add focalnet ppyoloe+ model (#7923)

configs/convnext/ppyoloe_convnext_tiny_36e_coco.yml

@@ -29,7 +29,7 @@ ConvNeXt:
 PPYOLOEHead:
   static_assigner_epoch: 12
   nms:
-    nms_top_k: 10000
+    nms_top_k: 1000
     keep_top_k: 300
     score_threshold: 0.01
     nms_threshold: 0.7

configs/focalnet/README.md

+# FocalNet (Focal Modulation Networks)
+
+## 模型库
+### FocalNet on COCO
+
+| 网络网络    | 输入尺寸| 图片数/GPU | 学习率策略 | mAP<sup>val<br>0.5:0.95 | mAP<sup>val<br>0.5 |  下载链接  | 配置文件 |
+| :--------- | :---- | :-------: | :------: | :---------------------: | :----------------: | :-------: |:------: |
+| PP-YOLOE+ FocalNet-tiny | 640 |    8      |   36e    |  -  |  46.6 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_focalnet_tiny_36e_coco.pdparams) | [配置文件](./ppyoloe_plus_focalnet_tiny_36e_coco.yml) |
+
+
+## Citations
+```
+@misc{yang2022focal,
+      title={Focal Modulation Networks},
+      author={Jianwei Yang and Chunyuan Li and Xiyang Dai and Jianfeng Gao},
+      journal={Advances in Neural Information Processing Systems (NeurIPS)},
+      year={2022}
+}
+```

configs/focalnet/ppyoloe_plus_focalnet_tiny_36e_coco.yml

+_BASE_: [
+  '../datasets/coco_detection.yml',
+  '../runtime.yml',
+  '../ppyoloe/_base_/ppyoloe_plus_crn.yml',
+  '../ppyoloe/_base_/ppyoloe_plus_reader.yml',
+]
+depth_mult: 0.33 # s version
+width_mult: 0.50
+
+log_iter: 100
+snapshot_epoch: 4
+weights: output/ppyoloe_plus_focalnet_tiny_36e_coco/model_final
+pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/pretrained/focalnet_tiny_lrf_pretrained.pdparams
+
+
+architecture: PPYOLOE
+norm_type: sync_bn
+use_ema: true
+ema_decay: 0.9998
+ema_black_list: ['proj_conv.weight']
+custom_black_list: ['reduce_mean']
+
+PPYOLOE:
+  backbone: FocalNet
+  neck: CustomCSPPAN
+  yolo_head: PPYOLOEHead
+  post_process: ~
+
+FocalNet:
+  arch: 'focalnet_T_224_1k_lrf'
+  out_indices: [1, 2, 3]
+
+PPYOLOEHead:
+  static_assigner_epoch: 12
+  nms:
+    nms_top_k: 1000
+    keep_top_k: 300
+    score_threshold: 0.01
+    nms_threshold: 0.7
+
+
+TrainReader:
+  batch_size: 8
+
+
+epoch: 36
+LearningRate:
+  base_lr: 0.0001
+  schedulers:
+  - !PiecewiseDecay
+    gamma: 0.1
+    milestones: [36]
+  - !LinearWarmup
+    start_factor: 0.1
+    steps: 1000
+
+OptimizerBuilder:
+  regularizer: false
+  optimizer:
+    type: AdamW
+    weight_decay: 0.0005

configs/swin/README.md

@@ -5,7 +5,7 @@
 | 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 |
 | :------------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: |
 | swin_T_224 | Faster R-CNN    |    2    |   36e    |     ----     |  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) |
-| swin_T_224 | PP-YOLOE+       |    8    |   36e    |     ----     |  43.6  | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_swin_tiny_36e_coco.pdparams) | [配置文件](./ppyoloe_plus_swin_tiny_36e_coco.yml) |
+| swin_T_224 | PP-YOLOE+       |    8    |   36e    |     ----     |  44.7  | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_swin_tiny_36e_coco.pdparams) | [配置文件](./ppyoloe_plus_swin_tiny_36e_coco.yml) |
 
 
 ## Citations

configs/swin/ppyoloe_plus_swin_tiny_36e_coco.yml

@@ -36,7 +36,7 @@ SwinTransformer:
 PPYOLOEHead:
   static_assigner_epoch: 12
   nms:
-    nms_top_k: 10000
+    nms_top_k: 1000
     keep_top_k: 300
     score_threshold: 0.01
     nms_threshold: 0.7