Difference between revisions of "Getting started with TI Jacinto 7 Edge AI/Demos/Python Demos/Getting the models"

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{{Getting started with TI Jacinto 7 Edge AI/Head|next=Demos/Python Demos/Classification|previous=Demos/Python Demos|metakeywords=}}
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== Getting the Models ==
 
== Getting the Models ==
  
==== Download the inference models ====  
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=== {{Download}} Download the inference models ===
  
* Login to your Jacinto 7 and navigate to the models directory.
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Login to your Jacinto 7 and navigate to the models directory:
  
 
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* Run the download models script to download the pre-imported models.
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* Run the ''download_models.sh'' script to download the pre-imported models:
  
 
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An interactive menu will launch with the list of pre-imported models. Use the space bar to select the models intended to download. See Figure 1 below.
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An interactive menu will launch with the list of pre-imported models. Use the space bar to select the models intended for download. See Figure 1.  
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|issue='''Note:''' To run the demos exemplified in this guide, the following models need to be downloaded:
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* TFL-CL-002-SqueezeNet
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* TFL-OD-200-ssd-mobV1-coco-mlperf-300x300
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* TVM-SS-569-fpnlite-aspp-regnetx400mf-ade20k32-384x384
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[[File:Getting-models-menu.png|frame|Interactive models|center|900px|link=|Figure 1. Interactive menu to download models]]
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[[File:Getting-models-menu.png|frameless|Interactive models|center|900px ]]
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<div style="text-align: center;">'''Figure 1'''. Interactive menu to download models.</div><br>
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Latest revision as of 13:29, 8 March 2023




Previous: Demos/Python Demos Index Next: Demos/Python Demos/Classification





Getting the Models

Download alt font awesome.svg Download the inference models

Login to your Jacinto 7 and navigate to the models directory:

cd /opt/edge_ai_apps/models
  • Run the download_models.sh script to download the pre-imported models:
./download_models.sh

An interactive menu will launch with the list of pre-imported models. Use the space bar to select the models intended for download. See Figure 1.

  • TFL-CL-002-SqueezeNet
  • TFL-OD-200-ssd-mobV1-coco-mlperf-300x300
  • TVM-SS-569-fpnlite-aspp-regnetx400mf-ade20k32-384x384


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Figure 1. Interactive menu to download models


Previous: Demos/Python Demos Index Next: Demos/Python Demos/Classification