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25 changes: 12 additions & 13 deletions examples/vision/detection/scaledyolov4/README.md
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## 下载预训练ONNX模型

为了方便开发者的测试，下面提供了ScaledYOLOv4导出的各系列模型，开发者可直接下载使用。（下表中模型的精度来源于源官方库）
| 模型 | 大小 | 精度 |
|:---------------------------------------------------------------- |:----- |:----- |
| [ScaledYOLOv4-P5-896](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5-896.onnx) | 271MB | 51.2% |
| [ScaledYOLOv4-P5+BoF-896](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5_-896.onnx) | 271MB | 51.7% |
| [ScaledYOLOv4-P6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6-1280.onnx) | 487MB | 53.9% |
| [ScaledYOLOv4-P6+BoF-1280](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6_-1280.onnx) | 487MB | 54.4% |
| [ScaledYOLOv4-P7-1536](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p7-1536.onnx) | 1.1GB | 55.0% |
| [ScaledYOLOv4-P5](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5.onnx) | 271MB | - |
| [ScaledYOLOv4-P5+BoF](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5_.onnx) | 271MB | -|
| [ScaledYOLOv4-P6](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6.onnx) | 487MB | - |
| [ScaledYOLOv4-P6+BoF](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6_.onnx) | 487MB | - |
| [ScaledYOLOv4-P7](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p7.onnx) | 1.1GB | - |

| 模型 | 大小 | 精度 | 备注 |
|:---------------------------------------------------------------- |:----- |:----- |:----- |
| [ScaledYOLOv4-P5-896](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5-896.onnx) | 271MB | 51.2% | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License |
| [ScaledYOLOv4-P5+BoF-896](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5_-896.onnx) | 271MB | 51.7% | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License |
| [ScaledYOLOv4-P6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6-1280.onnx) | 487MB | 53.9% | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License |
| [ScaledYOLOv4-P6+BoF-1280](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6_-1280.onnx) | 487MB | 54.4% | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License |
| [ScaledYOLOv4-P7-1536](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p7-1536.onnx) | 1.1GB | 55.0% | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License |
| [ScaledYOLOv4-P5](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5.onnx) | 271MB | - | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License |
| [ScaledYOLOv4-P5+BoF](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5_.onnx) | 271MB | -| 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License |
| [ScaledYOLOv4-P6](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6.onnx) | 487MB | - | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License |
| [ScaledYOLOv4-P6+BoF](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6_.onnx) | 487MB | - | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License |
| [ScaledYOLOv4-P7](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p7.onnx) | 1.1GB | - | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License |


## 详细部署文档
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25 changes: 12 additions & 13 deletions examples/vision/detection/yolor/README.md
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## 下载预训练ONNX模型

为了方便开发者的测试，下面提供了YOLOR导出的各系列模型，开发者可直接下载使用。（下表中模型的精度来源于源官方库）
| 模型 | 大小 | 精度 |
|:---------------------------------------------------------------- |:----- |:----- |
| [YOLOR-P6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-p6-paper-541-1280-1280.onnx) | 143MB | 54.1% |
| [YOLOR-W6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-w6-paper-555-1280-1280.onnx) | 305MB | 55.5% |
| [YOLOR-E6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-e6-paper-564-1280-1280.onnx ) | 443MB | 56.4% |
| [YOLOR-D6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-570-1280-1280.onnx) | 580MB | 57.0% |
| [YOLOR-D6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-573-1280-1280.onnx) | 580MB | 57.3% |
| [YOLOR-P6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-p6-paper-541-640-640.onnx) | 143MB | - |
| [YOLOR-W6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-w6-paper-555-640-640.onnx) | 305MB | - |
| [YOLOR-E6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-e6-paper-564-640-640.onnx ) | 443MB | - |
| [YOLOR-D6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-570-640-640.onnx) | 580MB | - |
| [YOLOR-D6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-573-640-640.onnx) | 580MB | - |

| 模型 | 大小 | 精度 | 备注 |
|:---------------------------------------------------------------- |:----- |:----- |:----- |
| [YOLOR-P6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-p6-paper-541-1280-1280.onnx) | 143MB | 54.1% | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License |
| [YOLOR-W6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-w6-paper-555-1280-1280.onnx) | 305MB | 55.5% | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License |
| [YOLOR-E6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-e6-paper-564-1280-1280.onnx ) | 443MB | 56.4% | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License |
| [YOLOR-D6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-570-1280-1280.onnx) | 580MB | 57.0% | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License |
| [YOLOR-D6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-573-1280-1280.onnx) | 580MB | 57.3% | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License |
| [YOLOR-P6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-p6-paper-541-640-640.onnx) | 143MB | - | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License |
| [YOLOR-W6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-w6-paper-555-640-640.onnx) | 305MB | - | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License |
| [YOLOR-E6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-e6-paper-564-640-640.onnx ) | 443MB | - | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License |
| [YOLOR-D6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-570-640-640.onnx) | 580MB | - | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License |
| [YOLOR-D6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-573-640-640.onnx) | 580MB | - | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License |


## 详细部署文档
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14 changes: 7 additions & 7 deletions examples/vision/detection/yolov5/README.md
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## 下载预训练ONNX模型

为了方便开发者的测试，下面提供了YOLOv5导出的各系列模型，开发者可直接下载使用。（下表中模型的精度来源于源官方库）
| 模型 | 大小 | 精度 |
|:---------------------------------------------------------------- |:----- |:----- |
| [YOLOv5n](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5n.onnx) | 7.6MB | 28.0% |
| [YOLOv5s](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5s.onnx) | 28MB | 37.4% |
| [YOLOv5m](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5m.onnx) | 82MB | 45.4% |
| [YOLOv5l](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5l.onnx) | 178MB | 49.0% |
| [YOLOv5x](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5x.onnx) | 332MB | 50.7% |
| 模型 | 大小 | 精度 | 备注 |
|:---------------------------------------------------------------- |:----- |:----- |:---- |
| [YOLOv5n](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5n.onnx) | 7.6MB | 28.0% | 此模型文件来源于[YOLOv5](https://github.com/ultralytics/yolov5)，GPL-3.0 License |
| [YOLOv5s](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5s.onnx) | 28MB | 37.4% | 此模型文件来源于[YOLOv5](https://github.com/ultralytics/yolov5)，GPL-3.0 License |
| [YOLOv5m](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5m.onnx) | 82MB | 45.4% | 此模型文件来源于[YOLOv5](https://github.com/ultralytics/yolov5)，GPL-3.0 License |
| [YOLOv5l](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5l.onnx) | 178MB | 49.0% | 此模型文件来源于[YOLOv5](https://github.com/ultralytics/yolov5)，GPL-3.0 License |
| [YOLOv5x](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5x.onnx) | 332MB | 50.7% | 此模型文件来源于[YOLOv5](https://github.com/ultralytics/yolov5)，GPL-3.0 License |


## 详细部署文档
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12 changes: 6 additions & 6 deletions examples/vision/detection/yolov5lite/README.md
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## 下载预训练ONNX模型

为了方便开发者的测试，下面提供了YOLOv5Lite导出的各系列模型，开发者可直接下载使用。（下表中模型的精度来源于源官方库）
| 模型 | 大小 | 精度 |
|:---------------------------------------------------------------- |:----- |:----- |
| [YOLOv5Lite-e](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-e-sim-320.onnx) | 3.1MB | 35.1% |
| [YOLOv5Lite-s](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-s-sim-416.onnx) | 6.3MB | 42.0% |
| [YOLOv5Lite-c](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-c-sim-512.onnx) | 18MB | 50.9% |
| [YOLOv5Lite-g](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-g-sim-640.onnx) | 21MB | 57.6% |
| 模型 | 大小 | 精度 | 备注 |
|:---------------------------------------------------------------- |:----- |:----- |:----- |
| [YOLOv5Lite-e](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-e-sim-320.onnx) | 3.1MB | 35.1% | 此模型文件来源于[YOLOv5-Lite](https://github.com/ppogg/YOLOv5-Lite)，GPL-3.0 License ｜
| [YOLOv5Lite-s](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-s-sim-416.onnx) | 6.3MB | 42.0% | 此模型文件来源于[YOLOv5-Lite](https://github.com/ppogg/YOLOv5-Lite)，GPL-3.0 License |
| [YOLOv5Lite-c](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-c-sim-512.onnx) | 18MB | 50.9% | 此模型文件来源于[YOLOv5-Lite](https://github.com/ppogg/YOLOv5-Lite)，GPL-3.0 License |
| [YOLOv5Lite-g](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-g-sim-640.onnx) | 21MB | 57.6% | 此模型文件来源于[YOLOv5-Lite](https://github.com/ppogg/YOLOv5-Lite)，GPL-3.0 License |


