はてなブックマーク

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この記事について Raspberry Pi、TensorFlow、Pythonのいずれにも詳しくない筆者が、物体検出をやって楽しんだ成果の記録です。 TensorFlow公式の物体検出のサンプルプログラムを実行します。 動作環境 ボード Raspberry Pi 4 Model B OS Raspberry Pi OS (32-bit または 64-bit) デスクトップ環境 カメラ Raspberry Pi カメラモジュール v2 Python Python 3.9 執筆時点で Raspberry Pi OS に入ってたやつそのまま Raspberry Pi ボードは以下のモデルでTensorFlow Lite がサポートされているようです。 Raspberry Pi 2 Raspberry Pi 3 Raspberry Pi 4 Raspberry Pi Zero 2 準備するもの R

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Deleted articles cannot be recovered. Draft of this article would be also deleted. Are you sure you want to delete this article?

Deleted articles cannot be recovered. Draft of this article would be also deleted. Are you sure you want to delete this article?

Deleted articles cannot be recovered. Draft of this article would be also deleted. Are you sure you want to delete this article?

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経緯 QiitaのようなOAuth認証を実装しようと試みた。 ググってみると、ユーザーをログインさせた後どうするかについて言及されていないものが多かった。 いろんな記事からアイデアを吸収して試行錯誤した結果、自分の思い通りの仕様に仕上がったので今後のためにメモ。 スタートの時点でこれらの記事が非常に参考になった。 RailsでいろんなSNSとOAuth連携/ログインする方法 Rails4 で Devise と OmniAuth で、Twitter/Facebook のOAuth認証と通常フォームでの認証を併用して実装 やりたいこと Devise認証付Railsアプリに、OmniAuthを追加し各ユーザーを複数のプロバイダで認証できる様にしたい。（ユーザーと全てのプロバイダーを紐付けする） Qiitaの仕様を目標とする。 プロバイダーを増やせるように拡張性を持たせる。 新規登録（３パターン）

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