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image_metrics's Introduction

Associated publications

This repository currently provides a link to some of the modelling constraints introduced in--

Kar, K., Kubilius, J., Schmidt, K. M., Issa, E. B., & DiCarlo, J. J. (2019). Evidence that recurrent circuits are critical to the ventral stream's execution of core object recognition behavior. Nature Neuroscience .

Download the dataset

You can download the .h5 file from the location below***: click here

*** please note that this file will be soon updated.

Access the main material from the file

Once you download the dataset.h5 file, please check it using matlab (python users can also use this file) in the following way.

>>h5disp('dataset.h5')

HDF5 dataset.h5 
Group '/' 
    Dataset 'i1' 
        Size:  1320x1
        MaxSize:  1320x1
        Datatype:   H5T_IEEE_F64LE (double)
        ChunkSize:  []
        Filters:  none
        FillValue:  0.000000
    Dataset 'images' 
        Size:  256x256x3x1320
        MaxSize:  256x256x3x1320
        Datatype:   H5T_IEEE_F64LE (double)
        ChunkSize:  []
        Filters:  none
        FillValue:  0.000000
    Dataset 'obj' 
        Size:  1320x1
        MaxSize:  1320x1
        Datatype:   H5T_IEEE_F64LE (double)
        ChunkSize:  []
        Filters:  none
        FillValue:  0.000000
    Dataset 'ost' 
        Size:  1320x1
        MaxSize:  1320x1
        Datatype:   H5T_IEEE_F64LE (double)
        ChunkSize:  []
        Filters:  none
        FillValue:  0.000000

The objects are numbered 1-10. Here's the lookup table

1. 'bear'
2. 'elephant'
3. 'person'
4.  'car'
5.  'dog'
6.  'apple'
7.  'chair'
8.  'plane'
9.  'bird'
10.  'zebra'

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