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FastDeploy/docs/docs_i18n/README_日本語.md
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[English](../../README_EN.md) | [简体中文](../../README_CN.md) | [हिन्दी](./README_हिन्दी.md) | 日本語 | [한국인](./README_한국인.md) | [Pу́сский язы́к](./README_Pу́сский_язы́к.md)
![FastDeploy](https://user-images.githubusercontent.com/31974251/185771818-5d4423cd-c94c-4a49-9894-bc7a8d1c29d0.png)
</p>
<p align="center">
<a href="./LICENSE"><img src="https://img.shields.io/badge/license-Apache%202-dfd.svg"></a>
<a href="https://github.com/PaddlePaddle/FastDeploy/releases"><img src="https://img.shields.io/github/v/release/PaddlePaddle/FastDeploy?color=ffa"></a>
<a href=""><img src="https://img.shields.io/badge/python-3.7+-aff.svg"></a>
<a href=""><img src="https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-pink.svg"></a>
<a href="https://github.com/PaddlePaddle/FastDeploy/graphs/contributors"><img src="https://img.shields.io/github/contributors/PaddlePaddle/FastDeploy?color=9ea"></a>
<a href="https://github.com/PaddlePaddle/FastDeploy/commits"><img src="https://img.shields.io/github/commit-activity/m/PaddlePaddle/FastDeploy?color=3af"></a>
<a href="https://github.com/PaddlePaddle/FastDeploy/issues"><img src="https://img.shields.io/github/issues/PaddlePaddle/FastDeploy?color=9cc"></a>
<a href="https://github.com/PaddlePaddle/FastDeploy/stargazers"><img src="https://img.shields.io/github/stars/PaddlePaddle/FastDeploy?color=ccf"></a>
</p>
<p align="center">
<a href="./../../docs/cn/build_and_install"><b> インストール </b></a>
|
<a href="./../../docs/README_CN.md"><b> ドキュメント </b></a>
|
<a href="./../../README_CN.md#fastdeploy-quick-start-python"><b> クイックスタート </b></a>
|
<a href="https://baidu-paddle.github.io/fastdeploy-api/"><b> APIドキュメンテーション </b></a>
|
<a href="https://github.com/PaddlePaddle/FastDeploy/releases"><b> Changelog </b></a>
</p>
<div align="center">
[<img src='https://user-images.githubusercontent.com/54695910/200465949-da478e1b-21ce-43b8-9f3f-287460e786bd.png' height="80px" width="110px">](../../examples/vision/classification)
[<img src='https://user-images.githubusercontent.com/54695910/188054680-2f8d1952-c120-4b67-88fc-7d2d7d2378b4.gif' height="80px" width="110px">](../../examples/vision/detection)
[<img src='https://user-images.githubusercontent.com/54695910/188054711-6119f0e7-d741-43b1-b273-9493d103d49f.gif' height="80px" width="110px">](../../examples/vision/segmentation/paddleseg)
[<img src='https://user-images.githubusercontent.com/54695910/188054718-6395321c-8937-4fa0-881c-5b20deb92aaa.gif' height="80px" width="110px">](../../examples/vision/segmentation/paddleseg)
[<img src='https://user-images.githubusercontent.com/54695910/188058231-a5fe1ce1-0a38-460f-9582-e0b881514908.gif' height="80px" width="110px">](../../examples/vision/matting)
[<img src='https://user-images.githubusercontent.com/54695910/188054691-e4cb1a70-09fe-4691-bc62-5552d50bd853.gif' height="80px" width="110px">](../../examples/vision/matting)
[<img src='https://user-images.githubusercontent.com/54695910/188054669-a85996ba-f7f3-4646-ae1f-3b7e3e353e7d.gif' height="80px" width="110px">](../../examples/vision/ocr)<br>
[<img src='https://user-images.githubusercontent.com/54695910/188059460-9845e717-c30a-4252-bd80-b7f6d4cf30cb.png' height="80px" width="110px">](../../examples/vision/facealign)
