Tf-GCZSL

Paper: Task-free Generalized Continual Zero-shot Learning (Tf-GCZSL) (Neural Network, 2022)

Link: https://www.sciencedirect.com/science/article/abs/pii/S0893608022003343

To run the code for task-agnostic setting follow the following instructions:

1. Go to 'tfgczsl_task_agnostic' folder
2. First run the 'data_loader.py' script to process the data.
3. Run the 'tfgczsl.py' to get the results in .csv file. (Harmonic Mean, Seen Accuracy, Unseen Accuracy)

Note:

  * The path variable must be changed to point to the dataset location. (CUB Dataset)

  * The Dataset can be downloaded from https://www.dropbox.com/sh/mrofy57ci4jcmx5/AACeN9zNpAe_ZyNi0_iouASma?dl=0 

  * For Without DER set 'use_der' variable in 'tfgczsl.py' to False 

To run the code for task_free setting follow the following instructions:

1. Go to the 'tfgczsl_taskfree' folder
2. First run the 'data_loader.py' script to process the data.
3. Run 'TFGCZSL_STG1_MB.py' to get the results for M_b setting in a .csv file.(Harmonic Mean, Seen Accuracy, Unseen Accuracy)
4. Run 'TFGCZSL_STG2_MST.py' to get the results for M_st setting in a .csv file.(Harmonic Mean, Seen Accuracy, Unseen Accuracy)

Note:

  * The path variable must be changed to point to the dataset location. (CUB Dataset)
  
  * The Dataset can be downloaded from https://www.dropbox.com/sh/mrofy57ci4jcmx5/AACeN9zNpAe_ZyNi0_iouASma?dl=0
  
  * For Without DER set 'use_der' variable in 'TFGCZSL_STG1_MB.py' and 'TFGCZSL_STG2_MST.py' to False