20.02
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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
.
Cmd: | ||
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-h | –help | Display help messages |
-i | –indir | Directory that .raw files are stored in |
-o | –outfile | Output CSV file path |
Example usage:
The ImageTensorGenerator
is a program for pre-processing a .jpg image before generating a .raw tensor file from it.
Build option: To build ModelAccuracyTool, pass the following options to Cmake: -DBUILD_ARMNN_QUANTIZER=1
Cmd: | ||
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-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 |
Example usage:
The ModelAccuracyTool-Armnn
is a program for measuring the Top 5 accuracy results of a model against an image dataset.
Prerequisites:
ArmnnConverter
can be used to convert a model to this format.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
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. |
Example usage: