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* [Model] Support PaddleYOLOv8 model * [YOLOv8] Add PaddleYOLOv8 pybind * [Other] update from latest develop (#30) * [Backend] Remove all lite options in RuntimeOption (#1109) * Remove all lite options in RuntimeOption * Fix code error * move pybind * Fix build error * [Backend] Add TensorRT FP16 support for AdaptivePool2d (#1116) * add fp16 cuda kernel * fix code bug * update code * [Doc] Fix KunlunXin doc (#1139) fix kunlunxin doc * [Model] Support PaddleYOLOv8 model (#1136) Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: yeliang2258 <30516196+yeliang2258@users.noreply.github.com> * [YOLOv8] add PaddleYOLOv8 pybind11 (#1144) (#31) * [Model] Support PaddleYOLOv8 model * [YOLOv8] Add PaddleYOLOv8 pybind * [Other] update from latest develop (#30) * [Backend] Remove all lite options in RuntimeOption (#1109) * Remove all lite options in RuntimeOption * Fix code error * move pybind * Fix build error * [Backend] Add TensorRT FP16 support for AdaptivePool2d (#1116) * add fp16 cuda kernel * fix code bug * update code * [Doc] Fix KunlunXin doc (#1139) fix kunlunxin doc * [Model] Support PaddleYOLOv8 model (#1136) Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: yeliang2258 <30516196+yeliang2258@users.noreply.github.com> Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: yeliang2258 <30516196+yeliang2258@users.noreply.github.com> Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: yeliang2258 <30516196+yeliang2258@users.noreply.github.com> * [benchmark] add PaddleYOLOv8 -> benchmark * [benchmark] add PaddleYOLOv8 -> benchmark * [Lite] Support PaddleYOLOv8 with Lite Backend * [Pick] Update from latest develop (#32) * [Model] Support Insightface model inferenceing on RKNPU (#1113) * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * Update issues.md * Update fastdeploy_init.sh * 更新交叉编译 * 更新insightface系列模型的rknpu2支持 * 更新insightface系列模型的rknpu2支持 * 更新说明文档 * 更新insightface * 尝试解决pybind问题 Co-authored-by: Jason <928090362@qq.com> Co-authored-by: Jason <jiangjiajun@baidu.com> * [Other] Add Function For Aligning Face With Five Points (#1124) * 更新5点人脸对齐的代码 * 更新代码格式 * 解决comment * update example * 更新注释 Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> * [Lite] Support PaddleYOLOv8 with Lite Backend (#1145) * [Model] Support PaddleYOLOv8 model * [YOLOv8] Add PaddleYOLOv8 pybind * [Other] update from latest develop (#30) * [Backend] Remove all lite options in RuntimeOption (#1109) * Remove all lite options in RuntimeOption * Fix code error * move pybind * Fix build error * [Backend] Add TensorRT FP16 support for AdaptivePool2d (#1116) * add fp16 cuda kernel * fix code bug * update code * [Doc] Fix KunlunXin doc (#1139) fix kunlunxin doc * [Model] Support PaddleYOLOv8 model (#1136) Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: yeliang2258 <30516196+yeliang2258@users.noreply.github.com> * [YOLOv8] add PaddleYOLOv8 pybind11 (#1144) (#31) * [Model] Support PaddleYOLOv8 model * [YOLOv8] Add PaddleYOLOv8 pybind * [Other] update from latest develop (#30) * [Backend] Remove all lite options in RuntimeOption (#1109) * Remove all lite options in RuntimeOption * Fix code error * move pybind * Fix build error * [Backend] Add TensorRT FP16 support for AdaptivePool2d (#1116) * add fp16 cuda kernel * fix code bug * update code * [Doc] Fix KunlunXin doc (#1139) fix kunlunxin doc * [Model] Support PaddleYOLOv8 model (#1136) Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: yeliang2258 <30516196+yeliang2258@users.noreply.github.com> Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: yeliang2258 <30516196+yeliang2258@users.noreply.github.com> Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: yeliang2258 <30516196+yeliang2258@users.noreply.github.com> * [benchmark] add PaddleYOLOv8 -> benchmark * [benchmark] add PaddleYOLOv8 -> benchmark * [Lite] Support PaddleYOLOv8 with Lite Backend Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: yeliang2258 <30516196+yeliang2258@users.noreply.github.com> * [Model] Add Silero VAD example (#1107) * add vad example * fix typo * fix typo * rename file * remove model and wav * delete Vad.cc * delete Vad.h * rename and format * fix max and min * update readme * rename var * format * add params * update readme * update readme * Update README.md * Update README_CN.md Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: Zheng-Bicheng <58363586+Zheng-Bicheng@users.noreply.github.com> Co-authored-by: Jason <928090362@qq.com> Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: yeliang2258 <30516196+yeliang2258@users.noreply.github.com> Co-authored-by: Qianhe Chen <54462604+chenqianhe@users.noreply.github.com> * [YOLOv8] Support PaddleYOLOv8 on Kunlunxin&Ascend * [YOLOv8] Add PaddleYOLOv8 model download links * [YOLOv8] Add PaddleYOLOv8 Box AP Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: yeliang2258 <30516196+yeliang2258@users.noreply.github.com> Co-authored-by: Zheng-Bicheng <58363586+Zheng-Bicheng@users.noreply.github.com> Co-authored-by: Jason <928090362@qq.com> Co-authored-by: Qianhe Chen <54462604+chenqianhe@users.noreply.github.com>
93 lines
8.0 KiB
Markdown
93 lines
8.0 KiB
Markdown
[English](README.md) | 简体中文
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# PaddleDetection模型部署
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## 模型版本说明
