From 18cc23ddf9ede6bd5f4fa0e407f636f59493f140 Mon Sep 17 00:00:00 2001 From: Feng Ni Date: Thu, 3 Mar 2022 16:10:42 +0800 Subject: [PATCH] [doc] fix doc deadlinks (#5272) * fix doc dead links * remove test_tipc --- configs/centernet/README.md | 9 ++++- configs/centernet/README_cn.md | 9 +++-- .../centernet/centernet_mbv1_140e_coco.yml | 21 ++++++++++ .../centernet_mbv3_large_140e_coco.yml | 22 +++++++++++ .../centernet_mbv3_small_140e_coco.yml | 28 +++++++++++++ .../centernet_shufflenetv2_140e_coco.yml | 33 ++++++++++++++++ configs/faster_rcnn/README.md | 39 ++++++++++--------- configs/ppyolo/README.md | 4 +- configs/ppyolo/README_cn.md | 4 +- 9 files changed, 141 insertions(+), 28 deletions(-) create mode 100644 configs/centernet/centernet_mbv1_140e_coco.yml create mode 100644 configs/centernet/centernet_mbv3_large_140e_coco.yml create mode 100644 configs/centernet/centernet_mbv3_small_140e_coco.yml create mode 100644 configs/centernet/centernet_shufflenetv2_140e_coco.yml diff --git a/configs/centernet/README.md b/configs/centernet/README.md index ab06d00ce..6dd52cd32 100644 --- a/configs/centernet/README.md +++ b/configs/centernet/README.md @@ -18,8 +18,13 @@ English | [简体中文](README_cn.md) | backbone | input shape | mAP | FPS | download | config | | :--------------| :------- | :----: | :------: | :----: |:-----: | | DLA-34(paper) | 512x512 | 37.4 | - | - | - | -| DLA-34 | 512x512 | 37.6 | - | [model](https://bj.bcebos.com/v1/paddledet/models/centernet_dla34_140e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/centernet/centernet_dla34_140e_coco.yml) | -| ResNet50 + DLAUp | 512x512 | 38.9 | - | [model](https://bj.bcebos.com/v1/paddledet/models/centernet_r50_140e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/centernet/centernet_r50_140e_coco.yml) | +| DLA-34 | 512x512 | 37.6 | - | [model](https://bj.bcebos.com/v1/paddledet/models/centernet_dla34_140e_coco.pdparams) | [config](./centernet_dla34_140e_coco.yml) | +| ResNet50 + DLAUp | 512x512 | 38.9 | - | [model](https://bj.bcebos.com/v1/paddledet/models/centernet_r50_140e_coco.pdparams) | [config](./centernet_r50_140e_coco.yml) | +| MobileNetV1 + DLAUp | 512x512 | 28.2 | - | [model](https://bj.bcebos.com/v1/paddledet/models/centernet_mbv1_140e_coco.pdparams) | [config](./centernet_mbv1_140e_coco.yml) | +| MobileNetV3_small + DLAUp | 512x512 | 17 | - | [model](https://bj.bcebos.com/v1/paddledet/models/centernet_mbv3_small_140e_coco.pdparams) | [config](./centernet_mbv3_small_140e_coco.yml) | +| MobileNetV3_large + DLAUp | 512x512 | 27.1 | - | [model](https://bj.bcebos.com/v1/paddledet/models/centernet_mbv3_large_140e_coco.pdparams) | [config](./centernet_mbv3_large_140e_coco.yml) | +| ShuffleNetV2 + DLAUp | 512x512 | 23.8 | - | [model](https://bj.bcebos.com/v1/paddledet/models/centernet_shufflenetv2_140e_coco.pdparams) | [config](./centernet_shufflenetv2_140e_coco.yml) | + ## Citations ``` diff --git a/configs/centernet/README_cn.md b/configs/centernet/README_cn.md index b03097a72..d78cd40e3 100644 --- a/configs/centernet/README_cn.md +++ b/configs/centernet/README_cn.md @@ -18,9 +18,12 @@ | 骨干网络 | 输入尺寸 | mAP | FPS | 下载链接 | 配置文件 | | :--------------| :------- | :----: | :------: | :----: |:-----: | | DLA-34(paper) | 512x512 | 37.4 | - | - | - | -| DLA-34 | 512x512 | 37.6 | - | [下载链接](https://bj.bcebos.com/v1/paddledet/models/centernet_dla34_140e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/centernet/centernet_dla34_140e_coco.yml) | -| ResNet50 + DLAUp | 512x512 | 38.9 | - | [下载链接](https://bj.bcebos.com/v1/paddledet/models/centernet_r50_140e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/centernet/centernet_r50_140e_coco.yml) | - +| DLA-34 | 512x512 | 37.6 | - | [下载链接](https://bj.bcebos.com/v1/paddledet/models/centernet_dla34_140e_coco.pdparams) | [配置文件](./centernet_dla34_140e_coco.yml) | +| ResNet50 + DLAUp | 512x512 | 38.9 | - | [下载链接](https://bj.bcebos.com/v1/paddledet/models/centernet_r50_140e_coco.pdparams) | [配置文件](./centernet_r50_140e_coco.yml) | +| MobileNetV1 + DLAUp | 512x512 | 28.2 | - | [下载链接](https://bj.bcebos.com/v1/paddledet/models/centernet_mbv1_140e_coco.pdparams) | [配置文件](./centernet_mbv1_140e_coco.yml) | +| MobileNetV3_small + DLAUp | 512x512 | 17 | - | [下载链接](https://bj.bcebos.com/v1/paddledet/models/centernet_mbv3_small_140e_coco.pdparams) | [配置文件](./centernet_mbv3_small_140e_coco.yml) | +| MobileNetV3_large + DLAUp | 512x512 | 27.1 | - | [下载链接](https://bj.bcebos.com/v1/paddledet/models/centernet_mbv3_large_140e_coco.pdparams) | [配置文件](./centernet_mbv3_large_140e_coco.yml) | +| ShuffleNetV2 + DLAUp | 512x512 | 23.8 | - | [下载链接](https://bj.bcebos.com/v1/paddledet/models/centernet_shufflenetv2_140e_coco.pdparams) | [配置文件](./centernet_shufflenetv2_140e_coco.yml) | ## 引用 ``` diff --git a/configs/centernet/centernet_mbv1_140e_coco.yml b/configs/centernet/centernet_mbv1_140e_coco.yml new file mode 100644 index 000000000..48429a1dd --- /dev/null +++ b/configs/centernet/centernet_mbv1_140e_coco.yml @@ -0,0 +1,21 @@ +_BASE_: [ + 'centernet_r50_140e_coco.yml' +] + +pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV1_pretrained.pdparams +weights: output/centernet_mbv1_140e_coco/model_final + +CenterNet: + backbone: MobileNet + neck: CenterNetDLAFPN + head: CenterNetHead + post_process: CenterNetPostProcess + +MobileNet: + scale: 1. + with_extra_blocks: false + extra_block_filters: [] + feature_maps: [3, 5, 11, 13] + +TrainReader: + batch_size: 32 diff --git a/configs/centernet/centernet_mbv3_large_140e_coco.yml b/configs/centernet/centernet_mbv3_large_140e_coco.yml new file mode 100644 index 000000000..57830a9b5 --- /dev/null +++ b/configs/centernet/centernet_mbv3_large_140e_coco.yml @@ -0,0 +1,22 @@ +_BASE_: [ + 'centernet_r50_140e_coco.yml' +] + +pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_large_x1_0_ssld_pretrained.pdparams +weights: output/centernet_mbv3_large_140e_coco/model_final + +CenterNet: + backbone: MobileNetV3 + neck: CenterNetDLAFPN + head: CenterNetHead + post_process: CenterNetPostProcess + +MobileNetV3: + model_name: large + scale: 1. + with_extra_blocks: false + extra_block_filters: [] + feature_maps: [4, 7, 13, 16] + +TrainReader: + batch_size: 32 diff --git a/configs/centernet/centernet_mbv3_small_140e_coco.yml b/configs/centernet/centernet_mbv3_small_140e_coco.yml new file mode 100644 index 000000000..de73f1b2f --- /dev/null +++ b/configs/centernet/centernet_mbv3_small_140e_coco.yml @@ -0,0 +1,28 @@ +_BASE_: [ + 'centernet_r50_140e_coco.yml' +] + +pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_small_x1_0_ssld_pretrained.pdparams +weights: output/centernet_mbv3_small_140e_coco/model_final + +CenterNet: + backbone: MobileNetV3 + neck: CenterNetDLAFPN + head: CenterNetHead + post_process: CenterNetPostProcess + +MobileNetV3: + model_name: small + scale: 1. + with_extra_blocks: false + extra_block_filters: [] + feature_maps: [4, 9, 12] + +CenterNetDLAFPN: + first_level: 0 + last_level: 3 + down_ratio: 8 + dcn_v2: False + +TrainReader: + batch_size: 32 diff --git a/configs/centernet/centernet_shufflenetv2_140e_coco.yml b/configs/centernet/centernet_shufflenetv2_140e_coco.yml new file mode 100644 index 000000000..9ccdae164 --- /dev/null +++ b/configs/centernet/centernet_shufflenetv2_140e_coco.yml @@ -0,0 +1,33 @@ +_BASE_: [ + 'centernet_r50_140e_coco.yml' +] + +pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ShuffleNetV2_x1_0_pretrained.pdparams +weights: output/centernet_shufflenetv2_140e_coco/model_final + +CenterNet: + backbone: ShuffleNetV2 + neck: CenterNetDLAFPN + head: CenterNetHead + post_process: CenterNetPostProcess + +ShuffleNetV2: + scale: 1.0 + feature_maps: [5, 13, 17] + act: leaky_relu + +CenterNetDLAFPN: + first_level: 0 + last_level: 3 + down_ratio: 8 + dcn_v2: False + +TrainReader: + batch_size: 32 + +TestReader: + sample_transforms: + - Decode: {} + - WarpAffine: {keep_res: False, input_h: 512, input_w: 512} + - NormalizeImage: {mean: [0.40789655, 0.44719303, 0.47026116], std: [0.2886383 , 0.27408165, 0.27809834]} + - Permute: {} diff --git a/configs/faster_rcnn/README.md b/configs/faster_rcnn/README.md index f22bdc495..da495599c 100644 --- a/configs/faster_rcnn/README.md +++ b/configs/faster_rcnn/README.md @@ -4,25 +4,26 @@ | 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 | | :------------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: | -| ResNet50 | Faster | 1 | 1x | ---- | 36.7 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_r50_1x_coco.yml) | -| ResNet50-vd | Faster | 1 | 1x | ---- | 37.6 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_r50_vd_1x_coco.yml) | -| ResNet101 | Faster | 1 | 1x | ---- | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_r101_1x_coco.yml) | -| ResNet34-FPN | Faster | 1 | 1x | ---- | 37.8 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_r34_fpn_1x_coco.yml) | -| ResNet34-vd-FPN | Faster | 1 | 1x | ---- | 38.5 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_r34_vd_fpn_1x_coco.yml) | -| ResNet50-FPN | Faster | 1 | 1x | ---- | 38.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.yml) | -| ResNet50-FPN | Faster | 1 | 2x | ---- | 40.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_r50_fpn_2x_coco.yml) | -| ResNet50-vd-FPN | Faster | 1 | 1x | ---- | 39.5 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_1x_coco.yml) | -| ResNet50-vd-FPN | Faster | 1 | 2x | ---- | 40.8 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_2x_coco.yml) | -| ResNet101-FPN | Faster | 1 | 2x | ---- | 41.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_r101_fpn_2x_coco.yml) | -| ResNet101-vd-FPN | Faster | 1 | 1x | ---- | 42.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_r101_vd_fpn_1x_coco.yml) | -| ResNet101-vd-FPN | Faster | 1 | 2x | ---- | 43.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_r101_vd_fpn_2x_coco.yml) | -| ResNeXt101-vd-FPN | Faster | 1 | 1x | ---- | 43.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_x101_vd_64x4d_fpn_1x_coco.yml) | -| ResNeXt101-vd-FPN | Faster | 1 | 2x | ---- | 44.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_x101_vd_64x4d_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_x101_vd_64x4d_fpn_2x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 1x | ---- | 41.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 2x | ---- | 42.3 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_ssld_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_r50_vd_ssld_fpn_2x_coco.yml) | -| Swin-Tiny-FPN | Faster | 2 | 1x | ---- | 42.6 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_swin_tiny_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_swin_tiny_1x_coco.yml) | -| Swin-Tiny-FPN | Faster | 2 | 2x | ---- | 44.8 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_swin_tiny_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_swin_tiny_2x_coco.yml) | -| Swin-Tiny-FPN | Faster | 2 | 3x | ---- | 45.3 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_swin_tiny_fpn_3x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/faster_rcnn/faster_rcnn_swin_tiny_3x_coco.yml) | +| ResNet50 | Faster | 1 | 1x | ---- | 36.7 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_1x_coco.pdparams) | [配置文件](./faster_rcnn_r50_1x_coco.yml) | +| ResNet50-vd | Faster | 1 | 1x | ---- | 37.6 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_1x_coco.pdparams) | [配置文件](./faster_rcnn_r50_vd_1x_coco.yml) | +| ResNet101 | Faster | 1 | 1x | ---- | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_1x_coco.pdparams) | [配置文件](./faster_rcnn_r101_1x_coco.yml) | +| ResNet34-FPN | Faster | 1 | 1x | ---- | 37.8 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_fpn_1x_coco.pdparams) | [配置文件](./faster_rcnn_r34_fpn_1x_coco.yml) | +| ResNet34-FPN-MultiScaleTest | Faster | 1 | 1x | ---- | 38.2 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_fpn_multiscaletest_1x_coco.pdparams) | [配置文件](./faster_rcnn_r34_fpn_multiscaletest_1x_coco.yml) | +| ResNet34-vd-FPN | Faster | 1 | 1x | ---- | 38.5 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_vd_fpn_1x_coco.pdparams) | [配置文件](./faster_rcnn_r34_vd_fpn_1x_coco.yml) | +| ResNet50-FPN | Faster | 1 | 1x | ---- | 38.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](./faster_rcnn_r50_fpn_1x_coco.yml) | +| ResNet50-FPN | Faster | 1 | 2x | ---- | 40.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_fpn_2x_coco.pdparams) | [配置文件](./faster_rcnn_r50_fpn_2x_coco.yml) | +| ResNet50-vd-FPN | Faster | 1 | 1x | ---- | 39.5 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_1x_coco.pdparams) | [配置文件](./faster_rcnn_r50_vd_fpn_1x_coco.yml) | +| ResNet50-vd-FPN | Faster | 1 | 2x | ---- | 40.8 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](./faster_rcnn_r50_vd_fpn_2x_coco.yml) | +| ResNet101-FPN | Faster | 1 | 2x | ---- | 41.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_fpn_2x_coco.pdparams) | [配置文件](./faster_rcnn_r101_fpn_2x_coco.yml) | +| ResNet101-vd-FPN | Faster | 1 | 1x | ---- | 42.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](./faster_rcnn_r101_vd_fpn_1x_coco.yml) | +| ResNet101-vd-FPN | Faster | 1 | 2x | ---- | 43.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_vd_fpn_2x_coco.pdparams) | [配置文件](./faster_rcnn_r101_vd_fpn_2x_coco.yml) | +| ResNeXt101-vd-FPN | Faster | 1 | 1x | ---- | 43.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](./faster_rcnn_x101_vd_64x4d_fpn_1x_coco.yml) | +| ResNeXt101-vd-FPN | Faster | 1 | 2x | ---- | 44.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_x101_vd_64x4d_fpn_2x_coco.pdparams) | [配置文件](./faster_rcnn_x101_vd_64x4d_fpn_2x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 1x | ---- | 41.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](./faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 2x | ---- | 42.3 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](./faster_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | +| Swin-Tiny-FPN | Faster | 2 | 1x | ---- | 42.6 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_swin_tiny_fpn_1x_coco.pdparams) | [配置文件](./faster_rcnn_swin_tiny_fpn_1x_coco.yml) | +| Swin-Tiny-FPN | Faster | 2 | 2x | ---- | 44.8 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_swin_tiny_fpn_2x_coco.pdparams) | [配置文件](./faster_rcnn_swin_tiny_fpn_2x_coco.yml) | +| Swin-Tiny-FPN | Faster | 2 | 3x | ---- | 45.3 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_swin_tiny_fpn_3x_coco.pdparams) | [配置文件](./faster_rcnn_swin_tiny_fpn_3x_coco.yml) | ## Citations ``` diff --git a/configs/ppyolo/README.md b/configs/ppyolo/README.md index 7a5fa1d6e..53cc2f31a 100644 --- a/configs/ppyolo/README.md +++ b/configs/ppyolo/README.md @@ -59,7 +59,7 @@ PP-YOLO and PP-YOLOv2 improved performance and speed of YOLOv3 with following me **Notes:** - PP-YOLO is trained on COCO train2017 dataset and evaluated on val2017 & test-dev2017 dataset，Box APtest is evaluation results of `mAP(IoU=0.5:0.95)`. -- PP-YOLO used 8 GPUs for training and mini-batch size as 24 on each GPU, if GPU number and mini-batch size is changed, learning rate and iteration times should be adjusted according [FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.3/docs/tutorials/FAQ.md). +- PP-YOLO used 8 GPUs for training and mini-batch size as 24 on each GPU, if GPU number and mini-batch size is changed, learning rate and iteration times should be adjusted according [FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.3/docs/tutorials/FAQ). - PP-YOLO inference speed is tesed on single Tesla V100 with batch size as 1, CUDA 10.2, CUDNN 7.5.1, TensorRT 5.1.2.2 in TensorRT mode. - PP-YOLO FP32 inference speed testing uses inference model exported by `tools/export_model.py` and benchmarked by running `depoly/python/infer.py` with `--run_benchmark`. All testing results do not contains the time cost of data reading and post-processing(NMS), which is same as [YOLOv4(AlexyAB)](https://github.com/AlexeyAB/darknet) in testing method. - TensorRT FP16 inference speed testing exclude the time cost of bounding-box decoding(`yolo_box`) part comparing with FP32 testing above, which means that data reading, bounding-box decoding and post-processing(NMS) is excluded(test method same as [YOLOv4(AlexyAB)](https://github.com/AlexeyAB/darknet) too) @@ -75,7 +75,7 @@ PP-YOLO and PP-YOLOv2 improved performance and speed of YOLOv3 with following me **Notes:** - PP-YOLO_MobileNetV3 is trained on COCO train2017 datast and evaluated on val2017 dataset，Box APval is evaluation results of `mAP(IoU=0.5:0.95)`, Box APval is evaluation results of `mAP(IoU=0.5)`. -- PP-YOLO_MobileNetV3 used 4 GPUs for training and mini-batch size as 32 on each GPU, if GPU number and mini-batch size is changed, learning rate and iteration times should be adjusted according [FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.3/docs/tutorials/FAQ.md). +- PP-YOLO_MobileNetV3 used 4 GPUs for training and mini-batch size as 32 on each GPU, if GPU number and mini-batch size is changed, learning rate and iteration times should be adjusted according [FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.3/docs/tutorials/FAQ). - PP-YOLO_MobileNetV3 inference speed is tested on Kirin 990 with 1 thread. ### PP-YOLO tiny diff --git a/configs/ppyolo/README_cn.md b/configs/ppyolo/README_cn.md index 88068eaba..990a429b3 100644 --- a/configs/ppyolo/README_cn.md +++ b/configs/ppyolo/README_cn.md @@ -58,7 +58,7 @@ PP-YOLO和PP-YOLOv2从如下方面优化和提升YOLOv3模型的精度和速度 **注意:** - PP-YOLO模型使用COCO数据集中train2017作为训练集，使用val2017和test-dev2017作为测试集，Box APtest为`mAP(IoU=0.5:0.95)`评估结果。 -- PP-YOLO模型训练过程中使用8 GPUs，每GPU batch size为24进行训练，如训练GPU数和batch size不使用上述配置，须参考[FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.3/docs/tutorials/FAQ.md)调整学习率和迭代次数。 +- PP-YOLO模型训练过程中使用8 GPUs，每GPU batch size为24进行训练，如训练GPU数和batch size不使用上述配置，须参考[FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.3/docs/tutorials/FAQ)调整学习率和迭代次数。 - PP-YOLO模型推理速度测试采用单卡V100，batch size=1进行测试，使用CUDA 10.2, CUDNN 7.5.1，TensorRT推理速度测试使用TensorRT 5.1.2.2。 - PP-YOLO模型FP32的推理速度测试数据为使用`tools/export_model.py`脚本导出模型后，使用`deploy/python/infer.py`脚本中的`--run_benchnark`参数使用Paddle预测库进行推理速度benchmark测试结果, 且测试的均为不包含数据预处理和模型输出后处理(NMS)的数据(与[YOLOv4(AlexyAB)](https://github.com/AlexeyAB/darknet)测试方法一致)。 - TensorRT FP16的速度测试相比于FP32去除了`yolo_box`(bbox解码)部分耗时，即不包含数据预处理，bbox解码和NMS(与[YOLOv4(AlexyAB)](https://github.com/AlexeyAB/darknet)测试方法一致)。 @@ -71,7 +71,7 @@ PP-YOLO和PP-YOLOv2从如下方面优化和提升YOLOv3模型的精度和速度 | PP-YOLO_MobileNetV3_small | 4 | 32 | 16MB | 320 | 17.2 | 33.8 | 21.5 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_small_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/ppyolo/ppyolo_mbv3_small_coco.yml) | - PP-YOLO_MobileNetV3 模型使用COCO数据集中train2017作为训练集，使用val2017作为测试集，Box APval为`mAP(IoU=0.5:0.95)`评估结果, Box AP50val为`mAP(IoU=0.5)`评估结果。 -- PP-YOLO_MobileNetV3 模型训练过程中使用4GPU，每GPU batch size为32进行训练，如训练GPU数和batch size不使用上述配置，须参考[FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.3/docs/tutorials/FAQ.md)调整学习率和迭代次数。 +- PP-YOLO_MobileNetV3 模型训练过程中使用4GPU，每GPU batch size为32进行训练，如训练GPU数和batch size不使用上述配置，须参考[FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.3/docs/tutorials/FAQ)调整学习率和迭代次数。 - PP-YOLO_MobileNetV3 模型推理速度测试环境配置为麒麟990芯片单线程。 ### PP-YOLO tiny模型 -- GitLab