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PaddleDetection
未验证 提交 3db9da4c 编写于 作者: K Kaipeng Deng 提交者： GitHub
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fix YOLOv3_ENHANCE_MODEL dead link (#242)

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docs/featured_model/YOLOv3_ENHANCEMENT.md
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...@@ -44,5 +44,5 @@ python tools/train.py -c configs/dcn/yolov3_r50vd_dcn_iouloss_obj365_pretrained_ ...@@ -44,5 +44,5 @@ python tools/train.py -c configs/dcn/yolov3_r50vd_dcn_iouloss_obj365_pretrained_
| YOLOv3 DarkNet | [DarkNet pretrain](https://paddle-imagenet-models-name.bj.bcebos.com/DarkNet53_pretrained.tar) | 38.9 | 原生：88.3ms<br>tensorRT-FP32: 42.5ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | | YOLOv3 DarkNet | [DarkNet pretrain](https://paddle-imagenet-models-name.bj.bcebos.com/DarkNet53_pretrained.tar) | 38.9 | 原生：88.3ms<br>tensorRT-FP32: 42.5ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) |
| YOLOv3 ResNet50_vd DCN | [ImageNet pretrain](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_pretrained.tar) | 39.1 | 原生：74.4ms<br>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_imagenet.tar) | | YOLOv3 ResNet50_vd DCN | [ImageNet pretrain](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_pretrained.tar) | 39.1 | 原生：74.4ms<br>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_imagenet.tar) |
| YOLOv3 ResNet50_vd DCN | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 42.5 | 原生：74.4ms<br>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_v2.tar) | | YOLOv3 ResNet50_vd DCN | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 42.5 | 原生：74.4ms<br>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_v2.tar) |
| YOLOv3 ResNet50_vd DCN DropBlock | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 42.8 | 原生：74.4ms<br/>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_db_obj365.tar) | | YOLOv3 ResNet50_vd DCN DropBlock | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 42.8 | 原生：74.4ms<br/>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_dropblock.tar) |
| YOLOv3 ResNet50_vd DCN DropBlock IoULoss | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 43.2 | 原生：74.4ms<br/>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_db_obj365.tar) | | YOLOv3 ResNet50_vd DCN DropBlock IoULoss | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 43.2 | 原生：74.4ms<br/>tensorRT-FP32: 35.2ms | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_dropblock_iouloss.tar) |
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