Project comparing auditory to visual attention

Visual folder : contain 4 scripts.

image_preprocess.ipynb: create arrayed figure for training to get the final layer parameter value, and also create the array figure for testing. Need to get access to ImageNet.
preprocess_image.ipynb: Get final layer parameter value for readout task. (The detection task weights is available on Dryad, also tunning value).
array_figure_mul_class.ipynb : Getting result for readout task.
vgg16_ObjectAttn.ipynb : Getting result for detection task.

Auditory folder : contain 5 scripts and one script folder:

script : The folder contain auditory pre-process (transfer auditory to numeric value (torch tensor)).
overall_script_auditory.ipynb: training final layer and getting tunning value for both detection and readout task.
get_grad_value.ipynb: Getting gradient value.
auditory_process.ipynb: The main forder for getting result for both detection and readout task.
pt_learn1.ipynb: Using perceptual learning method training MLP model to get attention mechanism.
pt_learn_test: Getting result for prceptual learning.