## 详细部署文档
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## 下载预训练ONNX模型

为了方便开发者的测试，下面提供了YOLOv6导出的各系列模型，开发者可直接下载使用。（下表中模型的精度来源于源官方库）
| 模型 | 大小 | 精度 |
|:---------------------------------------------------------------- |:----- |:----- |
| [YOLOv6s](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6s.onnx) | 66MB | 43.1% |
| [YOLOv6s_640](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6s-640x640.onnx) | 66MB | 43.1% |
| [YOLOv6t](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6t.onnx) | 58MB | 41.3% |
| [YOLOv6n](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6n.onnx) | 17MB | 35.0% |

| 模型 | 大小 | 精度 | 备注 |
|:---------------------------------------------------------------- |:----- |:----- |:----- |
| [YOLOv6s](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6s.onnx) | 66MB | 43.1% | 此模型文件来源于[YOLOv6](https://github.com/meituan/YOLOv6)，GPL-3.0 License |
| [YOLOv6s_640](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6s-640x640.onnx) | 66MB | 43.1% | 此模型文件来源于[YOLOv6](https://github.com/meituan/YOLOv6)，GPL-3.0 License |
| [YOLOv6t](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6t.onnx) | 58MB | 41.3% | 此模型文件来源于[YOLOv6](https://github.com/meituan/YOLOv6)，GPL-3.0 License |
| [YOLOv6n](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6n.onnx) | 17MB | 35.0% | 此模型文件来源于[YOLOv6](https://github.com/meituan/YOLOv6)，GPL-3.0 License |


## 详细部署文档
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## 下载预训练ONNX模型

为了方便开发者的测试，下面提供了YOLOv7导出的各系列模型，开发者可直接下载使用。（下表中模型的精度来源于源官方库）
| 模型 | 大小 | 精度 |
|:---------------------------------------------------------------- |:----- |:----- |
| [YOLOv7](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7.onnx) | 141MB | 51.4% |
| [YOLOv7x](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7x.onnx) | 273MB | 53.1% |
| [YOLOv7-w6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-w6.onnx) | 269MB | 54.9% |
| [YOLOv7-e6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6.onnx) | 372MB | 56.0% |
| [YOLOv7-d6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-d6.onnx) | 511MB | 56.6% |
| [YOLOv7-e6e](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6e.onnx) | 579MB | 56.8% |


| 模型 | 大小 | 精度 | 备注 |
|:---------------------------------------------------------------- |:----- |:----- | :----- |
| [YOLOv7](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7.onnx) | 141MB | 51.4% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License |
| [YOLOv7x](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7x.onnx) | 273MB | 53.1% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License |
| [YOLOv7-w6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-w6.onnx) | 269MB | 54.9% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License |
| [YOLOv7-e6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6.onnx) | 372MB | 56.0% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License |
| [YOLOv7-d6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-d6.onnx) | 511MB | 56.6% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License |
| [YOLOv7-e6e](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6e.onnx) | 579MB | 56.8% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License |


## 详细部署文档
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To facilitate testing for developers, we provide below the models exported by YOLOv7, which developers can download and use directly. (The accuracy of the models in the table is sourced from the official library)

| Model | Size | Accuracy |
| ------------------------------------------------------------------------ | ----- | -------- |
| [YOLOv7](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7.onnx) | 141MB | 51.4% |
| [YOLOv7x](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7x.onnx) | 273MB | 53.1% |
| [YOLOv7-w6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-w6.onnx) | 269MB | 54.9% |
| [YOLOv7-e6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6.onnx) | 372MB | 56.0% |
| [YOLOv7-d6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-d6.onnx) | 511MB | 56.6% |
| [YOLOv7-e6e](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6e.onnx) | 579MB | 56.8% |
| Model | Size | Accuracy | Note |
| ------------------------------------------------------------------------ | ----- | -------- | -------- |
| [YOLOv7](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7.onnx) | 141MB | 51.4% | This model file comes from [YOLOv7](https://github.com/WongKinYiu/yolov7), GPL-3.0 License |
| [YOLOv7x](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7x.onnx) | 273MB | 53.1% | This model file comes from [YOLOv7](https://github.com/WongKinYiu/yolov7), GPL-3.0 License |
| [YOLOv7-w6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-w6.onnx) | 269MB | 54.9% | This model file comes from [YOLOv7](https://github.com/WongKinYiu/yolov7), GPL-3.0 License |
| [YOLOv7-e6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6.onnx) | 372MB | 56.0% | This model file comes from [YOLOv7](https://github.com/WongKinYiu/yolov7), GPL-3.0 License |
| [YOLOv7-d6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-d6.onnx) | 511MB | 56.6% | This model file comes from [YOLOv7](https://github.com/WongKinYiu/yolov7), GPL-3.0 License |
| [YOLOv7-e6e](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6e.onnx) | 579MB | 56.8% | This model file comes from [YOLOv7](https://github.com/WongKinYiu/yolov7), GPL-3.0 License |

## Detailed Deployment Tutorials

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