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authorJan Eilers <jan.eilers@arm.com>2021-02-25 17:44:00 +0000
committerJan Eilers <jan.eilers@arm.com>2021-02-25 18:27:49 +0000
commitfd627ffaec8fd8801d980b4c91ee7c0607ab6aaf (patch)
treeeb4bc8f9b411f30c7655616142b5a4bdd3a1acd0 /21.02/md_tests__model_accuracy_tool-_armnn__r_e_a_d_m_e.xhtml
parentfb14ebbd68e04876809145296af96f6f41857418 (diff)
downloadarmnn-fd627ffaec8fd8801d980b4c91ee7c0607ab6aaf.tar.gz
IVGCVSW-5687 Update Doxygen Docu
* Update Doxygen Documentation for 21.02 release Signed-off-by: Jan Eilers <jan.eilers@arm.com> Change-Id: I9ed2f9caab038836ea99d7b378d7899fe431a4e5
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+<!-- Copyright (c) 2020 ARM Limited. -->
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+<div class="title">ModelAccuracyTool </div> </div>
+</div><!--header-->
+<div class="contents">
+<div class="textblock"><p>The <code>ModelAccuracyTool-Armnn</code> is a program for measuring the Top 5 accuracy results of a model against an image dataset.</p>
+<p>Prerequisites:</p><ol type="1">
+<li>The model is in .armnn format model file. The <code>ArmnnConverter</code> can be used to convert a model to this format.</li>
+</ol>
+<p>Build option: To build ModelAccuracyTool, pass the following options to Cmake:</p><ul>
+<li>-DFLATC_DIR=/path/to/flatbuffers/x86build/</li>
+<li>-DBUILD_ACCURACY_TOOL=1</li>
+<li>-DBUILD_ARMNN_SERIALIZER=1</li>
+</ul>
+<table class="doxtable">
+<tr>
+<th>Cmd:</th><th></th><th></th></tr>
+<tr>
+<td>-h </td><td>&ndash;help </td><td>Display help messages </td></tr>
+<tr>
+<td>-m </td><td>&ndash;model-path </td><td>Path to armnn format model file </td></tr>
+<tr>
+<td>-f </td><td>&ndash;model-format </td><td>The model format. Supported values: caffe, tensorflow, tflite </td></tr>
+<tr>
+<td>-i </td><td>&ndash;input-name </td><td>Identifier of the input tensors in the network separated by comma </td></tr>
+<tr>
+<td>-o </td><td>&ndash;output-name </td><td>Identifier of the output tensors in the network separated by comma </td></tr>
+<tr>
+<td>-d </td><td>&ndash;data-dir </td><td>Path to directory containing the ImageNet test data </td></tr>
+<tr>
+<td>-p </td><td>&ndash;model-output-labels </td><td>Path to model output labels file. </td></tr>
+<tr>
+<td>-v </td><td>&ndash;validation-labels-path </td><td>Path to ImageNet Validation Label file </td></tr>
+<tr>
+<td>-l </td><td>&ndash;data-layout ] </td><td>Data layout. Supported value: NHWC, NCHW. Default: NHWC </td></tr>
+<tr>
+<td>-c </td><td>&ndash;compute </td><td>Which device to run layers on by default. Possible choices: CpuRef, CpuAcc, GpuAcc. Default: CpuAcc, CpuRef </td></tr>
+<tr>
+<td>-r </td><td>&ndash;validation-range </td><td>The range of the images to be evaluated. Specified in the form &lt;begin index&gt;=""&gt;:&lt;end index&gt;=""&gt;. The index starts at 1 and the range is inclusive. By default the evaluation will be performed on all images. </td></tr>
+<tr>
+<td>-b </td><td>&ndash;blacklist-path </td><td>Path to a blacklist file where each line denotes the index of an image to be excluded from evaluation. </td></tr>
+</table>
+<p>Example usage: <br />
+ <code>./ModelAccuracyTool -m /path/to/model/model.armnn -f tflite -i input -o output -d /path/to/test/directory/ -p /path/to/model-output-labels -v /path/to/file/val.txt -c CpuRef -r 1:100</code> </p>
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