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415 lines
68 KiB
Markdown
415 lines
68 KiB
Markdown
[English](../../README_EN.md) | [简体中文](../../README_CN.md) | हिन्दी | [日本語](./README_日本語.md) | [한국인](./README_한국인.md) | [Pу́сский язы́к](./README_Pу́сский_язы́к.md)
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</p>
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<p align="center">
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<a href="./LICENSE"><img src="https://img.shields.io/badge/license-Apache%202-dfd.svg"></a>
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<a href="https://github.com/PaddlePaddle/FastDeploy/releases"><img src="https://img.shields.io/github/v/release/PaddlePaddle/FastDeploy?color=ffa"></a>
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<a href=""><img src="https://img.shields.io/badge/python-3.7+-aff.svg"></a>
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<a href=""><img src="https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-pink.svg"></a>
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<a href="https://github.com/PaddlePaddle/FastDeploy/graphs/contributors"><img src="https://img.shields.io/github/contributors/PaddlePaddle/FastDeploy?color=9ea"></a>
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<a href="https://github.com/PaddlePaddle/FastDeploy/commits"><img src="https://img.shields.io/github/commit-activity/m/PaddlePaddle/FastDeploy?color=3af"></a>
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<a href="https://github.com/PaddlePaddle/FastDeploy/issues"><img src="https://img.shields.io/github/issues/PaddlePaddle/FastDeploy?color=9cc"></a>
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<a href="https://github.com/PaddlePaddle/FastDeploy/stargazers"><img src="https://img.shields.io/github/stars/PaddlePaddle/FastDeploy?color=ccf"></a>
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</p>
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<p align="center">
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<a href="./../../docs/cn/build_and_install"><b> संस्थापन </b></a>
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<a href="./../../docs/README_EN.md"><b> दस्तावेज़ीकरण का उपयोग करें </b></a>
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<a href="./../../README_EN.md#Quick-Start"><b> तेजी से शुरू </b></a>
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<a href="https://baidu-paddle.github.io/fastdeploy-api/"><b> APIप्रलेखन </b></a>
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<a href="https://github.com/PaddlePaddle/FastDeploy/releases"><b> चेंजलॉग </b></a>
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</p>
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<div align="center">
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[<img src='https://user-images.githubusercontent.com/54695910/200465949-da478e1b-21ce-43b8-9f3f-287460e786bd.png' height="80px" width="110px">](../../examples/vision/classification)
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[<img src='https://user-images.githubusercontent.com/54695910/188054680-2f8d1952-c120-4b67-88fc-7d2d7d2378b4.gif' height="80px" width="110px">](../../examples/vision/detection)
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[<img src='https://user-images.githubusercontent.com/54695910/188054711-6119f0e7-d741-43b1-b273-9493d103d49f.gif' height="80px" width="110px">](../../examples/vision/segmentation/paddleseg)
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[<img src='https://user-images.githubusercontent.com/54695910/188054718-6395321c-8937-4fa0-881c-5b20deb92aaa.gif' height="80px" width="110px">](../../examples/vision/segmentation/paddleseg)
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[<img src='https://user-images.githubusercontent.com/54695910/188058231-a5fe1ce1-0a38-460f-9582-e0b881514908.gif' height="80px" width="110px">](../../examples/vision/matting)
