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vision_trainer_2d

参考

vit_pytorchでのtrain https://farml1.com/vit_2/

モデルの保存など
https://tzmi.hatenablog.com/entry/2020/03/05/222813

モデルの推論 https://pystyle.info/pytorch-how-to-use-pretrained-model/#outline__3_4

ファイル構成

ファイル名 内容
main_dl_and_predict.py メインファイル。各関数を読み出して実行、予測、GCSへの保存などを行う。
get_imgs_from_tw.py TWのタイムラインから画像を取得し、保存する
predict.py 指定したディレクトリに対して予測を行う
gcp_controller.py gcp上の操作を行う。画像の保存など
utils.py 細かい関数やクラスなど
model_environment.py モデル内の設定。モデルをいじるときはここをいじる。
train_by_vitpytorch.py 学習を行う

デプロイ手順

headless-chroniumとchromedriverのインストール
https://github.com/ryfeus/gcf-packs

上記リポジトリのselenium-chrome/source配下のchromedriverとheadless-chromiumを フォルダ直下に配置

デプロイ
bash cloud_function_deploy.sh

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