forked from PulseFocusPlatform/PulseFocusPlatform
88 lines
2.9 KiB
Markdown
88 lines
2.9 KiB
Markdown
# 模型库和基线
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## 测试环境
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- Python 3.7
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- PaddlePaddle 每日版本
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- CUDA 10.1
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- cuDNN 7.5
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- NCCL 2.4.8
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## 通用设置
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- 所有模型均在COCO17数据集中训练和测试。
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- 除非特殊说明，所有ResNet骨干网络采用[ResNet-B](https://arxiv.org/pdf/1812.01187)结构。
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- **推理时间(fps)**: 推理时间是在一张Tesla V100的GPU上通过'tools/eval.py'测试所有验证集得到，单位是fps(图片数/秒), cuDNN版本是7.5，包括数据加载、网络前向执行和后处理, batch size是1。
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## 训练策略
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- 我们采用和[Detectron](https://github.com/facebookresearch/Detectron/blob/master/MODEL_ZOO.md#training-schedules)相同的训练策略。
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- 1x 策略表示：在总batch size为8时，初始学习率为0.01，在8 epoch和11 epoch后学习率分别下降10倍，最终训练12 epoch。
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- 2x 策略为1x策略的两倍，同时学习率调整位置也为1x的两倍。
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## ImageNet预训练模型
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Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型均通过标准的Imagenet-1k数据集训练得到，ResNet和MobileNet等是采用余弦学习率调整策略或SSLD知识蒸馏训练得到的高精度预训练模型，可在[PaddleClas](https://github.com/PaddlePaddle/PaddleClas)查看模型细节。
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## 基线
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### Faster R-CNN
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请参考[Faster R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/configs/faster_rcnn/)
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### Mask R-CNN
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请参考[Mask R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/configs/mask_rcnn/)
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### Cascade R-CNN
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请参考[Cascade R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/configs/cascade_rcnn)
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### YOLOv3
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请参考[YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/configs/yolov3/)
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### SSD
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请参考[SSD](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/configs/ssd/)
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### FCOS
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请参考[FCOS](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/configs/fcos/)
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### SOLOv2
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请参考[SOLOv2](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/configs/solov2/)
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### PP-YOLO
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请参考[PP-YOLO](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/configs/ppyolo/)
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### TTFNet
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请参考[TTFNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/configs/ttfnet/)
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### Group Normalization
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请参考[Group Normalization](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/configs/gn/)
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### Deformable ConvNets v2
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请参考[Deformable ConvNets v2](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/configs/dcn/)
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### HRNets
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请参考[HRNets](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/configs/hrnet/)
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### Res2Net
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请参考[Res2Net](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/configs/res2net/)
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## 旋转框检测
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### S2ANet
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请参考[S2ANet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/configs/dota/)
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