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[<img src='https://user-images.githubusercontent.com/54695910/188054691-e4cb1a70-09fe-4691-bc62-5552d50bd853.gif' height="80px" width="110px">](../../examples/vision/matting)
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[<img src='https://user-images.githubusercontent.com/54695910/188054669-a85996ba-f7f3-4646-ae1f-3b7e3e353e7d.gif' height="80px" width="110px">](../../examples/vision/ocr)<br>
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[<img src='https://user-images.githubusercontent.com/54695910/188059460-9845e717-c30a-4252-bd80-b7f6d4cf30cb.png' height="80px" width="110px">](../../examples/vision/facealign)
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[<img src='https://user-images.githubusercontent.com/54695910/188054671-394db8dd-537c-42b1-9d90-468d7ad1530e.gif' height="80px" width="110px">](../../examples/vision/keypointdetection)
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[<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)
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[<img src='https://user-images.githubusercontent.com/54695910/200162475-f5d85d70-18fb-4930-8e7e-9ca065c1d618.gif' height="80px" width="110px">](../../examples/text)
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[<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)
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</div>
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**⚡️फास्टडिप्लोय**एक एआई अनुमान तैनाती उपकरण है जो **सभी परिदृश्य**, **उपयोग करने में आसान और लचीला** और **बेहद कुशल** है। एक📦**आउट-ऑफ-द-बॉक्स** **क्लाउड-एज** परिनियोजन अनुभव प्रदान करता है, 🔥160+ से अधिक **टेक्स्ट**, **विजन**, **स्पीच** और **क्रॉस-मोडल** मॉडल का समर्थन करता है, और 🔚 **एंड-टू-एंड** अनुमान प्रदर्शन अनुकूलन को लागू करता है। डेवलपर्स की जरूरतों को पूरा करने के लिए छवि वर्गीकरण, ऑब्जेक्ट डिटेक्शन, छवि विभाजन, चेहरे का पता लगाने, चेहरे की पहचान, मुख्य बिंदु का पता लगाने, कटआउट, ओसीआर, एनएलपी, टीटीएस और अन्य कार्यों सहित **बहु-परिदृश्य, बहु-हार्डवेयर, बहु-मंच** उद्योग की तैनाती की जरूरत है।
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<div align="center">
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<img src="https://user-images.githubusercontent.com/115439700/212800436-9cb39830-fca5-4b40-9def-a1fd83fcfc90.png" >
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</div>
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## 🌠 ताज़ा अपडेट
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- ✨✨✨ **2023.01.17** यह रिलीज फास्ट डिसेनियोजित हार्डवेयर श्रृंखला पर [**YOLOv8**](./../../examples/vision/detection/paddledetection/) की तैनाती का समर्थन करता है। जो भी शामिल [**Paddle YOLOv8**](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8) तथा [**समुदाय ultralytics YOLOv8**](https://github.com/ultralytics/ultralytics)
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- [**Paddle YOLOv8**](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8) हार्डवेयर निर्दिष्ट करता है जो तैनात किया जा सकता है।[**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), शामिल **Python** तैनाती तथा **C++** तैनाती；**गणना ऊर्जा** और **RK3588** अद्यतन किया जा रहा है।
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- [**समुदाय ultralytics YOLOv8**](https://github.com/ultralytics/ultralytics)[**Intel CPU**] हार्डवेयर निर्दिष्ट करता है जो तैनात किया जा सकता है।(./examples/vision/detection/yolov8)、[**NVIDIA GPU**](./../../examples/vision/detection/yolov8)、[**Jetson**](./../../examples/vision/detection/yolov8), शामिल **Python** तैनाती तथा **C++** तैनाती；
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- FastDeploy एक लाइन मॉडल API स्विचन **YOLOv8**、 **PP-YOLOE+**、**YOLOv5** और अन्य मॉडलों की प्रदर्शन तुलना का एहसास कर सकते हैं।
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- **✨👥✨ सामुदायिक संचार**
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- **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
