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NET_NAME: The name of network
Any name can be set.
MODEL_DIR: Path to directory which includes .onnx files
All .onnx files under the directory are converted.
IMAGE_DIR: Path to directory which includes image files for optimizing quantization
Please put the directory image files for training. Recommended number of image files is 100 to 200.
Image file format should be the format that are supported by OpenCV (Ex. JPEG, PNG and etc…).
Any resolution is supported.
OUTPUT_DIR: Path to directory which converted data in placed.
PARSER_OPTION: Quantization mode
Select from FIX8/FIX16/MIX (FIX8/FIX16 mixed).
IN_DATA_CHANNEL: Number of input image channel for target model
N_DATA_WIDTH: Width of input image for target model
IN_DATA_HEIGHT: Height of input image for target model
IN_MEAN: Normalization parameter (mean) of input image
Please refrain from using space between “,” as shown below if using numerical value.
IN_MEAN=127.5,127.5,127.5
IN_SCALE: Normalization parameter (scale) of input image
Please refrain from using space between “,” and only use “,” to separate values when setting different values for each channel.
IS_BGR: Format of input image (RGB or BGR)
OUT_LAYER: The name of output layer for target network
If two or more layers exists, separate layers by “,”.
When the following symbols are contained in the name of input/output node, conversion may not be successful.
: | ; , ‘
PRIORBOX_NODE: Node equivalent to “priorbox”
Need to set when IS_SSD=1
PREPRO: Path of preprocessing script (python script)
Refer to “/home/cvtool/ common/prepro.py” for how to create a script
PREPRO_ARG: Argument of preprocessing script (python script)
IN_DATA_FILEFORMAT: Input data format
Examples : uint8->0,0,0,0, float32->1,2,0,7, float16-> 1>1,1,0,4
When the value of IN_DATA_FILEFORMAT changes from “0,0,0,0”, setting PREPRO is needed.
IN_DATA_TRANSPOSE: Specify when performing TRANSPOSE on the input data
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The model includes unsupported node by cvtool
Run the following command.Code Block $ graph_surgery.py onnx -m (model name before modification) -o (model name after modification) -t CVFlow
Please refer here for the list of supported node.
You can check if the model includes unsupported node, by using onnx_print_graph_summary.py in cvtool.Code Block $ onnx_print_graph_summary.py -p (model name)
Input of the model has variable value
Replace with fixed value by the following command.
Code Block $ graph_surgery.py onnx -m (model name before modification) -o (model name after modification) -isrc "i:input|is:1,3,960,960" -t SetIOShapes
Input shape of the model is NHWC, and transposed to NCHW first
Separate from the beginning of the model to “Tranpose” node.
Code Block $ graph_surgery.py onnx -m (model name before modification) -o (model name after modification) -isrc "i:(output name of Transpose node)|is:1,3,224,224" -t CutGraph
Unsupported character ( : | ; , ‘ ) is included in OUT_LAYER
Rename the node by the following command.Code Block $ graph_surgery.py onnx -m (model name before modification) -o (model name after modification) -t "RenameTensors(original_name=new_name)"
If multiple nodes are specified, please separate those by ",".
Code Block -t "RenameTensors(node::1=node1,node::2=node2)"
The model has nodes of rank > 4
Conversion may not be possible due to SoC constraints.
You can check if the model has such nodes, by using onnx_print_graph_summary.py. The following message will be output when the nodes are found.Code Block $ onnx_print_graph_summary.py -p (model name) INFO: 08/29/2024 03:22:40.725761 onnx_print_graph_summary.py:384 [PrintGraphSummary] Unsupported tensors with rank > 4 (3): INFO: 08/29/2024 03:22:40.725837 onnx_print_graph_summary.py:386 [PrintGraphSummary] -> 'output' [1 x 3 x 52 x 52 x 85] INFO: 08/29/2024 03:22:40.725909 onnx_print_graph_summary.py:386 [PrintGraphSummary] -> '1026' [1 x 3 x 26 x 26 x 85] INFO: 08/29/2024 03:22:40.725993 onnx_print_graph_summary.py:386 [PrintGraphSummary] -> '1046' [1 x 3 x 13 x 13 x 85]
Please modify the model in one of the following ways.
・Modify the nodes before exporting to onnx.
・Separate the back of the node from the model.Code Block $ graph_surgery.py onnx -m (model name before modification) -o (model name after modification) -on (node name before the node of rank > 4) -t CutGraph
・Replace the node with that of rank <= 4.Code Block $ graph_surgery.py onnx -m (model name before modification) -o (model name after modification) -t ReplaceSubgraph
※If you wish to use “ReplaceSubgraph”, please contact us.
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Althogh the node of rank=4, conversion may not be possible when the number of elements in the first dimension of the node is not 1. Please take the same action as in case of rank > 4. |