From 8055e86ec738e6d416bfc6a18628c87674e313fd Mon Sep 17 00:00:00 2001 From: Kaipeng Deng Date: Fri, 12 Jun 2020 14:31:13 +0800 Subject: [PATCH] split weights and PaddleLite model in configs/mobile/README (#935) * split weights and PaddleLite model in configs/mobile/README --- configs/mobile/README.md | 22 +++++++++------------- configs/mobile/README_en.md | 22 +++++++++------------- 2 files changed, 18 insertions(+), 26 deletions(-) diff --git a/configs/mobile/README.md b/configs/mobile/README.md index d498b50f1..bc155b781 100755 --- a/configs/mobile/README.md +++ b/configs/mobile/README.md @@ -7,23 +7,19 @@ PaddleDetection目前提供一系列针对移动应用进行优化的模型，主要支持以下结构: -| 骨干网络 | 结构 | 输入大小 | 图片/gpu 1 | 学习率策略 | Box AP | 下载 2 | -|--------------------------|---------------------------|-------|------------------------|---------------|--------|-----------------------| -| MobileNetV3 Small | SSDLite | 320 | 64 | 400K (cosine) | 16.6 | [链接](https://paddlemodels.bj.bcebos.com/object_detection/ssdlite_mobilenet_v3_small.tar.gz) | -| MobileNetV3 Large | SSDLite | 320 | 64 | 400K (cosine) | 22.8 | [链接](https://paddlemodels.bj.bcebos.com/object_detection/ssdlite_mobilenet_v3_large.tar.gz) | -| MobileNetV3 Large w/ FPN | Cascade RCNN | 320 | 2 | 500k (cosine) | 25.0 | [链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_mobilenetv3_fpn_320.tar.gz) | -| MobileNetV3 Large w/ FPN | Cascade RCNN | 640 | 2 | 500k (cosine) | 30.2 | [链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_mobilenetv3_fpn_640.tar.gz) | -| MobileNetV3 Large | YOLOv3 | 320 | 8 | 500K | 27.1 | [链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.tar.gz) | -| MobileNetV3 Large | YOLOv3 Prune 3 | 320 | 8 | - | 24.6 | [链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3_prune86_FPGM_320.tar.gz) | +| 骨干网络 | 结构 | 输入大小 | 图片/gpu 1 | 学习率策略 | Box AP | 下载 | PaddleLite模型下载 | +| :----------------------- | :------------------------ | :---: | :--------------------: | :------------ | :----: | :--- | :----------------- | +| MobileNetV3 Small | SSDLite | 320 | 64 | 400K (cosine) | 16.6 | [链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_small.tar) | [链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/lite/ssdlite_mobilenet_v3_small.tar) | +| MobileNetV3 Large | SSDLite | 320 | 64 | 400K (cosine) | 22.8 | [链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_large.tar) | [链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/lite/ssdlite_mobilenet_v3_large.tar) | +| MobileNetV3 Large w/ FPN | Cascade RCNN | 320 | 2 | 500k (cosine) | 25.0 | [链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/cascade_rcnn_mobilenetv3_fpn_320.tar) | [链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/lite/cascade_rcnn_mobilenetv3_fpn_320.tar) | +| MobileNetV3 Large w/ FPN | Cascade RCNN | 640 | 2 | 500k (cosine) | 30.2 | [链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/cascade_rcnn_mobilenetv3_fpn_640.tar) | [链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/lite/cascade_rcnn_mobilenetv3_fpn_640.tar) | +| MobileNetV3 Large | YOLOv3 | 320 | 8 | 500K | 27.1 | [链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/lite/yolov3_mobilenet_v3.tar) | +| MobileNetV3 Large | YOLOv3 Prune 2 | 320 | 8 | - | 24.6 | [链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/yolov3_mobilenet_v3_prune75875_FPGM_distillby_r34.pdparams) | [链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/lite/yolov3_mobilenet_v3_prune86_FPGM_320.tar) | **注意**: - [1] 模型统一使用8卡训练. -- [2] 压缩包包括下列文件 - - 模型权重文件 (`.pdparams` or `.tar`) - - inference model 文件 (`__model__` and `__params__`) - - Paddle-Lite 模型文件 (`.nb`) -- [3] 参考下面关于YOLO剪裁的说明 +- [2] 参考下面关于YOLO剪裁的说明 ## 评测结果 diff --git