[<img src='https://user-images.githubusercontent.com/54695910/188054671-394db8dd-537c-42b1-9d90-468d7ad1530e.gif' height="80px" width="110px">](../../examples/vision/keypointdetection)
[<img src='https://user-images.githubusercontent.com/48054808/173034825-623e4f78-22a5-4f14-9b83-dc47aa868478.gif' height="80px" width="110px">](https://github.com/PaddlePaddle/FastDeploy/issues/6)
[<img src='https://user-images.githubusercontent.com/54695910/200162475-f5d85d70-18fb-4930-8e7e-9ca065c1d618.gif' height="80px" width="110px">](../../examples/text)
[<img src='https://user-images.githubusercontent.com/54695910/212314909-77624bdd-1d12-4431-9cca-7a944ec705d3.png' height="80px" width="110px">](https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/001.wav)
</div>
**FastDeploy**は、**オールシナリオで使いやすく**、**柔軟で非常に効率的な**AI推論デプロイツールです。 🔥160以上の**テキスト**、**ビジョン**、**スピーチ**および🔚クロスモーダルモデルをサポートし、エンドツーエンドの推論パフォーマンスの最適化を可能にする、すぐに使えるクラウド側のデプロイメントエクスペリエンスを提供します。 これには、画像分類、物体検出、画像分割、顔検出、顔認識、キーポイント検出、キーイング、OCR、NLP、TTSなどのタスクが含まれ、**マルチシーン**、**マルチハードウェア**、**マルチプラットフォーム**の産業展開に対する開発者のニーズに応えています。
<div align="center">
<img src="https://user-images.githubusercontent.com/115439700/212800436-9cb39830-fca5-4b40-9def-a1fd83fcfc90.png" >
</div>
## 🌠 最近の更新情報
- ✨✨✨ **2023.01.17** FastDeployファミリーのハードウェアに対する[**YOLOv8**](./../../examples/vision/detection/paddledetection/) デプロイメントサポートをリリースしました。これには[**Paddle YOLOv8**](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8)と[**コミュニティ ultralytics YOLOv8**](https://github.com/ultralytics/ultralytics)
- [**Paddle YOLOv8**](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8) 配置可能なハードウェア:[**Intel CPU**](./../../examples/vision/detection/paddledetection/python/infer_yolov8.py)、[**NVIDIA GPU**](./../../examples/vision/detection/paddledetection/python/infer_yolov8.py)、[**Jetson**](./../../examples/vision/detection/paddledetection/python/infer_yolov8.py)、[**Phytium**](./../../examples/vision/detection/paddledetection/python/infer_yolov8.py)、[**KunlunXin**](./../../examples/vision/detection/paddledetection/python/infer_yolov8.py)、[**Huawei Ascend**](./../../examples/vision/detection/paddledetection/python/infer_yolov8.py)、[**ARM CPU**](./../../examples/vision/detection/paddledetection/cpp/infer_yolov8.cc) が含まれる **Python** 配備状況と**C++** 配備状況;**アルゴリズムTPU** 和 **RK3588** が更新されています
- [**コミュニティ ultralytics YOLOv8**](https://github.com/ultralytics/ultralytics) 配置可能なハードウェア:[**Intel CPU**](./../../examples/vision/detection/yolov8)、[**NVIDIA GPU**](./../../examples/vision/detection/yolov8)、[**Jetson**](./../../examples/vision/detection/yolov8), が含まれる **Python** 配備状況と**C++** 配備状況;
- FastDeployの1行モデルAPIスイッチにより、YOLOv8、PP-YOLOE+、YOLOv5、その他のモデルの性能比較が可能になります
- **✨👥✨ 交流**
- **Slack**Join our [Slack community](https://join.slack.com/t/fastdeployworkspace/shared_invite/zt-1m88mytoi-mBdMYcnTF~9LCKSOKXd6Tg) and chat with other community members about ideas
- **WeChat**: QRコードを読み取り、アンケートに答えてテクニカルコミュニティに参加し、コミュニティ開発者と展開業界の実装の悩みについて交流することができます
<div align="center">
<img src="https://user-images.githubusercontent.com/54695910/200145290-d5565d18-6707-4a0b-a9af-85fd36d35d13.jpg" width = "150" height = "150" />
</div>
<div id="fastdeploy-acknowledge"></div>
## 🌌 推論バックエンドと機能
<font size=0.5em>
| | ビデオストリーミング | サービス指向の展開 |エンドツーエンドのパフォーマンス最適化| Linux | Windows | Android |macOS |
|:----------|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|
