add ppyoloe tiny 320 models, test=document_fix (#7793)

configs/ppyoloe/README.md

@@ -46,11 +46,12 @@ PP-YOLOE is composed of following methods:
 
 #### Tiny model
 
-|     Model      | Epoch | GPU number | images/GPU |  backbone  | input shape | Box AP<sup>val<br>0.5:0.95 | Box AP<sup>test<br>0.5:0.95 | Params(M) | FLOPs(G) | V100 FP32(FPS) | V100 TensorRT FP16(FPS) |                                       download                                       |                   config                    |
-|:--------------:|:-----:|:-------:|:----------:|:----------:| :-------:|:--------------------------:|:---------------------------:|:---------:|:--------:|:---------------:| :---------------------: |:------------------------------------------------------------------------------------:|:-------------------------------------------:|
-|   PP-YOLOE+_t-aux(640) |  300   |     8     |    8     | cspresnet-t  |    640  |            39.7       |            56.4             |   4.85   |  19.15 |   -    |   344.8   | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_auxhead_300e_coco.pdparams) | [config](./ppyoloe_plus_crn_t_auxhead_300e_coco.yml) |
-|   PP-YOLOE-t-P2(320)   |  300   |     8     |    8     | cspresnet-t  |    320  |            34.7       |            50.0             |   6.82   |  4.78  |   -    |   -   | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_t_p2_320_300e_coco.pdparams) | [config](./ppyoloe_crn_t_p2_320_300e_coco.yml) |
-|   PP-YOLOE+_t-P2-aux(320) |  300 |     8   |    8     | cspresnet-t  |    320  |            36.3       |            51.7             |   6.00   |  15.46 |   -    |   -   | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_p2_auxhead_320_300e_coco.pdparams) | [config](./ppyoloe_plus_crn_t_p2_auxhead_320_300e_coco.yml) |
+|   Model  | Epoch | GPU number | images/GPU |  backbone  | input shape | Box AP<sup>val<br>0.5:0.95 | Box AP<sup>test<br>0.5:0.95 | Params(M) | FLOPs(G) | T4 TensorRT FP16(FPS) | download  | config  |
+|:--------:|:-----:|:----------:|:----------:|:----------:|:-----------:|:--------------------------:|:---------------------------:|:---------:|:--------:|:---------------------:| :------: |:--------:|
+|   PP-YOLOE+_t-aux(640) |  300   |     8     |    8     | cspresnet-t  |    640  |            39.7       |            56.4             |   4.85   |  19.15 |  344.8   | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_auxhead_300e_coco.pdparams) | [config](./ppyoloe_plus_crn_t_auxhead_300e_coco.yml) |
+|   PP-YOLOE+_t-aux(640)-relu |  300   |     8     |    8     | cspresnet-t  |    640  |            36.4       |            53.0        |   3.60   |  12.17 |   476.2   | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_auxhead_relu_300e_coco.pdparams) | [config](./ppyoloe_plus_crn_t_auxhead_relu_300e_coco.yml) |
+|   PP-YOLOE+_t-aux(320) |  300   |     8     |    8     | cspresnet-t  |    320  |            33.3       |            48.5             |   4.85   |  4.80 |   729.9   | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_auxhead_320_300e_coco.pdparams) | [config](./ppyoloe_plus_crn_t_auxhead_320_300e_coco.yml) |
+|   PP-YOLOE+_t-aux(320)-relu |  300   |     8     |    8     | cspresnet-t  |    320  |            29.5       |            43.7        |   3.60   |  3.04 |   984.8   | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_auxhead_relu_320_300e_coco.pdparams) | [config](./ppyoloe_plus_crn_t_auxhead_relu_320_300e_coco.yml) |
 
