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products:sbc:vim3:npu:ksnn:ksnn-convert [2023/09/15 11:56]
sravan [Conversion example] 		products:sbc:vim3:npu:ksnn:ksnn-convert [2024/05/08 02:16]
louis
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 ===== Conversion example ===== ===== Conversion example =====
  
-Choose tensorflow Inception V3 as an example.+Choose tensorflow MobileNet SSD as an example.
  
 1. Get the frozen model, 1. Get the frozen model,
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 ```shell ```shell
 $ cd aml_npu_sdk/acuity-toolkit/python $ cd aml_npu_sdk/acuity-toolkit/python
-$ wget https://github.com/yan-wyb/models-zoo/raw/master/tensonrflow/inception/inception_v3_2016_08_28_frozen.pb+$ wget https://github.com/yan-wyb/models-zoo/raw/master/tensorflow/mobilenet_ssd/ssd_mobilenet_v1_coco_2017_11_17.pb
 ``` ```
  
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 ```shell ```shell
-$ ./convert --model-name inception \+# uint8 
 +$ ./convert --model-name mobilenet_ssd \
 >           --platform tensorflow \ >           --platform tensorflow \
->           --model /home/yan/yan/Yan/models-zoo/tensorflow/inception/inception_v3_2016_08_28_frozen.pb \ +>           --model /home/yan/yan/Yan/models-zoo/tensorflow/mobilenet_ssd/ssd_mobilenet_v1_coco_2017_11_17.pb \ 
->           --input-size-list '299,299,3' \ +>           --input-size-list '300,300,3' \ 
->           --inputs input \ +>           --inputs FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm/batchnorm/mul_1 \ 
->           --outputs InceptionV3/Predictions/Reshape_1 \ +>           --outputs "'concat concat_1'" \ 
->           --mean-values '128 128 128 0.0078125' \+>           --mean-values '127.5 127.5 127.5 0.007843137' \
 >           --quantized-dtype asymmetric_affine \ >           --quantized-dtype asymmetric_affine \
 +>           --source-files ./data/dataset/dataset0.txt \
 +>           --kboard VIM3 --print-level 0
 +
 +# int8
 +$ ./convert --model-name mobilenet_ssd \
 +>           --platform tensorflow \
 +>           --model /home/yan/yan/Yan/models-zoo/tensorflow/mobilenet_ssd/ssd_mobilenet_v1_coco_2017_11_17.pb \
 +>           --input-size-list '300,300,3' \
 +>           --inputs FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm/batchnorm/mul_1 \
 +>           --outputs "'concat concat_1'" \
 +>           --mean-values '127.5 127.5 127.5 0.007843137' \
 +>           --quantized-dtype dynamic_fixed_point \
 +>           --qtype int8 \
 +>           --source-files ./data/dataset/dataset0.txt \
 +>           --kboard VIM3 --print-level 0
 +
 +# int16
 +$ ./convert --model-name mobilenet_ssd \
 +>           --platform tensorflow \
 +>           --model /home/yan/yan/Yan/models-zoo/tensorflow/mobilenet_ssd/ssd_mobilenet_v1_coco_2017_11_17.pb \
 +>           --input-size-list '300,300,3' \
 +>           --inputs FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm/batchnorm/mul_1 \
 +>           --outputs "'concat concat_1'" \
 +>           --mean-values '127.5 127.5 127.5 0.007843137' \
 +>           --quantized-dtype dynamic_fixed_point \
 +>           --qtype int16 \
 >           --source-files ./data/dataset/dataset0.txt \ >           --source-files ./data/dataset/dataset0.txt \
 >           --kboard VIM3 --print-level 0 >           --kboard VIM3 --print-level 0
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 ```shell ```shell
 $ cd aml_npu_sdk/acuity-toolkit/python $ cd aml_npu_sdk/acuity-toolkit/python
-$ ls outputs/inception/ +$ ls outputs/mobilenet_ssd/ 
-inception.nb  libnn_inception.so+mobilenet_ssd.nb  libnn_mobilenet_ssd.so
 ``` ```
  
Last modified: 2024/05/27 22:15 by louis

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