Data Structure ?
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Data Structure ?
*The above analysis is the result extracted and analyzed by the system, and the specific actual data shall prevail.
README.md
文脈
このプロジェクトは、Nvidia DIGITSとNVCaffeソフトウェアのテストとして開始され、良質なデータセットに必要な画像の種類を評価しようと試みました。私はBVLC_googlenet.cafemodelを使用して20％の平均平均精度（mAP）を達成し、Nvidia Jetson TX2を使用してハチを成功裏に推論することができました。ここにビデオがあります：[瓶の中のハチ][1]。DIGITSとAmazon Web Servicesの使い方の説明が載ったメインのプロジェクトページはこちらです：[メインプロジェクトページ][2]
内容
ハチの画像が約3,000枚あり、それぞれに物体推論用のバウンディングボックスがラベル付けされています。一部の画像は部分的に遮蔽されたり切り取られたりしていますが、ラベルにはこれらの属性は記述されていません。
謝辞
他の人たちの助けがなければ、私たちはここにいることはできません。謝辞や引用が必要な場合は、ここに過去の研究の引用とともに記載してください。
着想
画像に対するいくつかの批判を返信してください。私の質問のいくつかは次の通りです。
1. すべての画像を高品質にすべきですか？
2. 画像は「現実の」カメラ環境を反映すべきですか？
3. 画像の何％をぼやけた/ピンボケにすべきですか？
4. 遮蔽と切り取りをラベル付けすることはどれほど重要ですか？
5. 画像に異なる背景を持たせることはどれほど重要ですか？
….. ありがとう！
[1]: https://www.youtube.com/watch?v=01MJmSwYuIo
[2]: https://hackaday.io/project/161581-wasp-and-asian-hornet-sentry-gun
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