From 6940dd720ebb6b3d1df8ca203ab696daefe58189 Mon Sep 17 00:00:00 2001 From: Jim Flynn Date: Fri, 20 Mar 2020 12:25:56 +0000 Subject: renamed Documentation folder 20.02 and added .nojekyll file Signed-off-by: Jim Flynn --- 20.02/other_tools.xhtml | 206 ++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 206 insertions(+) create mode 100644 20.02/other_tools.xhtml (limited to '20.02/other_tools.xhtml') diff --git a/20.02/other_tools.xhtml b/20.02/other_tools.xhtml new file mode 100644 index 0000000000..48a78b09ad --- /dev/null +++ b/20.02/other_tools.xhtml @@ -0,0 +1,206 @@ + + + + + + + + + + + + + +ArmNN: Other Tools + + + + + + + + + + + + + + + + +
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Other Tools
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Table of Contents

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+The ImageCSVFileGenerator

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The ImageCSVFileGenerator is a program for creating a CSV file that contains a list of .raw tensor files. These .raw tensor files can be generated using theImageTensorGenerator.

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Cmd:
-h –help Display help messages
-i –indir Directory that .raw files are stored in
-o –outfile Output CSV file path
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Example usage:
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./ImageCSVFileGenerator -i /path/to/directory/ -o /output/path/csvfile.csv


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+The ImageTensorGenerator

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The ImageTensorGenerator is a program for pre-processing a .jpg image before generating a .raw tensor file from it.

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Build option: To build ModelAccuracyTool, pass the following options to Cmake: -DBUILD_ARMNN_QUANTIZER=1

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Cmd:
-h –help Display help messages
-f –model-format Format of the intended model file that uses the images.Different formats have different image normalization styles.Accepted values (caffe, tensorflow, tflite)
-i –infile Input image file to generate tensor from
-o –outfile Output raw tensor file path
-z –output-type The data type of the output tensors.If unset, defaults to "float" for all defined inputs. Accepted values (float, int or qasymm8)
–new-width Resize image to new width. Keep original width if unspecified
–new-height Resize image to new height. Keep original height if unspecified
-l –layout Output data layout, "NHWC" or "NCHW". Default value: NHWC
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Example usage:
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.sh ./ImageTensorGenerator -i /path/to/image/dog.jpg -o /output/path/dog.raw --new-width 224 --new-height 224


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+The ModelAccuracyTool-ArmNN

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The ModelAccuracyTool-Armnn is a program for measuring the Top 5 accuracy results of a model against an image dataset.

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Prerequisites:

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  1. The model is in .armnn format model file. The ArmnnConverter can be used to convert a model to this format.
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Build option: To build ModelAccuracyTool, pass the following options to Cmake: -DFLATC_DIR=/path/to/flatbuffers/x86build/ -DBUILD_ACCURACY_TOOL=1 -DBUILD_ARMNN_SERIALIZER=1

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Cmd:
-h –help Display help messages
-m –model-path Path to armnn format model file
-f –model-format The model format. Supported values: caffe, tensorflow, tflite
-i –input-name Identifier of the input tensors in the network separated by comma
-o –output-name Identifier of the output tensors in the network separated by comma
-d –data-dir Path to directory containing the ImageNet test data
-p –model-output-labels Path to model output labels file.
-v –validation-labels-path Path to ImageNet Validation Label file
-l –data-layout ] Data layout. Supported value: NHWC, NCHW. Default: NHWC
-c –compute Which device to run layers on by default. Possible choices: CpuRef, CpuAcc, GpuAcc. Default: CpuAcc, CpuRef
-r –validation-range The range of the images to be evaluated. Specified in the form <begin index>="">:<end index>="">. The index starts at 1 and the range is inclusive. By default the evaluation will be performed on all images.
-b –blacklist-path Path to a blacklist file where each line denotes the index of an image to be excluded from evaluation.
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Example usage:
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./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


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