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products:sbc:vim4:npu:demos:densenet [2023/09/18 01:52]
sravan [Build a virtual environment] 		products:sbc:vim4:npu:demos:densenet [2025/06/11 21:49] (current)
louis
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 ~~tag> NPU Densenet VIM4 ONNX~~ ~~tag> NPU Densenet VIM4 ONNX~~
-====== DenseNet CTC ONNX Keras VIM4 Demo - 3======+ 
 +**Doc for version ddk-3.4.7.7** 
 + 
 +====== DenseNet CTC ONNX Keras VIM4 Demo - 3 ======
  
 {{indexmenu_n>3}} {{indexmenu_n>3}}
 +
 +===== Introduction =====
 +
 +Densenet_CTC is a text recognition model. It only can recognize single line text. Therefore usually, it needs to be used in conjunction with a text detection model.
 +
 +Recognition image and inference results on VIM4.
 +
 +{{:products:sbc:vim4:npu:demos:khadasteam.webp?400|}}  {{:products:sbc:vim4:npu:demos:densenet-demo-output.webp?400|}}
 +
 ===== Get the source code ===== ===== Get the source code =====
  
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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 the conversion tool ==== ==== Get the conversion tool ====
  
-Download The conversion tool from [[gl>khadas/vim4_npu_sdk]].+Download The conversion tool from [[gh>khadas/vim4_npu_sdk]].
  
 ```shell ```shell
-$ git clone https://gitlab.com/khadas/vim4_npu_sdk+$ git clone https://github.com/khadas/vim4_npu_sdk 
 +$ cd vim4_npu_sdk 
 +$ git lfs pull 
 +$ ls 
 +adla-toolkit-binary  adla-toolkit-binary-3.1.7.4  convert-in-docker.sh  Dockerfile  docs  README.md
 ``` ```
  
-After training the model, run the scripts as follows to modify net input and output and convert model to ONNX.+  * ''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 ==== 
 + 
 +After training the model, run the scripts as follows to modify net input and output and convert the model to ONNX.
  
 <WRAP tip > <WRAP tip >
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 ``` ```
  
-Enter ''vim4_npu_sdk/demo'' and modify ''convert_adla.sh'' as follows. We should quantize the model to **int16**, because it is very inaccurate with **int8**.+Enter ''vim4_npu_sdk/demo'' and modify ''convert_adla.sh'' as follows.
  
 ```bash convert_adla.sh ```bash convert_adla.sh
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         --dtypes "float32" \         --dtypes "float32" \
         --inference-input-type float32 \         --inference-input-type float32 \
- --inference-output-type float32 \ + --inference-output-type float32 \ 
-        --quantize-dtype int16 --outdir onnx_output  \+        --quantize-dtype int8 --outdir onnx_output  \
         --channel-mean-value "0,0,0,255"  \         --channel-mean-value "0,0,0,255"  \
         --source-file ./densenet_ctc_dataset.txt  \         --source-file ./densenet_ctc_dataset.txt  \
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 ``` ```
  
-Run ''convert_adla.sh'' to generate VIM4 model. The converted model is ''xxx.adla'' in ''onnx_output''.+Run ''convert_adla.sh'' to generate the VIM4 model. The converted model is ''xxx.adla'' in ''onnx_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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 === Picture input demo === === Picture input demo ===
  
-Put ''densenet_ctc_int16.adla'' in ''vim4_npu_applications/densenet_ctc/data/''.+Put ''densenet_ctc_int8.adla'' in ''vim4_npu_applications/densenet_ctc/data/''.
  
 ```shell ```shell
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 # Run # Run
-$ sudo ./densenet_ctc -m ../data/densenet_ctc_int16.adla -p ../data/KhadasTeam.png+$ ./densenet_ctc -m ../data/densenet_ctc_int8.adla -p ../data/KhadasTeam.png
 ``` ```
  
-<WRAP tip > +{{:products:sbc:vim4:npu:demos:khadasteam.webp?400|}} 
-If your **DenseNet_CTC** model classes is not the same, please change ''data/class_str.txt'' and the ''OBJ_CLASS_NUM'' in ''include/postprocess.h''.+ 
 +{{:products:sbc:vim4:npu:demos:densenet-demo-output.webp?400|}} 
 + 
 +<WRAP tip> 
 +If your ''densenet_ctc'' - **DenseNet-CTC** model classes are not the same, please change ''data/class_str.txt'' and the ''OBJ_CLASS_NUM'' in ''include/postprocess.h''.
 </WRAP> </WRAP>
  
Last modified: 2023/09/18 01:52 by sravan

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