| X86_64&nbsp;CPU | |&nbsp;&nbsp;&nbsp;<img src="https://user-images.githubusercontent.com/54695910/212545467-e64ee45d-bf12-492c-b263-b860cb1e172b.png" height = "25"/>&nbsp;&nbsp;&nbsp; | <img src="https://user-images.githubusercontent.com/54695910/212474104-d82f3545-04d4-4ddd-b240-ffac34d8a920.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473391-92c9f289-a81a-4927-9f31-1ab3fa3c2971.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473392-9df374d4-5daa-4e2b-856b-6e50ff1e4282.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473190-fdf3cee2-5670-47b5-85e7-6853a8dd200a.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473391-92c9f289-a81a-4927-9f31-1ab3fa3c2971.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473392-9df374d4-5daa-4e2b-856b-6e50ff1e4282.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473190-fdf3cee2-5670-47b5-85e7-6853a8dd200a.svg" height = "17"/> | | <img src="https://user-images.githubusercontent.com/54695910/212473391-92c9f289-a81a-4927-9f31-1ab3fa3c2971.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473392-9df374d4-5daa-4e2b-856b-6e50ff1e4282.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473190-fdf3cee2-5670-47b5-85e7-6853a8dd200a.svg" height = "17"/> |
| NVDIA&nbsp;GPU | <img src="https://user-images.githubusercontent.com/54695910/212545467-e64ee45d-bf12-492c-b263-b860cb1e172b.png" height = "25"/> | <img src="https://user-images.githubusercontent.com/54695910/212545467-e64ee45d-bf12-492c-b263-b860cb1e172b.png" height = "25"/> | <img src="https://user-images.githubusercontent.com/54695910/212474106-a297aa0d-9225-458e-b5b7-e31aec7cfa79.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212474104-d82f3545-04d4-4ddd-b240-ffac34d8a920.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473390-cebf7880-7c47-407d-94ae-01784d6a23d1.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473556-d2ebb7cc-e72b-4b49-896b-83f95ae1fe63.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473190-fdf3cee2-5670-47b5-85e7-6853a8dd200a.svg" height = "17"/> |<img src="https://user-images.githubusercontent.com/54695910/212473390-cebf7880-7c47-407d-94ae-01784d6a23d1.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473556-d2ebb7cc-e72b-4b49-896b-83f95ae1fe63.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473190-fdf3cee2-5670-47b5-85e7-6853a8dd200a.svg" height = "17"/> | | |
|Phytium CPU | | | <img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473393-ae1958bd-ab7d-4863-94b9-32863e600ba1.svg" height = "17"/> | | | |
| KunlunXin XPU | | | <img src="https://user-images.githubusercontent.com/54695910/212474104-d82f3545-04d4-4ddd-b240-ffac34d8a920.svg" height = "17"/> |<img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/> | | | |
| Huawei Ascend NPU | | | <img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212474104-d82f3545-04d4-4ddd-b240-ffac34d8a920.svg" height = "17"/>| <img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/> | | | |
|Graphcore&nbsp;IPU | | <img src="https://user-images.githubusercontent.com/54695910/212545467-e64ee45d-bf12-492c-b263-b860cb1e172b.png" height = "25"/> | | <img src="https://user-images.githubusercontent.com/54695910/212473391-92c9f289-a81a-4927-9f31-1ab3fa3c2971.svg" height = "17"/> | | | |
| Sophgo | | | | <img src="https://user-images.githubusercontent.com/54695910/212473382-e3e9063f-c298-4b61-ad35-a114aa6e6555.svg" height = "17"/> | | | |
