PaddleDetection-release-2.5.zip

简体中文 | [English](README_en.md) # PP-PicoDet  ## 最新动态 - 发布PicoDet-NPU模型，支持模型全量化部署。详情请参考[PicoDet全量化示例](./FULL_QUANTIZATION.md) **（2022.08.10）** - 发布全新系列PP-PicoDet模型：**（2022.03.20）** - (1)引入TAL及ETA Head，优化PAN等结构，精度提升2个点以上； - (2)优化CPU端预测速度，同时训练速度提升一倍； - (3)导出模型将后处理包含在网络中，预测直接输出box结果，无需二次开发，迁移成本更低，端到端预测速度提升10%-20%。 ## 历史版本模型 - 详情请参考：[PicoDet 2021.10版本](./legacy_model/) ## 简介 PaddleDetection中提出了全新的轻量级系列模型`PP-PicoDet`，在移动端具有卓越的性能，成为全新SOTA轻量级模型。详细的技术细节可以参考我们的[arXiv技术报告](https://arxiv.org/abs/2111.00902)。 PP-PicoDet模型有如下特点： - 🌟 更高的mAP: 第一个在1M参数量之内`mAP(0.5:0.95)`超越**30+**(输入416像素时)。 - 🚀 更快的预测速度: 网络预测在ARM CPU下可达150FPS。 - 😊 部署友好: 支持PaddleLite/MNN/NCNN/OpenVINO等预测库，支持转出ONNX，提供了C++/Python/Android的demo。 - 😍 先进的算法: 我们在现有SOTA算法中进行了创新, 包括：ESNet, CSP-PAN, SimOTA等等。 <div align="center"> <img src="../../docs/images/picodet_map.png" width='600'/> </div> ## 基线 | 模型 | 输入尺寸 | mAP<sup>val<br>0.5:0.95 | mAP<sup>val<br>0.5 | 参数量<br><sup>(M) | FLOPS<br><sup>(G) | 预测时延<sup><small>[CPU](#latency)</small><sup><br><sup>(ms) | 预测时延<sup><small>[Lite](#latency)</small><sup><br><sup>(ms) | 权重下载 | 配置文件 | 导出模型 | | :-------- | :--------: | :---------------------: | :----------------: | :----------------: | :---------------: | :-----------------------------: | :-----------------------------: | :----------------------------------------: | :--------------------------------------- | :--------------------------------------- | | PicoDet-XS | 320*320 | 23.5 | 36.1 | 0.70 | 0.67 | 3.9ms | 7.81ms | [model](https://paddledet.bj.bcebos.com/models/picodet_xs_320_coco_lcnet.pdparams) &#124; [log](https://paddledet.bj.bcebos.com/logs/train_picodet_xs_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_xs_320_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_320_coco_lcnet.tar) &#124; [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_320_coco_lcnet_non_postprocess.tar) | | PicoDet-XS | 416*416 | 26.2 | 39.3 | 0.70 | 1.13 | 6.1ms | 12.38ms | [model](https://paddledet.bj.bcebos.com/models/picodet_xs_416_coco_lcnet.pdparams) &#124; [log](https://paddledet.bj.bcebos.com/logs/train_picodet_xs_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_xs_416_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_416_coco_lcnet.tar) &#124; [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_416_coco_lcnet_non_postprocess.tar) | | PicoDet-S | 320*320 | 29.1 | 43.4 | 1.18 | 0.97 | 4.8ms | 9.56ms | [model](https://paddledet.bj.bcebos.com/models/picodet_s_320_coco_lcnet.pdparams) &#124; [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_s_320_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_320_coco_lcnet.tar) &#124; [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_320_coco_lcnet_non_postprocess.tar) | | PicoDet-S | 416*416 | 32.5 | 47.6 | 1.18 | 1.65 | 6.6ms | 15.20ms | [model](https://paddledet.bj.bcebos.com/models/picodet_s_416_coco_lcnet.pdparams) &#124; [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_s_416_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_416_coco_lcnet.tar) &#124; [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_416_coco_lcnet_non_postprocess.tar) | | PicoDet-M | 320*320 | 34.4 | 50.0 | 3.46 | 2.57 | 8.2ms | 17.68ms | [model](https://paddledet.bj.bcebos.com/models/picodet_m_320_coco_lcnet.pdparams) &#124; [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_m_320_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_320_coco_lcnet.tar) &#124; [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_320_coco_lcnet_non_postprocess.tar) | | PicoDet-M | 416*416 | 37.5 | 53.4 | 3.46 | 4.34 | 12.7ms | 28.39ms | [model](https://paddledet.bj.bcebos.com/models/picodet_m_416_coco_lcnet.pdparams) &#124; [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_m_416_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_416_coco_lcnet.tar) &#124; [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_416_coco_lcnet_non_postprocess.tar) | | PicoDet-L | 320*320 | 36.1 | 52.0 | 5.80 | 4.20 | 11.5ms | 25.21ms | [model](https://paddledet.bj.bcebos.com/models/picodet_l_320_coco_lcnet.pdparams) &#124; [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_l_320_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_320_coco_lcnet.tar) &#124; [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_320_coco_lcnet_non_postprocess.tar) | | PicoDet-L | 416*416 | 39.4 | 55.7 | 5.80 | 7.10 | 20.7ms | 42.23ms | [model](https://paddledet.bj.bcebos.com/models/picodet_l_416_coco_lcnet.pdparams) &#124; [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_l_416_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_416_coco_lcnet.tar) &#124; [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_416_coco_lcnet_non_postprocess.tar) | | PicoDet-L | 640*640 | 42.6 | 59.2 | 5.80 | 16.81 | 62.5ms | 108.1ms | [model](https://paddledet.bj.bcebos.com/models/picodet_l_640_coco_lcnet.pdparams) &#124; [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_640_coco_lcnet.log) | [config](https