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- **WeChat**: दो आयामी कोड स्कैन करें, तकनीकी समुदाय में शामिल होने के लिए प्रश्नावली भरें और समुदाय डेवलपर्स के साथ तैनात उद्योग से होने वाले दर्द बिंदुओं के बारे में संवाद करें।
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<div align="center">
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<img src="https://user-images.githubusercontent.com/54695910/200145290-d5565d18-6707-4a0b-a9af-85fd36d35d13.jpg" width = "150" height = "150" />
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</div>
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<div id="fastdeploy-acknowledge"></div>
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## 🌌 तर्क वापस अंत और क्षमता
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<font size=0.5em>
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| | वीडियो स्ट्रीम | सेवाकरण परिनियोजन |एंड टू एंड परफॉरमेंस ऑप्टिमाइज़ेशन।| Linux | Windows | Android |macOS |
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| X86_64 CPU | | <img src="https://user-images.githubusercontent.com/54695910/212545467-e64ee45d-bf12-492c-b263-b860cb1e172b.png" height = "25"/> | <img src="https://user-images.githubusercontent.com/54695910/212474104-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"/> |
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| NVDIA 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"/> | | |
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|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"/> | | | |
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| 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"/> | | | |
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| 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"/> | | | |
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|Graphcore 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"/> | | | |
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| Sophgo | | | | <img src="https://user-images.githubusercontent.com/54695910/212473382-e3e9063f-c298-4b61-ad35-a114aa6e6555.svg" height = "17"/> | | | |
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|Intel graphics card | | | | <img src="https://user-images.githubusercontent.com/54695910/212473392-9df374d4-5daa-4e2b-856b-6e50ff1e4282.svg" height = "17"/> | | | |
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|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"/> | | | |
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|ARM 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"/> |
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|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"/> | | | |
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|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"/> | | | |
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| 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"/> | | | |
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| 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>
|
||
|
||
|
||
## 🔮 प्रलेखन ट्यूटोरियल
|
||
- [✴️ Python SDK तेजी से शुरू](#fastdeploy-quick-start-python)
|
||
- [✴️ C++ SDK तेजी से शुरू](#fastdeploy-quick-start-cpp)
|
||
- **संस्थापन दस्तावेज़**
|
||
- [प्रीकम्पाइल लाइब्रेरी को डाउनलोड और इंस्टॉल करें](./../../docs/en/build_and_install/download_prebuilt_libraries.md)
|
||
- [GPU संकलन और तैनाती पर्यावरण स्थापित करें](./../../docs/en/build_and_install/gpu.md)
|
||
- [CPU संकलन और तैनाती पर्यावरण स्थापित करें](./../../docs/en/build_and_install/cpu.md)
|
||
- [IPU संकलन और तैनाती पर्यावरण स्थापित करें](./../../docs/en/build_and_install/ipu.md)
|
||
- [KunlunXin XPU संकलन और तैनाती पर्यावरण स्थापित करें](./../../docs/en/build_and_install/kunlunxin.md)
|
||
- [Rockchip RV1126 संकलन और तैनाती पर्यावरण स्थापित करें](./../../docs/en/build_and_install/rv1126.md)
|
||
- [Rockchip RK3588 संकलन और तैनाती पर्यावरण स्थापित करें](./../../docs/en/build_and_install/rknpu2.md)
|
||
- [Amlogic A311D संकलन और तैनाती पर्यावरण स्थापित करें](./../../docs/en/build_and_install/a311d.md)
