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products:sbc:vim4:npu:demos:vgg16 [2023/09/18 00:37]
sravan [Build virtual environment] 		products:sbc:vim4:npu:demos:vgg16 [2025/06/11 21:50] (current)
louis
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 ~~tag>NPU VGG16 VIM4 Tensorflow Keras ~~ ~~tag>NPU VGG16 VIM4 Tensorflow Keras ~~
  
-====== VGG16 Tensorflow Keras VIM4 Demo 4 ======+**Doc for version ddk-3.4.7.7** 
 + 
 +====== VGG16 TensorFlow Keras VIM4 Demo 4 ======
  
 {{indexmenu_n>4}} {{indexmenu_n>4}}
 +
 +===== Introduction =====
 +
 +VGG16 is a classification model. It can assign a single label to an entire image.
 +
 +Image and inference results on VIM4.
 +
 +{{:products:sbc:vim4:npu:demos:airplane.webp?400|}}
 +
 +{{:products:sbc:vim4:npu:demos:vgg16-demo-output.webp?400|}}
  
 [[https://www.google.com/search?q=VGG16|VGG16]] is a convolution neural net architecture that’s used for image recognition. It utilizes 16 layers with weights and is considered one of the best vision model architectures to date. [[https://www.google.com/search?q=VGG16|VGG16]] is a convolution neural net architecture that’s used for image recognition. It utilizes 16 layers with weights and is considered one of the best vision model architectures to date.
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 Follow Docker official documentation to install Docker: [[https://docs.docker.com/engine/install/ubuntu/|Install Docker Engine on Ubuntu]]. Follow Docker official documentation to install Docker: [[https://docs.docker.com/engine/install/ubuntu/|Install Docker Engine on Ubuntu]].
  
-Then fetch the prebuilt NPU Docker Container and run it.+Follow the script below to get Docker image:
  
 ```shell ```shell
-$ docker pull yanwyb/npu:v1 +docker pull numbqq/npu-vim4
-$ docker run -it --name vim4-npu1 -v $(pwd):/home/khadas/npu \ +
- -v /etc/localtime:/etc/localtime:ro \ +
- -v /etc/timezone:/etc/timezone:ro \ +
- yanwyb/npu:v1+
 ``` ```
  
 ==== Get convert tool ==== ==== Get convert tool ====
  
-Download Tool from [[gl>khadas/vim4_npu_sdk]].+Download Tool from [[gh>khadas/vim4_npu_sdk]].
  
 ```shell ```shell
-$ git clone https://gitlab.com/khadas/vim4_npu_sdk+$ git lfs install 
 +$ git lfs clone https://github.com/khadas/vim4_npu_sdk 
 +$ cd vim4_npu_sdk 
 +$ ls 
 +adla-toolkit-binary  adla-toolkit-binary-1.2.0.9  convert-in-docker.sh  Dockerfile  docs  README.md
 ``` ```
 +
 +  * ''adla-toolkit-binary/docs'' - SDK documentations
 +  * ''adla-toolkit-binary/bin'' - SDK tools required for model conversion
 +  * ''adla-toolkit-binary/demo'' - Conversion examples
 +
 +<WRAP important>
 +If your kernel is older than 241129, please use branch npu-ddk-1.7.5.5.
 +</WRAP>
  
 ==== Convert ==== ==== Convert ====
  
-This demo is to convert it to TensorFlow model (''.pb'') first, and convert TensorFlow model to ADLA model. We use this tool to convert [[gh>amir-abdi/keras_to_tensorflow]]+We first need to convert the Keras model(''.h5'') into a TensorFlow model (''.pb''). We use this tool to convert [[gh>amir-abdi/keras_to_tensorflow]]
  
 ```shell ```shell
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 ``` ```
  
-Enter ''vim4_npu_sdk/demo'' and modify ''convert_adla.sh'' as follows.+Then we need to convert the TensorFlow model to an ADLA model (''.adla'') 
 + 
 +Enter ''vim4_npu_sdk/demo'' and overwrite ''convert_adla.sh'' as follows.
  
 ```sh convert_adla.sh ```sh convert_adla.sh
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         --quantize-dtype int8 --outdir tensorflow_output \         --quantize-dtype int8 --outdir tensorflow_output \
         --channel-mean-value "0,0,0,255" \         --channel-mean-value "0,0,0,255" \
 +        --inference-input-type "float32" \
 +        --inference-output-type "float32" \
         --source-file vgg16_dataset.txt \         --source-file vgg16_dataset.txt \
         --iterations 500 \         --iterations 500 \
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 ``` ```
  
-Run ''convert_adla.sh'' to generate VIM4 model. The converted model is ''xxx.adla'' in ''tensorflow_output''.+Run ''convert_adla.sh'' to generate the VIM4 model. The converted model is ''xxx.adla'' in ''tensorflow_output''.
  
 ```shell ```shell
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 $ git clone https://github.com/khadas/vim4_npu_applications $ git clone https://github.com/khadas/vim4_npu_applications
 ``` ```
 +
 +<WRAP important>
 +If your kernel is older than 241129, please use version before tag ddk-3.4.7.7.
 +</WRAP>
  
 ==== Install dependencies ==== ==== Install dependencies ====
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 # Run # Run
-$ sudo ./vgg16 -m ../data/vgg16_int8.adla -p ../data/airplane.jpeg+$ ./vgg16 -m ../data/vgg16_int8.adla -p ../data/airplane.jpeg
 ``` ```
  
 <WRAP tip > <WRAP tip >
-If your **vgg16** model classes is not the same as **cifar10**, please change ''data/vgg16_class.txt'' and the ''OBJ_CLASS_NUM'' in ''include/postprocess.h''.+If your **VGG16** model classes are not the same as **CIFAR10**, please change ''data/vgg16_class.txt'' and the ''OBJ_CLASS_NUM'' in ''include/postprocess.h''.
 </WRAP> </WRAP>
  
Last modified: 2023/09/18 00:37 by sravan

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