("infile,i", po::value<std::string>(&m_InputFileName)->required(),
"Input image file to generate tensor from")
("model-format,f", po::value<std::string>(&m_ModelFormat)->required(),
- "Format of the model file, Accepted values (caffe, tensorflow, tflite)")
+ "Format of the intended model file that uses the images."
+ "Different formats have different image normalization styles."
+ "Accepted values (caffe, tensorflow, tflite)")
("outfile,o", po::value<std::string>(&m_OutputFileName)->required(),
"Output raw tensor file path")
("output-type,z", po::value<std::string>(&m_OutputType)->default_value("float"),
"The data type of the output tensors."
"If unset, defaults to \"float\" for all defined inputs. "
"Accepted values (float, int or qasymm8)")
- ("new-width,w", po::value<std::string>(&m_NewWidth)->default_value("0"),
+ ("new-width", po::value<std::string>(&m_NewWidth)->default_value("0"),
"Resize image to new width. Keep original width if unspecified")
- ("new-height,h", po::value<std::string>(&m_NewHeight)->default_value("0"),
+ ("new-height", po::value<std::string>(&m_NewHeight)->default_value("0"),
"Resize image to new height. Keep original height if unspecified")
("layout,l", po::value<std::string>(&m_Layout)->default_value("NHWC"),
"Output data layout, \"NHWC\" or \"NCHW\", default value NHWC");
# The ImageTensorGenerator
-The `ImageTensorGenerator` is a program for generating a .raw tensor file from a .jpg image.
+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:|||
| ---|---|---|
-| -h | --help | Display help messages |
-| -i | --infile | Input image file to generate tensor from |
-| -l | --layout | Output data layout, "NHWC" or "NCHW". Default value: NHWC |
-| -o | --outfile | Output raw tensor file path |
+| -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: <br>
-<code>./ImageTensorGenerator -i /path/to/image/dog.jpg -l NHWC -o /output/path/dog.raw</code>
+<code>./ImageTensorGenerator -i /path/to/image/dog.jpg -o /output/path/dog.raw --new-width 224 --new-height 224</code>
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Prerequisites:
1. The model is in .armnn format model file. The `ArmnnConverter` can be used to convert a model to this format.
-2. The ImageNet test data is in raw tensor file format. The `ImageTensorGenerator` can be used to convert the test
-images 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 |
-| -c | --compute | Which device to run layers on by default. Possible choices: CpuRef, CpuAcc, GpuAcc. Default: CpuAcc, CpuRef |
-| -d | --data-dir | Path to directory containing the ImageNet test data |
+| -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 |
-| -v | --validation-labels-path | Path to ImageNet Validation Label file |
+| -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: NHCW
+| -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: <br>
-<code>./ModelAccuracyTool -m /path/to/model/model.armnn -c CpuRef -d /path/to/test/directory/ -i input -o output
--v /path/to/file/val.txt</code>
+<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>
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