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- [PaddleDetection Release/2.4](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4)
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## 支持模型列表
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目前FastDeploy支持如下模型的部署
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- [PP-YOLOE(含PP-YOLOE+)系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/ppyoloe)
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- [PicoDet系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/picodet)
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- [PP-YOLO系列模型(含v2)](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/ppyolo)
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- [YOLOv3系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/yolov3)
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- [YOLOX系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/yolox)
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- [FasterRCNN系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/faster_rcnn)
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- [MaskRCNN系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/mask_rcnn)
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- [SSD系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ssd)
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- [YOLOv5系列模型](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov5)
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- [YOLOv6系列模型](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6)
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- [YOLOv7系列模型](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov7)
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- [YOLOv8系列模型](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8)
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- [RTMDet系列模型](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet)
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- [CascadeRCNN系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn)
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- [PSSDet系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/rcnn_enhance)
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- [RetinaNet系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/retinanet)
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- [PPYOLOESOD系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/smalldet)
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- [FCOS系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/fcos)
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- [TTFNet系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ttfnet)
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- [TOOD系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/tood)
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- [GFL系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/gfl)
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## 导出部署模型
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在部署前，需要先将PaddleDetection导出成部署模型，导出步骤参考文档[导出模型](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.4/deploy/EXPORT_MODEL.md)
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**注意**
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- 在导出模型时不要进行NMS的去除操作，正常导出即可
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- 如果用于跑原生TensorRT后端（非Paddle Inference后端），不要添加--trt参数
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- 导出模型时，不要添加`fuse_normalize=True`参数
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## 下载预训练模型
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为了方便开发者的测试，下面提供了PaddleDetection导出的各系列模型，开发者可直接下载使用。
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其中精度指标来源于PaddleDetection中对各模型的介绍，详情各参考PaddleDetection中的说明。
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| 模型 | 参数大小 | 精度 | 备注 |
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|:---------------------------------------------------------------- |:----- |:----- | :------ |
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| [picodet_l_320_coco_lcnet](https://bj.bcebos.com/paddlehub/fastdeploy/picodet_l_320_coco_lcnet.tgz) |23MB | Box AP 42.6% |
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| [ppyoloe_crn_l_300e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz) |200MB | Box AP 51.4% |
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| [ppyoloe_plus_crn_m_80e_coco](https://bj.bcebos.com/fastdeploy/models/ppyoloe_plus_crn_m_80e_coco.tgz) |83.3MB | Box AP 49.8% |
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| [ppyolo_r50vd_dcn_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/ppyolo_r50vd_dcn_1x_coco.tgz) | 180MB | Box AP 44.8% | 暂不支持TensorRT |
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| [ppyolov2_r101vd_dcn_365e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/ppyolov2_r101vd_dcn_365e_coco.tgz) | 282MB | Box AP 49.7% | 暂不支持TensorRT |
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| [yolov3_darknet53_270e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov3_darknet53_270e_coco.tgz) |237MB | Box AP 39.1% | |
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| [yolox_s_300e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolox_s_300e_coco.tgz) | 35MB | Box AP 40.4% | |
