---
layout: default
title: 64x64x3 Convolutional Neural Network
permalink: /gallery/ILSVRC2012/Pear
---

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## ILSVRC2012 Classification: 64x64x3 Convolutional Neural Network (50.08% top 1 accuracy, 74.74% top 5 accuracy, 85ms/frame on Raspberry Pi 3 (Raspbian) @ 700MHz)

<table class="table table-striped table-bordered">
    <tr>
        <td> Download </td>
        <td> <a href="https://github.com/Microsoft/ELL-models/raw/master/models/ILSVRC2012/Pear/Pear.ell.zip">Pear.ell.zip</a></td>
    </tr>
    <tr>
        <td> Accuracy </td>
        <td colspan="3"> ILSVRC2012: 74.74% (Top 5), 50.08% (Top 1) </td>
    </tr>
    <tr>
        <td> Performance </td>
        <td colspan="3"> Raspberry Pi 3 (Raspbian) @ 700MHz : 85ms/frame </td>
    </tr>
    <tr>
        <td> Uncompressed Size </td>
        <td colspan="3"> 25MB </td>
    </tr>
    <tr>
        <td> Input </td>
        <td colspan="3"> 64 &times; 64 &times; {B,G,R} </td>
    </tr>
    <tr>
        <td> Architecture </td>
        <td>
            Download <a href="https://github.com/Microsoft/ELL-models/raw/master/models/ILSVRC2012/Pear/Pear.onnx.zip">Pear.onnx.zip</a>, unzip file, then use <a href="https://lutzroeder.github.io/netron/" target="_blank">Netron</a> to view.
        </td>
    </tr>
    <tr>
        <td> Output </td>
        <td colspan="3"> <a href="https://github.com/Microsoft/ELL-models/raw/master/models/ILSVRC2012/categories.txt">ILSVRC2012 1000 classes</a> </td>
    </tr>
    <tr>
        <td> Notes </td>
        <td colspan="3"> Trained by Mason Remy using PyTorch 1.0.0 </td>
    </tr>
</table>