|Intel graphics card | | | | <img src="https://user-images.githubusercontent.com/54695910/212473392-9df374d4-5daa-4e2b-856b-6e50ff1e4282.svg" height = "17"/> | | | |
|Jetson |<img src="https://user-images.githubusercontent.com/54695910/212545467-e64ee45d-bf12-492c-b263-b860cb1e172b.png" height = "25"/> | <img src="https://user-images.githubusercontent.com/54695910/212545467-e64ee45d-bf12-492c-b263-b860cb1e172b.png" height = "25"/> | <img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212474106-a297aa0d-9225-458e-b5b7-e31aec7cfa79.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473390-cebf7880-7c47-407d-94ae-01784d6a23d1.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473556-d2ebb7cc-e72b-4b49-896b-83f95ae1fe63.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473190-fdf3cee2-5670-47b5-85e7-6853a8dd200a.svg" height = "17"/> | | | |
|ARM&nbsp;CPU | | | <img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212474104-d82f3545-04d4-4ddd-b240-ffac34d8a920.svg" height = "17"/>| <img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473393-ae1958bd-ab7d-4863-94b9-32863e600ba1.svg" height = "17"/> | | <img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473393-ae1958bd-ab7d-4863-94b9-32863e600ba1.svg" height = "17"/> |
|RK3588 etc. | | | <img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473387-2559cc2a-024b-4452-806c-6105d8eb2339.svg" height = "17"/> | | | |
|RV1126 etc. | | | <img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/> | | | |
| Amlogic | | | <img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/> | | | |
| NXP | | | <img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/> |<img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/> | | | |
</font>
## 🔮 ドキュメント・チュートリアル
- [✴️ Python SDK クイックスタート](#fastdeploy-quick-start-python)
- [✴️ C++ SDK クイックスタート](#fastdeploy-quick-start-cpp)
- **インストールドキュメント**
- [プリコンパイルされたライブラリのダウンロードとインストール](./../../docs/en/build_and_install/download_prebuilt_libraries.md)
- [GPU デプロイメント環境のコンパイルとインストール](./../../docs/en/build_and_install/gpu.md)
- [CPU デプロイメント環境のコンパイルとインストール](./../../docs/en/build_and_install/cpu.md)
- [IPU デプロイメント環境のコンパイルとインストール](./../../docs/en/build_and_install/ipu.md)
- [KunlunXin XPUデプロイメント環境のコンパイルとインストール](./../../docs/en/build_and_install/kunlunxin.md)
- [Rockchip RV1126 デプロイメント環境のコンパイルとインストール](./../../docs/en/build_and_install/rv1126.md)
- [Rockchip RK3588 デプロイメント環境のコンパイルとインストール](./../../docs/en/build_and_install/rknpu2.md)
- [Amlogic A311D デプロイメント環境のコンパイルとインストール](./../../docs/en/build_and_install/a311d.md)
- [Huawei Ascend デプロイメント環境のコンパイルとインストール](./../../docs/en/build_and_install/huawei_ascend.md)
- [Jetson デプロイメント環境のコンパイルとインストール](./../../docs/en/build_and_install/jetson.md)
- [Android デプロイメント環境のコンパイルとインストール](./../../docs/en/build_and_install/android.md)
- **クイックユース**
- [PP-YOLOE Python 展開例](./../../docs/en/quick_start/models/python.md)
- [PP-YOLOE C++ 展開例](./../../docs/en/quick_start/models/cpp.md)
- **バックエンドの利用**
- [Runtime Python 使用例](./../../docs/en/quick_start/runtime/python.md)
- [Runtime C++ 使用例](./../../docs/en/quick_start/runtime/cpp.md)
- [モデルデプロイメントのための推論バックエンドの設定方法](./../../docs/en/faq/how_to_change_backend.md)
- **サービス・デプロイメント**
- [サービス展開イメージのコンパイルとインストール](./../../serving/docs/zh_CN/compile.md)
- [サービス・デプロイメント](./../../serving)
