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products:sbc:vim3:npu:ksnn:demos:yolov8n

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products:sbc:vim3:npu:ksnn:demos:yolov8n [2024/02/17 22:37]
louis
products:sbc:vim3:npu:ksnn:demos:yolov8n [2024/02/22 05:19] (current)
louis
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 ``` ```
  
-Refer ''README.md'' to create and train a YOLOv8n model.+Refer ''README.md'' to create and train a YOLOv8n model. My version ''torch==1.10.1'' and ''ultralytics==8.0.86''.
  
 ===== Convert the model ===== ===== Convert the model =====
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             --quantized-dtype asymmetric_affine \             --quantized-dtype asymmetric_affine \
             --source-files ./data/dataset/dataset0.txt \             --source-files ./data/dataset/dataset0.txt \
 +            --batch-size 1 \
 +            --iterations 1 \
             --kboard VIM3 --print-level 0              --kboard VIM3 --print-level 0 
 ``` ```
  
-If you use ''VIM3L'' , please use ''VIM3L'' to replace ''VIM3''+If you want to use more quantified images, please modify ''batch-size'' and ''iterations''. ''batch-size''×''iterations''=number of quantified images. 
 + 
 +If you use ''VIM3L'' , please use ''VIM3L'' to replace ''VIM3''.
  
 If run succeed, converted model and library will generate in ''outputs/yolov8n''. If run succeed, converted model and library will generate in ''outputs/yolov8n''.
Last modified: 2024/02/17 22:37 by louis