a/configs/mobile/README_en.md b/configs/mobile/README_en.md index b2a6f9dd5..2d6d3a1b8 100755 --- a/configs/mobile/README_en.md +++ b/configs/mobile/README_en.md @@ -7,23 +7,19 @@ English | [简体中文](README.md) This directory contains models optimized for mobile applications, at present the following models included: -| Backbone | Architecture | Input | Image/gpu 1 | Lr schd | Box AP | Download 2 | -|--------------------------|---------------------------|-------|------------------------|---------------|--------|-----------------------| -| MobileNetV3 Small | SSDLite | 320 | 64 | 400K (cosine) | 16.6 | [Link](https://paddlemodels.bj.bcebos.com/object_detection/ssdlite_mobilenet_v3_small.tar.gz) | -| MobileNetV3 Large | SSDLite | 320 | 64 | 400K (cosine) | 22.8 | [Link](https://paddlemodels.bj.bcebos.com/object_detection/ssdlite_mobilenet_v3_large.tar.gz) | -| MobileNetV3 Large w/ FPN | Cascade RCNN | 320 | 2 | 500k (cosine) | 25.0 | [Link](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_mobilenetv3_fpn_320.tar.gz) | -| MobileNetV3 Large w/ FPN | Cascade RCNN | 640 | 2 | 500k (cosine) | 30.2 | [Link](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_mobilenetv3_fpn_640.tar.gz) | -| MobileNetV3 Large | YOLOv3 | 320 | 8 | 500K | 27.1 | [Link](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.tar.gz) | -| MobileNetV3 Large | YOLOv3 Prune 3 | 320 | 8 | - | 24.6 | [Link](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3_prune86_FPGM_320.tar.gz) | +| Backbone | Architecture | Input | Image/gpu 1 | Lr schd | Box AP | Download | PaddleLite Model Download | +| :----------------------- | :------------------------ | :---: | :--------------------: | :------------ | :----: | :------- | :------------------------ | +| MobileNetV3 Small | SSDLite | 320 | 64 | 400K (cosine) | 16.6 | [Link](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_small.tar) | [Link](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/lite/ssdlite_mobilenet_v3_small.tar) | +| MobileNetV3 Large | SSDLite | 320 | 64 | 400K (cosine) | 22.8 | [Link](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_large.tar) | [Link](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/lite/ssdlite_mobilenet_v3_large.tar) | +| MobileNetV3 Large w/ FPN | Cascade RCNN | 320 | 2 | 500k (cosine) | 25.0 | [Link](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/cascade_rcnn_mobilenetv3_fpn_320.tar) | [Link](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/lite/cascade_rcnn_mobilenetv3_fpn_320.tar) | +| MobileNetV3 Large w/ FPN | Cascade RCNN | 640 | 2 | 500k (cosine) | 30.2 | [Link](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/cascade_rcnn_mobilenetv3_fpn_640.tar) | [Link](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/lite/cascade_rcnn_mobilenetv3_fpn_640.tar) | +| MobileNetV3 Large | YOLOv3 | 320 | 8 | 500K | 27.1 | [Link](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [Link](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/lite/yolov3_mobilenet_v3.tar) | +| MobileNetV3 Large | YOLOv3 Prune 2 | 320 | 8 | - | 24.6 | [Link](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/yolov3_mobilenet_v3_prune75875_FPGM_distillby_r34.pdparams) | [Link](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/lite/yolov3_mobilenet_v3_prune86_FPGM_320.tar) | **Notes**: - [1] All models are trained on 8 GPUs. -- [2] Each tarball contains the following files - - model weight file (`.pdparams` or `.tar`) - - inference model files (`__model__` and `__params__`) - - Paddle-Lite model file (`.nb`) -- [3] See the note section on how YOLO head is pruned +- [2] See the note section on how YOLO head is pruned ## Benchmarks Results -- GitLab