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Table of contents

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環境構築

環境構築手順はこちらをご参照ください。

モデルの変換

モデル変換については下記ページをご参照ください。

　設定ファイル仕様・サンプルモデル変換（Caffe編）

　設定ファイル仕様・サンプルモデル変換（Tensorflow編）

　設定ファイル仕様・サンプルモデル変換（ONNX/PyTorch編）

モデルの評価

CVツールには、変換後のモデルの推論時間、精度などを評価する仕組みは含まれていません。

変換後モデルをi-PROカメラ上で実行し、評価を行ってください。

推論時間

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Preparation

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Please refer here for the environment construction procedure.

Conversion

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Please refer to the following page for model conversion.

　AI model convert tool: Caffe

　AI model convert tool: Tensorflow

　AI model convert: ONNX(PyTorch)

Evaluate AI model

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Please evaluate in one of the following ways.

1. Running the converted model on the i-PRO camera
   Inference time
   Measure the time before and after the inference execution API (Adam_AI_RunNet())

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1. call
   

精度

1. Precision
   Evaluate the accuracy using the data obtained by the API (Adam_AI_GetOutput(

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CVツールには、変換後モデルの推論時間と出力層のデータを取得できるサンプルアプリが含まれています。

次から使用方法を紹介します。

評価の準備

評価にはChrome拡張機能のADAM OPERATION UIを使用します。

インストール方法の詳細はSDK同梱のドキュメント「AdamAppDevelopmentManualForIpro.pdf」を参照してください。

また、アプリがインストールできるi-PROネットワークカメラを用意してください。

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1. )) that acquires the data of the output layer of the model.
   

2. Using sample app
   The CV tool includes a sample app that allows you to obtain inference time and output layer data for the converted model. This page explains how to use it.
   

3. Using simulator in CV tool
   It is possible to perform inference for the converted model. Please refer here on how to use it.

Sample app for evaluation

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Preparing for the evaluation

Use the Chrome extension's ADAM OPERATION UI for evaluation.

For details on how to install, refer here.

Also, make sure you have an i-PRO network camera that the app can install on.

DnnSdApp

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Install the app

First, copy the DnnSdApp package (DnnSdApp_V0_45_ambaCV2XambaCV2X5X.ext) を、ホストPCにコピーします。in the container to the host PC.

[Work Directory]は任意のディレクトリAny directory

$ cd [Work Directory]
$ sudo docker run -it --rm -v $(pwd):/work [image name] /bin/bash
$ cp /home/cvtool/app/DnnSdApp_V0_45_ambaCV2XambaCV2X5X.ext /work

ADAM OPERATION UIを表示します。Launch a browser and access the detailed setting

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Set [Basic] - [SD memory card] - [Operation Mode] - [SD memory card] and [Ext. software mode] to "On".

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Move to the Ext. software and install DnnSdApp.

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Change settings to match your rating model

Configure various settings with ADAM OPERATION UI.

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layernamein: Input layer name

layernameout: Output layer name (separated by comma for multiple settings)

NETNAME: Model name

TftpServerIP：TFTP server address where models are stored
　　　　　　　*Set if SD card is not used

ChannelNum：Channels of model

ImgHeight：Height of input image

ImgWidth：Width of input image

PixelFormat：Pixel format of model

Prepare evaluation images

Compress the images to be used for evaluation (dnn.tar.gz) .

Follow the folder structure below, either jpeg or mp4 only can be used.

tar cvzf dnn.tar.gz dnn

Upload images to DnnSdApp

Open the app screen and upload the image data.

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Upload the model file to the app

Upload the model file.

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Run the app

After placing the model and image, click the "Start" button to start execution.

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Download the results

Once the run is complete, you can get the result file from the Download button.

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SsdSdApp

The operation is similar to DnnSdApp.

Please replace the folder name with "SSD" ⇒ "DNN".