|
||
- [Huawei Ascend संकलन और तैनाती पर्यावरण स्थापित करें](./../../docs/en/build_and_install/huawei_ascend.md)
|
||
- [Jetson संकलन और तैनाती पर्यावरण स्थापित करें](./../../docs/en/build_and_install/jetson.md)
|
||
- [Android संकलन और तैनाती पर्यावरण स्थापित करें](./../../docs/en/build_and_install/android.md)
|
||
- **त्वरित उपयोग**
|
||
- [PP-YOLOE Python तैनाती उदाहरण](./../../docs/en/quick_start/models/python.md)
|
||
- [PP-YOLOE C++ तैनाती उदाहरण](./../../docs/en/quick_start/models/cpp.md)
|
||
- **पीछे के अंत का उपयोग करें**
|
||
- [Runtime Python उदाहरण का उपयोग करें](./../../docs/en/quick_start/runtime/python.md)
|
||
- [Runtime C++ उदाहरण का उपयोग करें](./../../docs/en/quick_start/runtime/cpp.md)
|
||
- [मॉडल परिनियोजन के लिए तर्क संबंधी अंत को मैं कैसे कॉन्फ़िगर करूं](./../../docs/en/faq/how_to_change_backend.md)
|
||
- **सेवाकरण परिनियोजन**
|
||
- [सेवा तैनाती छवि संकलन और स्थापना](./../../serving/docs/EN/compile-en.md)
|
||
- [सेवाकरण परिनियोजन](./../../serving)
|
||
- **API दस्तावेज़**
|
||
- [Python API दस्तावेज़](https://www.paddlepaddle.org.cn/fastdeploy-api-doc/python/html/)
|
||
- [C++ API दस्तावेज़](https://www.paddlepaddle.org.cn/fastdeploy-api-doc/cpp/html/)
|
||
- [Android Java API दस्तावेज़](./../../java/android)
|
||
- **परफ़ॉर्मेंस ट्यूनिंग**
|
||
- [त्वरण त्वरण](./../../docs/en/quantize.md)
|
||
- [मल्टी थ्रेडेड मल्टी प्रोसेस उपयोग](./../../tutorials/multi_thread)
|
||
- **क्यू एंड ए**
|
||
- [1. Windows कै से इस्तेमाल करे C++ SDK](./../../docs/en/faq/use_sdk_on_windows.md)
|
||
- [2. Android कैसे इस्तेमाल करे FastDeploy C++ SDK](./../../docs/en/faq/use_cpp_sdk_on_android.md)
|
||
- [3. TensorRT उपयोग की जा रही कुछ तकनीकें](./../../docs/en/faq/tensorrt_tricks.md)
|
||
- **अधिक Fastअधिक Deploy परिनियोजन मॉड्यूल**
|
||
- [Benchmark परीक्षण](./../../benchmark)
|
||
- **मॉडल समर्थन सूची**
|
||
- [🖥️ सर्वर साइड मॉडल सूचियों का समर्थन करता है](#fastdeploy-server-models)
|
||
- [📳 मोबाइल और एंड-साइड मॉडल समर्थन सूची](#fastdeploy-edge-models)
|
||
- [⚛️ Web और छोटे कार्यक्रम मॉडल समर्थन सूची](#fastdeploy-web-models)
|
||
- **💕डेवलपर योगदान**
|
||
- [नया मॉडल जोड़ें](./../../docs/en/faq/develop_a_new_model.md)
|
||
|
||
|
||
|
||
<div id="fastdeploy-quick-start-python"></div>
|
||
|
||
## तेजी से शुरू💨
|
||
|
||
<details Open>
|
||
|
||
<summary><b>Python SDK तेजी से (खोलें और सिकोड़ें)b></summary><div>
|
||
|
||
### 🎆 त्वरित स्थापना
|
||
|
||
#### 🔸 पूर्वता
|
||
|
||
- CUDA >= 11.2、cuDNN >= 8.0、Python >= 3.6
|
||
- OS: Linux x86_64/macOS/Windows 10
|
||
|
||
#### 🔸 इंस्टॉल करें GPU संस्करण
|
||
|
||
```bash
|
||
pip install numpy opencv-python fastdeploy-gpu-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
|
||
```
|
||
|
||
#### [🔸 Conda स्थापना (अनुशंसित✨)](./../../docs/en/build_and_install/download_prebuilt_libraries.md)
|
||
|
||
```bash
|
||
conda config --add channels conda-forge && conda install cudatoolkit=11.2 cudnn=8.2
|
||
```
|
||
|
||
#### 🔸 इंस्टॉल करें CPU संस्करण
|
||
|
||
```bash
|
||
pip install numpy opencv-python fastdeploy-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
|
||
```
|
||
|
||
### 🎇 Python अनुमान उदाहरण
|
||
|
||
* मॉडल और तस्वीरें तैयार करें
|
||
|
||
```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
|
||
```
|
||
|
||
* परीक्षण अनुमान परिणाम
|
||
|
||
```python
|
||
# GPU/TensorRT तैनाती, संदर्भ 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 तेजी से शुरू (अधिक जानकारी के लिए क्लिक करें)</b></summary><div>
|
||
|
||
|
||
### 🎆 इंस्टॉल करें
|
||
|
||
- संदर्भ [C++ प्रीकम्पाइल लाइब्रेरी डाउनलोड](./../../docs/cn/build_and_install/download_prebuilt_libraries.md)文档
|
||
|
||
#### 🎇 C++ अनुमान उदाहरण
|
||
|
||
* मॉडल और तस्वीरें तैयार करें
|
||
|
||
```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
|
||
```
|
||
|
||
* परीक्षण अनुमान परिणाम
|
||
|
||
```C++
|
||
// GPU/TensorRT तैनाती, संदर्भ 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>
|
||
|
||
अधिक तैनाती के मामलों के लिए, देखें[मॉडल परिनियोजन उदाहरण](./../../examples) .