- **API ドキュメンテーション**
- [Python API ドキュメンテーション](https://www.paddlepaddle.org.cn/fastdeploy-api-doc/python/html/)
- [C++ API ドキュメンテーション](https://www.paddlepaddle.org.cn/fastdeploy-api-doc/cpp/html/)
- [Android Java API ドキュメンテーション](./../../java/android)
- **パフォーマンスチューニング**
- [量的加速](./../../docs/cn/quantize.md)
- [マルチスレッド・マルチプロセスの使用](./../../tutorials/multi_thread)
- **よくある質問**
- [1. Windows上C++ SDK の場合使用方法](./../../docs/en/faq/use_sdk_on_windows.md)
- [2. FastDeploy C++ SDKをAndroidで使用する方法](./../../docs/en/faq/use_cpp_sdk_on_android.md)
- [3. TensorRT 使い方のコツ](./../../docs/en/faq/tensorrt_tricks.md)
- **続きを読むFastDeployモジュールのデプロイメント**
- [Benchmark テスト](./../../benchmark)
- **モデル対応表**
- [🖥️ サーバーサイドモデル対応表](#fastdeploy-server-models)
- [📳 モバイル・エンド側モデル対応表](#fastdeploy-edge-models)
- [⚛️ アプレットモデル対応表](#fastdeploy-web-models)
- **💕 開発者拠出金**
- [新規モデルの追加](./../../docs/en/faq/develop_a_new_model.md)
<div id="fastdeploy-quick-start-python"></div>
## クイックスタート💨
<details Open>
<summary><b>Python SDKクイックスタートタップで縮小</b></summary><div>
### 🎆 クイックインストール
#### 🔸 先行依存関係
- CUDA >= 11.2、cuDNN >= 8.0、Python >= 3.6
- OS: Linux x86_64/macOS/Windows 10
#### 🔸 インストールGPUバージョン
```bash
pip install numpy opencv-python fastdeploy-gpu-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
```
#### [🔸 Conda のインストール(推奨✨)](./../../docs/cn/build_and_install/download_prebuilt_libraries.md)
```bash
conda config --add channels conda-forge && conda install cudatoolkit=11.2 cudnn=8.2
```
#### 🔸 インストールCPUバージョン
```bash
pip install numpy opencv-python fastdeploy-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
```
### 🎇 Python 推論例
* モデルや画像の準備
```bash
wget https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz
tar xvf ppyoloe_crn_l_300e_coco.tgz
wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
```
* 推論結果のテスト
```python
# GPU/TensorRT デプロイメント、リファレンスexamples/vision/detection/paddledetection/python
import cv2
import fastdeploy.vision as vision
model = vision.detection.PPYOLOE("ppyoloe_crn_l_300e_coco/model.pdmodel",
"ppyoloe_crn_l_300e_coco/model.pdiparams",
"ppyoloe_crn_l_300e_coco/infer_cfg.yml")
im = cv2.imread("000000014439.jpg")
result = model.predict(im)
print(result)
vis_im = vision.vis_detection(im, result, score_threshold=0.5)
cv2.imwrite("vis_image.jpg", vis_im)
```
</div></details>
<div id="fastdeploy-quick-start-cpp"></div>
<details close>
<summary><b>C++ SDK クイックスタート(クリックすると詳細が表示されます) </b></summary><div>
### 🎆 インストール
- リファレンス[C++ プリコンパイルライブラリのダウンロード](./../../docs/cn/build_and_install/download_prebuilt_libraries.md)文档
#### 🎇 C++ 推論例
* モデルや画像の準備
```bash
wget https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz
tar xvf ppyoloe_crn_l_300e_coco.tgz
wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
```
* 推論結果のテスト
```C++
// GPU/TensorRT デプロイメント、リファレンス examples/vision/detection/paddledetection/cpp
#include "fastdeploy/vision.h"
int main(int argc, char* argv[]) {
namespace vision = fastdeploy::vision;
auto model = vision::detection::PPYOLOE("ppyoloe_crn_l_300e_coco/model.pdmodel",
"ppyoloe_crn_l_300e_coco/model.pdiparams",
"ppyoloe_crn_l_300e_coco/infer_cfg.yml");
auto im = cv::imread("000000014439.jpg");
vision::DetectionResult res;
model.Predict(im, &res);
auto vis_im = vision::VisDetection(im, res, 0.5);
cv::imwrite("vis_image.jpg", vis_im);
return 0;
}
```
</div></details>
その他の展開例は、以下を参照してください[モデル展開例](./../../examples) .
