Training and test data, plus saved models for the upcoming paper `Top-down perceptual inference shaping the activity of early visual cortex'

Each .pkl file contains a training or test dataset in the form of a Python dictionary (generated with Python 3.8.5) with the following fields:

'train_images': 640,000 float32 images used for model training. These are 40px images that contain 1600 pixel intensities each.
'train_labels': float32 labels for each image in 'train_images'. All natural images are labeled with 0.0. Texture images are labeled with 0.0, 1,0, 2.0, 3.0, or 4.0, according to their texture family.
'test_images': 64,000 float32 images used for model testing. These are 40px images that contain 1600 pixel intensities each.
'test_labels': float32 labels for each image in 'test_images'. All natural images are labeled with 0.0. Texture images are labeled with 0.0, 1,0, 2.0, 3.0, or 4.0, according to their texture family.
The .zip file contains a saved model snapshot and various intermediate evaluative data. Details on these are coming soon.