add ppyolo_2x (#1155)

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.
 
 <div align="center">
   <img src="../../docs/images/ppyolo_map_fps.png" width=500 />
@@ -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:**
 

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。
 
 <div align="center">
   <img src="../../docs/images/ppyolo_map_fps.png" width=500 />
@@ -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:**
 

configs/ppyolo/ppyolo_2x.yml

+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'