<div id="fastdeploy-server-models"></div>
## ✴️ ✴️ サーバーサイドモデル対応表 ✴️ ✴️
表記: (1) ✅: 対応済み; (2) ❔:進行中 ; (3) N/A: 未対応; <br>
<details open><summary><b> サーバーサイドモデル対応一覧(クリックで縮小します)</b></summary><div>
<div align="center">
<img src="https://user-images.githubusercontent.com/54695910/198620704-741523c1-dec7-44e5-9f2b-29ddd9997344.png"/>
</div>
| ミッションシナリオ | モデル | Linux | Linux | Win | Win | Mac | Mac | Linux | Linux | Linux | Linux | Linux |
|:----------------------:|:--------------------------------------------------------------------------------------------:|:------------------------------------------------:|:----------:|:-------:|:----------:|:-------:|:-------:|:-----------:|:---------------:|:-------------:|:-------------:|:-------:|
| --- | --- | X86 CPU | NVIDIA GPU | X86 CPU | NVIDIA GPU | X86 CPU | Arm CPU | AArch64 CPU | Phytium D2000CPU | NVIDIA Jetson | Graphcore IPU | Serving |
| Classification | [PaddleClas/ResNet50](./../../examples/vision/classification/paddleclas) | [](./../../examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Classification | [TorchVison/ResNet](./../../examples/vision/classification/resnet) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| Classification | [ultralytics/YOLOv5Cls](./../../examples/vision/classification/yolov5cls) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| Classification | [PaddleClas/PP-LCNet](./../../examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Classification | [PaddleClas/PP-LCNetv2](./../../examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Classification | [PaddleClas/EfficientNet](./../../examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Classification | [PaddleClas/GhostNet](./../../examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Classification | [PaddleClas/MobileNetV1](./../../examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Classification | [PaddleClas/MobileNetV2](./../../examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Classification | [PaddleClas/MobileNetV3](./../../examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Classification | [PaddleClas/ShuffleNetV2](./../../examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Classification | [PaddleClas/SqueeezeNetV1.1](./../../examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Classification | [PaddleClas/Inceptionv3](./../../examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
| Classification | [PaddleClas/PP-HGNet](./../../examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Detection | [PaddleDetection/PP-YOLOE](./.../../examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
| Detection | [🔥PaddleDetection/YOLOv8](./../../examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |✅ | ❔ |
| Detection | [🔥ultralytics/YOLOv8](./../../examples/vision/detection/yolov8) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |❔ | ❔ |
| Detection | [PaddleDetection/PicoDet](./../../examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
| Detection | [PaddleDetection/YOLOX](./../../examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
| Detection | [PaddleDetection/YOLOv3](./../../examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
| Detection | [PaddleDetection/PP-YOLO](./../../examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
| Detection | [PaddleDetection/PP-YOLOv2](./../../examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
| Detection | [PaddleDetection/Faster-RCNN](./../../examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
| Detection | [PaddleDetection/Mask-RCNN](./../../examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
| Detection | [Megvii-BaseDetection/YOLOX](./../../examples/vision/detection/yolox) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| Detection | [WongKinYiu/YOLOv7](./../../examples/vision/detection/yolov7) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| Detection | [WongKinYiu/YOLOv7end2end_trt](./../../examples/vision/detection/yolov7end2end_trt) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| Detection | [WongKinYiu/YOLOv7end2end_ort](./../../examples/vision/detection/yolov7end2end_ort) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| Detection | [meituan/YOLOv6](./../../examples/vision/detection/yolov6) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| Detection | [ultralytics/YOLOv5](./../../examples/vision/detection/yolov5) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
