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様々な画像フォーマット（PNG、JPEG、WebP）のサポート\n- CUDAによる高速化（オプション）\n- マルチスレッド処理\n- 処理状況を追跡するプログレスバー\n\n## 前提条件\n\n- Rust 1.68以降\n- CUDAツールキット（オプション）\n\n## インストール\n\n1. リポジトリをクローンします：\n   ```shell\n   git clone https://github.com/yourusername/anime-seg-rs.git\n   cd anime-seg-rs\n   ```\n\n2. プロジェクトをビルドします：\n   ```shell\n   cargo build --release\n   ```\n\n   CUDAサポートを有効にする場合は、`cuda`を追加します：\n   ```shell\n   cargo build --release --features cuda\n   ```\n\n## 使用方法\n\n以下のコマンドでツールを実行します：\n\n```shell\nanime-seg-rs --model-path \u003cモデルパス\u003e [オプション] \u003c入力ディレクトリ\u003e \u003c出力ディレクトリ\u003e \n```\n\n### 引数：\n\n- `--model-path, -m`: ISNetモデルファイルのパス（ONNXフォーマット）\n- `--format, -f`: 出力画像フォーマット（デフォルト: \"png\"）\n- `--device-id, -d`: CUDA デバイスID（デフォルト: 0）\n- `--batch-size, -b`: バッチサイズ（デフォルト: 1）\n\n### 使用例：\n\n```shell\nanime-seg-rs --input-dir ./input_images --output-dir ./output_images --model-path ./isnet_fp16.onnx --format png\n```\n\n## ソースからのビルド\n\nソースからプロジェクトをビルドするには、RustとCargoがインストールされていることを確認してから、以下を実行します:\n\n```shell\ncargo build --release\n```\n\n## モデルの互換性と最適化\n\nこのRust実装は、元のanime-segmentationプロジェクトのISNet ONNXモデルで動作するように\n設計されています。事前学習済みのISNetモデルは [Hugging Face](https://huggingface.co/skytnt/anime-seg)\nからダウンロードできます。\n\n## ライセンス\n\n- [Apache License 2.0](LICENSE)\n\n## 謝辞\n\n- [SkyTNT](https://github.com/SkyTNT)による元の[anime-segmentation](https://github.com/SkyTNT/anime-segmentation)プロジェクト\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnusu-github%2Fanime-seg-rs","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnusu-github%2Fanime-seg-rs","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnusu-github%2Fanime-seg-rs/lists"}