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| [faster_rcnn_r50_vd_fpn_2x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/faster_rcnn_r50_vd_fpn_2x_coco.tgz) | 160MB | Box AP 40.8%| 暂不支持TensorRT |
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| [mask_rcnn_r50_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/mask_rcnn_r50_1x_coco.tgz) | 128M | Box AP 37.4%, Mask AP 32.8%| 暂不支持TensorRT、ORT |
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| [ssd_mobilenet_v1_300_120e_voc](https://bj.bcebos.com/paddlehub/fastdeploy/ssd_mobilenet_v1_300_120e_voc.tgz) | 24.9M | Box AP 73.8%| 暂不支持TensorRT、ORT |
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| [ssd_vgg16_300_240e_voc](https://bj.bcebos.com/paddlehub/fastdeploy/ssd_vgg16_300_240e_voc.tgz) | 106.5M | Box AP 77.8%| 暂不支持TensorRT、ORT |
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| [ssdlite_mobilenet_v1_300_coco](https://bj.bcebos.com/paddlehub/fastdeploy/ssdlite_mobilenet_v1_300_coco.tgz) | 29.1M | | 暂不支持TensorRT、ORT |
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| [rtmdet_l_300e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/rtmdet_l_300e_coco.tgz) | 224M | Box AP 51.2%| |
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| [rtmdet_s_300e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/rtmdet_s_300e_coco.tgz) | 42M | Box AP 44.5%| |
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| [yolov5_l_300e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5_l_300e_coco.tgz) | 183M | Box AP 48.9%| |
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| [yolov5_s_300e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5_s_300e_coco.tgz) | 31M | Box AP 37.6%| |
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| [yolov6_l_300e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6_l_300e_coco.tgz) | 229M | Box AP 51.0%| |
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| [yolov6_s_400e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6_s_400e_coco.tgz) | 68M | Box AP 43.4%| |
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| [yolov7_l_300e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7_l_300e_coco.tgz) | 145M | Box AP 51.0%| |
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| [yolov7_x_300e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7_x_300e_coco.tgz) | 277M | Box AP 53.0%| |
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| [cascade_rcnn_r50_fpn_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/cascade_rcnn_r50_fpn_1x_coco.tgz) | 271M | Box AP 41.1%| 暂不支持TensorRT、ORT |
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| [cascade_rcnn_r50_vd_fpn_ssld_2x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.tgz) | 271M | Box AP 45.0%| 暂不支持TensorRT、ORT |
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| [faster_rcnn_enhance_3x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/faster_rcnn_enhance_3x_coco.tgz) | 119M | Box AP 41.5%| 暂不支持TensorRT、ORT |
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| [fcos_r50_fpn_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/fcos_r50_fpn_1x_coco.tgz) | 129M | Box AP 39.6%| 暂不支持TensorRT |
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| [gfl_r50_fpn_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/gfl_r50_fpn_1x_coco.tgz) | 128M | Box AP 41.0%| 暂不支持TensorRT |
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| [ppyoloe_crn_l_80e_sliced_visdrone_640_025](https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_80e_sliced_visdrone_640_025.tgz) | 200M | Box AP 31.9%| |
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| [retinanet_r101_fpn_2x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/retinanet_r101_fpn_2x_coco.tgz) | 210M | Box AP 40.6%| 暂不支持TensorRT、ORT |
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| [retinanet_r50_fpn_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/retinanet_r50_fpn_1x_coco.tgz) | 136M | Box AP 37.5%| 暂不支持TensorRT、ORT |
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| [tood_r50_fpn_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/tood_r50_fpn_1x_coco.tgz) | 130M | Box AP 42.5%| 暂不支持TensorRT、ORT |
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| [ttfnet_darknet53_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/ttfnet_darknet53_1x_coco.tgz) | 178M | Box AP 33.5%| 暂不支持TensorRT、ORT |
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| [yolov8_x_500e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov8_x_500e_coco.tgz) | 265M | Box AP 53.8%
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| [yolov8_l_500e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov8_l_500e_coco.tgz) | 173M | Box AP 52.8%
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| [yolov8_m_500e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov8_m_500e_coco.tgz) | 99M | Box AP 50.2%
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| [yolov8_s_500e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov8_s_500e_coco.tgz) | 43M | Box AP 44.9%
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| [yolov8_n_500e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov8_n_500e_coco.tgz) | 13M | Box AP 37.3%
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## 详细部署文档
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- [Python部署](python)
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- [C++部署](cpp)
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