| Detection | [WongKinYiu/YOLOR](./../../examples/vision/detection/yolor) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| Detection | [WongKinYiu/ScaledYOLOv4](./../../examples/vision/detection/scaledyolov4) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| Detection | [ppogg/YOLOv5Lite](./../../examples/vision/detection/yolov5lite) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| Detection | [RangiLyu/NanoDetPlus](./../../examples/vision/detection/nanodet_plus) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| KeyPoint | [PaddleDetection/TinyPose](./../../examples/vision/keypointdetection/tiny_pose) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| KeyPoint | [PaddleDetection/PicoDet + TinyPose](./../../examples/vision/keypointdetection/det_keypoint_unite) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| HeadPose | [omasaht/headpose](./../../examples/vision/headpose) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| Tracking | [PaddleDetection/PP-Tracking](./../../examples/vision/tracking/pptracking) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| OCR | [PaddleOCR/PP-OCRv2](./../../examples/vision/ocr) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| OCR | [PaddleOCR/PP-OCRv3](./../../examples/vision/ocr) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
| Segmentation | [PaddleSeg/PP-LiteSeg](./../../examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| Segmentation | [PaddleSeg/PP-HumanSegLite](./../../examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| Segmentation | [PaddleSeg/HRNet](./../../examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| Segmentation | [PaddleSeg/PP-HumanSegServer](./../../examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| Segmentation | [PaddleSeg/Unet](./../../examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| Segmentation | [PaddleSeg/Deeplabv3](./../../examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| FaceDetection | [biubug6/RetinaFace](./../../examples/vision/facedet/retinaface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| FaceDetection | [Linzaer/UltraFace](./../../examples/vision/facedet/ultraface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| FaceDetection | [deepcam-cn/YOLOv5Face](./../../examples/vision/facedet/yolov5face) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| FaceDetection | [insightface/SCRFD](./../../examples/vision/facedet/scrfd) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| FaceAlign | [Hsintao/PFLD](./../../examples/vision/facealign/pfld) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| FaceAlign | [Single430FaceLandmark1000](./../../examples/vision/facealign/face_landmark_1000) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| FaceAlign | [jhb86253817/PIPNet](./../../examples/vision/facealign) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| FaceRecognition | [insightface/ArcFace](./../../examples/vision/faceid/insightface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| FaceRecognition | [insightface/CosFace](./../../examples/vision/faceid/insightface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| FaceRecognition | [insightface/PartialFC](./../../examples/vision/faceid/insightface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| FaceRecognition | [insightface/VPL](./../../examples/vision/faceid/insightface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| Matting | [ZHKKKe/MODNet](./../../examples/vision/matting/modnet) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| Matting | [PeterL1n/RobustVideoMatting]() | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| Matting | [PaddleSeg/PP-Matting](./../../examples/vision/matting/ppmatting) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| Matting | [PaddleSeg/PP-HumanMatting](./../../examples/vision/matting/modnet) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| Matting | [PaddleSeg/ModNet](./../../examples/vision/matting/modnet) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
| Video Super-Resolution | [PaddleGAN/BasicVSR](./) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| Video Super-Resolution | [PaddleGAN/EDVR](./../../examples/vision/sr/edvr) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| Video Super-Resolution | [PaddleGAN/PP-MSVSR](./../../examples/vision/sr/ppmsvsr) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
| Information Extraction | [PaddleNLP/UIE](./../../examples/text/uie) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | |
| NLP | [PaddleNLP/ERNIE-3.0](./../../examples/text/ernie-3.0) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | ❔ | ✅ |
| Speech | [PaddleSpeech/PP-TTS](./../../examples/audio/pp-tts) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | -- | ✅ |
</div></details>
<div id="fastdeploy-edge-models"></div>
## 📳 エンドユーザーモデル対応表
<details open><summary><b> エンドユーザーモデル対応表(クリックで縮小)</b></summary><div>
<div align="center">
<img src="https://user-images.githubusercontent.com/54695910/198620704-741523c1-dec7-44e5-9f2b-29ddd9997344.png" />
</div>
| ミッションシナリオ | モデル | サイズ(MB) | Linux | Android | Linux | Linux | Linux | Linux | Linux | TBD... |
|:------------------:|:-----------------------------------------------------------------------------------------:|:--------:|:-------:|:-------:|:-------:|:-----------------------:|:------------------------------:|:---------------------------:|:--------------------------------:|:-------:|