 
 ### Comprehensive Metrics

configs/ppyoloe/README_cn.md

@@ -45,10 +45,13 @@ PP-YOLOE由以下方法组成
 
 #### Tiny模型
 
-|       模型        | Epoch |   GPU个数   | 每GPU图片个数 |  骨干网络  |    输入尺寸    | Box AP<sup>val<br>0.5:0.95 | Box AP<sup>test<br>0.5:0.95 | Params(M) | FLOPs(G) | V100 FP32(FPS) | V100 TensorRT FP16(FPS) |                                         模型下载                                         |                    配置文件                     |
-|:---------------:|:-----:|:---------:|:--------:|:----------:|:----------:|:--------------------------:|:---------------------------:|:---------:|:--------:|:---------------:| :---------------------: |:------------------------------------------------------------------------------------:|:-------------------------------------------:|
-|   PP-YOLOE+_t-aux(640) |  300   |     8     |    8     | cspresnet-t  |    640  |            39.7       |            56.4             |   4.85   |  19.15 |   -    |   344.8   | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_auxhead_300e_coco.pdparams) | [config](./ppyoloe_plus_crn_t_auxhead_300e_coco.yml) |
-|   PP-YOLOE+_t-aux(640)-relu |  300   |     8     |    8     | cspresnet-t  |    640  |            36.5       |            53.1             |   3.60   |  12.17 |   -    |   476.2   | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_auxhead_relu_300e_coco.pdparams) | [config](./ppyoloe_plus_crn_t_auxhead_relu_300e_coco.yml) |
+|    模型    | Epoch |  GPU个数  | 每GPU图片个数 |  骨干网络  |  输入尺寸  | Box AP<sup>val<br>0.5:0.95 | Box AP<sup>test<br>0.5:0.95 | Params(M) | FLOPs(G) | T4 TensorRT FP16(FPS) |  模型下载 |  配置文件 |
+|:----------:|:-----:|:--------:|:-----------:|:---------:|:--------:|:--------------------------:|:---------------------------:|:---------:|:--------:|:---------------------:| :------: |:--------:|
+|   PP-YOLOE+_t-aux(640) |  300   |     8     |    8     | cspresnet-t  |    640  |            39.7       |            56.4             |   4.85   |  19.15 |  344.8   | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_auxhead_300e_coco.pdparams) | [config](./ppyoloe_plus_crn_t_auxhead_300e_coco.yml) |
+|   PP-YOLOE+_t-aux(640)-relu |  300   |     8     |    8     | cspresnet-t  |    640  |            36.4       |            53.0        |   3.60   |  12.17 |   476.2   | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_auxhead_relu_300e_coco.pdparams) | [config](./ppyoloe_plus_crn_t_auxhead_relu_300e_coco.yml) |
+|   PP-YOLOE+_t-aux(320) |  300   |     8     |    8     | cspresnet-t  |    320  |            33.3       |            48.5             |   4.85   |  4.80 |   729.9   | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_auxhead_320_300e_coco.pdparams) | [config](./ppyoloe_plus_crn_t_auxhead_320_300e_coco.yml) |
+|   PP-YOLOE+_t-aux(320)-relu |  300   |     8     |    8     | cspresnet-t  |    320  |            29.5       |            43.7        |   3.60   |  3.04 |   984.8   | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_auxhead_relu_320_300e_coco.pdparams) | [config](./ppyoloe_plus_crn_t_auxhead_relu_320_300e_coco.yml) |
+
 
 ### 综合指标
 |            模型            | Epoch | AP<sup>0.5:0.95 | AP<sup>0.5 | AP<sup>0.75 | AP<sup>small | AP<sup>medium | AP<sup>large | AR<sup>small | AR<sup>medium | AR<sup>large |

configs/ppyoloe/ppyoloe_plus_crn_t_auxhead_320_300e_coco.yml

+_BASE_: [
+  '../datasets/coco_detection.yml',
+  '../runtime.yml',
+  './_base_/optimizer_300e.yml',
+  './_base_/ppyoloe_plus_crn_tiny_auxhead.yml',
+  './_base_/ppyoloe_plus_reader_320.yml',
+]
+
+log_iter: 100
+snapshot_epoch: 10
+weights: output/ppyoloe_plus_crn_t_auxhead_320_300e_coco/model_final
+
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/CSPResNetb_t_pretrained.pdparams
+depth_mult: 0.33
+width_mult: 0.375

configs/ppyoloe/ppyoloe_plus_crn_t_auxhead_relu_320_300e_coco.yml

+_BASE_: [
+  '../datasets/coco_detection.yml',
+  '../runtime.yml',
+  './_base_/optimizer_300e.yml',
+  './_base_/ppyoloe_plus_crn_tiny_auxhead.yml',
+  './_base_/ppyoloe_plus_reader_320.yml',
+]
+
+log_iter: 100
+snapshot_epoch: 10
+weights: output/ppyoloe_plus_crn_t_auxhead_relu_320_300e_coco/model_final
+
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/CSPResNetb_t_pretrained.pdparams
+depth_mult: 0.33
+width_mult: 0.375
+
+
+CSPResNet:
+  act: 'relu'
+
+CustomCSPPAN:
+  act: 'relu'
+
+PPYOLOEHead:
+  act: 'relu'
+  attn_conv: None