|
||
|
||
|
||
<div id="fastdeploy-server-models"></div>
|
||
|
||
|
||
## ✴️ ✴️ सर्वर साइड मॉडल सूचियों का समर्थन करता है ✴️ ✴️
|
||
|
||
प्रतीक विवरण: (1) ✅: पहले से समर्थित; (2) ❔:गति पर ; (3) N/A: समर्थित नहीं; <br>
|
||
|
||
<details open><summary><b> सर्वर-साइड मॉडल समर्थन सूची (ढहने के लिए क्लिक करें)</b></summary><div>
|
||
|
||
<div align="center">
|
||
<img src="https://user-images.githubusercontent.com/54695910/198620704-741523c1-dec7-44e5-9f2b-29ddd9997344.png"/>
|
||
</div>
|
||
|
||
| कार्य परिदृश्य | नमूना | 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) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
|
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| OCR | [PaddleOCR/PP-OCRv2](./../../examples/vision/ocr) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
|
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| OCR | [PaddleOCR/PP-OCRv3](./../../examples/vision/ocr) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
|
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| Segmentation | [PaddleSeg/PP-LiteSeg](./../../examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
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| Segmentation | [PaddleSeg/PP-HumanSegLite](./../../examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
|
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| Segmentation | [PaddleSeg/HRNet](./../../examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
|
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| Segmentation | [PaddleSeg/PP-HumanSegServer](./../../examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
|
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| Segmentation | [PaddleSeg/Unet](./../../examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
|
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| Segmentation | [PaddleSeg/Deeplabv3](./../../examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
|
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| FaceDetection | [biubug6/RetinaFace](./../../examples/vision/facedet/retinaface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
|
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| FaceDetection | [Linzaer/UltraFace](./../../examples/vision/facedet/ultraface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
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| FaceDetection | [deepcam-cn/YOLOv5Face](./../../examples/vision/facedet/yolov5face) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
|
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| FaceDetection | [insightface/SCRFD](./../../examples/vision/facedet/scrfd) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
|
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| FaceAlign | [Hsintao/PFLD](./../../examples/vision/facealign/pfld) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
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| FaceAlign | [Single430FaceLandmark1000](./../../examples/vision/facealign/face_landmark_1000) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
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| FaceAlign | [jhb86253817/PIPNet](./../../examples/vision/facealign) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
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| FaceRecognition | [insightface/ArcFace](./../../examples/vision/faceid/insightface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
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| FaceRecognition | [insightface/CosFace](./../../examples/vision/faceid/insightface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
|
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| FaceRecognition | [insightface/PartialFC](./../../examples/vision/faceid/insightface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
|
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| 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) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
|
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| 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>
|
||
|
||
## 📲 मोबाइल और एंड-साइड मॉडल समर्थन सूची
|
||
|
||
<details open><summary><b> एंड-साइड मॉडल समर्थन सूची (पतन के लिए क्लिक करें)</b></summary><div>
|
||
|
||
<div align="center">
|
||
<img src="https://user-images.githubusercontent.com/54695910/198620704-741523c1-dec7-44e5-9f2b-29ddd9997344.png" />
|
||
</div>
|
||
|
||
| कार्य परिदृश्य | नमूना | आकार(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 8M 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>
|
||
|
||
## ⚛️ Web और छोटे कार्यक्रम मॉडल समर्थन सूची
|
||
|
||
<div id="fastdeploy-web-models"></div>
|
||
|
||
<details open><summary><b>Web और मिनी प्रोग्राम परिनियोजन समर्थन सूची (ढहने के लिए क्लिक करें)</b></summary><div>
|
||
|
||
| कार्य परिदृश्य | नमूना | [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
|
||
|
||
यह परियोजना SDK पीढ़ी और डाउनलोड हम [EasyEdge](https://ai.baidu.com/easyedge/app/openSource) में मुक्त और खुली क्षमताओं का उपयोग करने के लिए आभारी हैं।
|
||
|
||
## ©️ License
|
||
|
||
<div id="fastdeploy-license"></div>
|
||
|
||
FastDeploy निम्नानुसार है [Apache-2.0 खुला स्रोत लाइसेंस](./../../LICENSE)
|