 1024 --batch_size 12 --epochs 3 --num_labels 200 --K_number 50 --TH_value 0.9 --dataset AWF
python3 evaluate.py --max_len 1024 --batch_size 12 --epochs 3 --num_labels 4 --K_number 4 --TH_value 0.9 --dataset DC
python3 evaluate.py --max_len 1024 --batch_size 12 --epochs 3 --num_labels 12 --K_number 5 --TH_value 0.8 --dataset USTC
python3 evaluate.py --max_len 1024 --batch_size 12 --epochs 5 --num_labels 75 --K_number 20 --TH_value 0.8 --dataset CSTNe