From 2ac2a4a843b527422921350b0ae41581c16e11dc Mon Sep 17 00:00:00 2001 From: Kaipeng Deng Date: Tue, 4 Aug 2020 19:00:08 +0800 Subject: [PATCH] add ppyolo_2x (#1156) --- configs/ppyolo/README.md | 6 ++- configs/ppyolo/README_cn.md | 6 ++- configs/ppyolo/ppyolo_2x.yml | 92 ++++++++++++++++++++++++++++++++++++ 3 files changed, 102 insertions(+), 2 deletions(-) create mode 100644 configs/ppyolo/ppyolo_2x.yml diff --git a/configs/ppyolo/README.md b/configs/ppyolo/README.md index 61afc5e6b..4f481ba07 100644 --- a/configs/ppyolo/README.md +++ b/configs/ppyolo/README.md @@ -13,7 +13,7 @@ English | [简体中文](README_cn.md) [PP-YOLO](https://arxiv.org/abs/2007.12099) is a optimized model based on YOLOv3 in PaddleDetection，whose performance(mAP on COCO) and inference spped are better than [YOLOv4](https://arxiv.org/abs/2004.10934)，PaddlePaddle 1.8.4(will release in mid-August 202) or [Daily Version](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/Tables.html#whl-dev) is required to run this PP-YOLO。 -PP-YOLO reached mmAP(IoU=0.5:0.95) as 45.2% on COCO test-dev2017 dataset, and inference speed of FP32 on single V100 is 72.9 FPS, inference speed of FP16 with TensorRT on single V100 is 155.6 FPS. +PP-YOLO reached mmAP(IoU=0.5:0.95) as 45.9% on COCO test-dev2017 dataset, and inference speed of FP32 on single V100 is 72.9 FPS, inference speed of FP16 with TensorRT on single V100 is 155.6 FPS.
@@ -46,6 +46,10 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods: | PP-YOLO | 8 | 24 | ResNet50vd | 512 | 44.4 | 89.9 | 188.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ppyolo/ppyolo.yml) | | PP-YOLO | 8 | 24 | ResNet50vd | 416 | 42.5 | 109.1 | 215.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ppyolo/ppyolo.yml) | | PP-YOLO | 8 | 24 | ResNet50vd | 320 | 39.3 | 132.2 | 242.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ppyolo/ppyolo.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 608 | 45.9 | 72.9 | 155.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ppyolo/ppyolo_2x.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 512 | 45.0 | 89.9 | 188.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ppyolo/ppyolo_2x.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 416 | 43.2 | 109.1 | 215.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ppyolo/ppyolo_2x.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 320 | 40.1 | 132.2 | 242.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ppyolo/ppyolo_2x.yml) | **Notes:** diff --git a/configs/ppyolo/README_cn.md b/configs/ppyolo/README_cn.md index c05900521..2d3deceb2 100644 --- a/configs/ppyolo/README_cn.md +++ b/configs/ppyolo/README_cn.md @@ -13,7 +13,7 @@ [PP-YOLO](https://arxiv.org/abs/2007.12099)是PaddleDetection优化和改进的YOLOv3的模型，其精度(COCO数据集mAP)和推理速度均优于[YOLOv4](https://arxiv.org/abs/2004.10934)模型，要求使用PaddlePaddle 1.8.4(2020年8月中旬发布)或适当的[develop版本](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/Tables.html#whl-dev)。 -PP-YOLO在[COCO](http://cocodataset.org) test-dev2017数据集上精度达到45.2%，在单卡V100上FP32推理速度为72.9 FPS, V100上开启TensorRT下FP16推理速度为155.6 FPS。 +PP-YOLO在[COCO](http://cocodataset.org) test-dev2017数据集上精度达到45.9%，在单卡V100上FP32推理速度为72.9 FPS, V100上开启TensorRT下FP16推理速度为155.6 FPS。
@@ -46,6 +46,10 @@ PP-YOLO从如下方面优化和提升YOLOv3模型的精度和速度： | PP-YOLO | 8 | 24 | ResNet50vd | 512 | 44.4 | 89.9 | 188.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ppyolo/ppyolo.yml) | | PP-YOLO | 8 | 24 | ResNet50vd | 416 | 42.5 | 109.1 | 215.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ppyolo/ppyolo.yml) | | PP-YOLO | 8 | 24 | ResNet50vd | 320 | 39.3 | 132.2 | 242.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ppyolo/ppyolo.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 608 | 45.9 | 72.9 | 155.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ppyolo/ppyolo.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 512 | 45.0 | 89.9 | 188.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ppyolo/ppyolo.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 416 | 43.2 | 109.1 | 215.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ppyolo/ppyolo.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 320 | 40.1 | 132.2 | 242.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ppyolo/ppyolo.yml) | **注意:** diff --git a/configs/ppyolo/ppyolo_2x.yml b/configs/ppyolo/ppyolo_2x.yml new file mode 100644 index 000000000..8c2493372 --- /dev/null +++ b/configs/ppyolo/ppyolo_2x.yml @@ -0,0 +1,92 @@ +architecture: YOLOv3 +use_gpu: true +max_iters: 500000 +log_smooth_window: 100 +log_iter: 100 +save_dir: output +snapshot_iter: 10000 +metric: COCO +pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_ssld_pretrained.tar +weights: output/ppyolo/model_final +num_classes: 80 +use_fine_grained_loss: true +use_ema: true +ema_decay: 0.9998 + +YOLOv3: + backbone: ResNet + yolo_head: YOLOv3Head + use_fine_grained_loss: true + +ResNet: + norm_type: sync_bn + freeze_at: 0 + freeze_norm: false + norm_decay: 0. + depth: 50 + feature_maps: [3, 4, 5] + variant: d + dcn_v2_stages: [5] + +YOLOv3Head: + anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]] + anchors: [[10, 13], [16, 30], [33, 23], + [30, 61], [62, 45], [59, 119], + [116, 90], [156, 198], [373, 326]] + norm_decay: 0. + coord_conv: true + iou_aware: true + iou_aware_factor: 0.4 + scale_x_y: 1.05 + spp: true + yolo_loss: YOLOv3Loss + nms: MatrixNMS + drop_block: true + +YOLOv3Loss: + batch_size: 24 + ignore_thresh: 0.7 + scale_x_y: 1.05 + label_smooth: false + use_fine_grained_loss: true + iou_loss: IouLoss + iou_aware_loss: IouAwareLoss + +IouLoss: + loss_weight: 2.5 + max_height: 608 + max_width: 608 + +IouAwareLoss: + loss_weight: 1.0 + max_height: 608 + max_width: 608 + +MatrixNMS: + background_label: -1 + keep_top_k: 100 + normalized: false + score_threshold: 0.01 + post_threshold: 0.01 + +LearningRate: + base_lr: 0.01 + schedulers: + - !PiecewiseDecay + gamma: 0.1 + milestones: + - 400000 + - 450000 + - !LinearWarmup + start_factor: 0. + steps: 4000 + +OptimizerBuilder: + optimizer: + momentum: 0.9 + type: Momentum + regularizer: + factor: 0.0005 + type: L2 + +_READER_: 'ppyolo_reader.yml' -- GitLab