| --- | --- | --- | ARM CPU | ARM CPU | Rockchip-NPU<br>RK3568/RK3588 | Rockchip-NPU<br>RV1109/RV1126/RK1808 | Amlogic-NPU <br>A311D/S905D/C308X | NXP-NPU<br>i.MX&nbsp;8M&nbsp;Plus | TBD... |
| Classification | [PaddleClas/ResNet50](./../../examples/vision/classification/paddleclas) | 98 | ✅ | ✅ | ❔ | ✅ | | | |
| Classification | [PaddleClas/PP-LCNet](./../../examples/vision/classification/paddleclas) | 11.9 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
| Classification | [PaddleClas/PP-LCNetv2](./../../examples/vision/classification/paddleclas) | 26.6 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
| Classification | [PaddleClas/EfficientNet](./../../examples/vision/classification/paddleclas) | 31.4 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
| Classification | [PaddleClas/GhostNet](./../../examples/vision/classification/paddleclas) | 20.8 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
| Classification | [PaddleClas/MobileNetV1](./../../examples/vision/classification/paddleclas) | 17 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
| Classification | [PaddleClas/MobileNetV2](./../../examples/vision/classification/paddleclas) | 14.2 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
| Classification | [PaddleClas/MobileNetV3](./../../examples/vision/classification/paddleclas) | 22 | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ | -- |
| Classification | [PaddleClas/ShuffleNetV2](./../../examples/vision/classification/paddleclas) | 9.2 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
| Classification | [PaddleClas/SqueezeNetV1.1](./../../examples/vision/classification/paddleclas) | 5 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
| Classification | [PaddleClas/Inceptionv3](./../../examples/vision/classification/paddleclas) | 95.5 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
| Classification | [PaddleClas/PP-HGNet](./../../examples/vision/classification/paddleclas) | 59 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
| Detection | [PaddleDetection/PicoDet_s](./../../examples/vision/detection/paddledetection) | 4.9 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | -- |
| Detection | [YOLOv5](./../../examples/vision/detection/rkyolo) | | ❔ | ❔ | [](./examples/vision/detection/rkyolo) | ❔ | ❔ | ❔ | -- |
| Face Detection | [deepinsight/SCRFD](./../../examples/vision/facedet/scrfd) | 2.5 | ✅ | ✅ | ✅ | -- | -- | -- | -- |
| Keypoint Detection | [PaddleDetection/PP-TinyPose](./../../examples/vision/keypointdetection/tiny_pose) | 5.5 | ✅ | ✅ | ❔ | ❔ | ❔ | ❔ | -- |
| Segmentation | [PaddleSeg/PP-LiteSeg(STDC1)](./../../examples/vision/segmentation/paddleseg) | 32.2 | ✅ | ✅ | ✅ | -- | -- | -- | -- |
| Segmentation | [PaddleSeg/PP-HumanSeg-Lite](./../../examples/vision/segmentation/paddleseg) | 0.556 | ✅ | ✅ | ✅ | -- | -- | -- | -- |
| Segmentation | [PaddleSeg/HRNet-w18](./../../examples/vision/segmentation/paddleseg) | 38.7 | ✅ | ✅ | ✅ | -- | -- | -- | -- |
| Segmentation | [PaddleSeg/PP-HumanSeg](./../../examples/vision/segmentation/paddleseg) | 107.2 | ✅ | ✅ | ✅ | -- | -- | -- | -- |
| Segmentation | [PaddleSeg/Unet](./../../examples/vision/segmentation/paddleseg) | 53.7 | ✅ | ✅ | ✅ | -- | -- | -- | -- |
| Segmentation | [PaddleSeg/Deeplabv3](./../../examples/vision/segmentation/paddleseg) | 150 | ❔ | ✅ | ✅ | | | | |
| OCR | [PaddleOCR/PP-OCRv2](./../../examples/vision/ocr/PP-OCRv2) | 2.3+4.4 | ✅ | ✅ | ❔ | -- | -- | -- | -- |
| OCR | [PaddleOCR/PP-OCRv3](./../../examples/vision/ocr/PP-OCRv3) | 2.4+10.6 | ✅ | ❔ | ❔ | ❔ | ❔ | ❔ | -- |
</div></details>
## ⚛️ アプレットモデル対応表
<div id="fastdeploy-web-models"></div>
<details open><summary><b> ウェブ・アプレット展開サポートリスト(クリックで縮小)</b></summary><div>
| ミッションシナリオ | モデル | [web_demo](./../../examples/application/js/web_demo) |
|:------------------:|:-------------------------------------------------------------------------------------------:|:--------------------------------------------:|
| --- | --- | [Paddle.js](./../../examples/application/js) |
| Detection | [FaceDetection](./../../examples/application/js/web_demo/src/pages/cv/detection) | ✅ |
| Detection | [ScrewDetection](./../../examples/application/js/web_demo/src/pages/cv/detection) | ✅ |
| Segmentation | [PaddleSeg/HumanSeg](./../../examples/application/js/web_demo/src/pages/cv/segmentation/HumanSeg) | ✅ |
| Object Recognition | [GestureRecognition](./../../examples/application/js/web_demo/src/pages/cv/recognition) | ✅ |
| Object Recognition | [ItemIdentification](./../../examples/application/js/web_demo/src/pages/cv/recognition) | ✅ |
| OCR | [PaddleOCR/PP-OCRv3](./../../examples/application/js/web_demo/src/pages/cv/ocr) | ✅ |
</div></details>
## 💐 Acknowledge
このプロジェクトでは、SDKの生成とダウンロードに [EasyEdge](https://ai.baidu.com/easyedge/app/openSource) の無償かつオープンな機能を利用しており、そのことに謝意を表したいと思います。
## ©️ License
<div id="fastdeploy-license"></div>
FastDeploy は、[Apache-2.0 オープンソースプロトコル](./../../LICENSE)に従っています