未验证 提交 f5394864 编写于 作者: F Feng Ni 提交者: GitHub

[cherry-pick] update phuman ppvehicle tiny models (#7728)

* update pphuman ppvechicle new models, test=document_fixb

* update docs, test=document_fixb

* update docs, test=document_fix

* fix configs, test=document_fix
上级 8a2367c9
...@@ -11,8 +11,8 @@ PaddleDetection团队提供了针对行人的基于PP-YOLOE的检测模型,用 ...@@ -11,8 +11,8 @@ PaddleDetection团队提供了针对行人的基于PP-YOLOE的检测模型,用
|PP-YOLOE-l| CrowdHuman | 48.0 | 81.9 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_36e_crowdhuman.pdparams) | [配置文件](./ppyoloe_crn_l_36e_crowdhuman.yml) | |PP-YOLOE-l| CrowdHuman | 48.0 | 81.9 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_36e_crowdhuman.pdparams) | [配置文件](./ppyoloe_crn_l_36e_crowdhuman.yml) |
|PP-YOLOE-s| 业务数据集 | 53.2 | - | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_s_36e_pipeline.zip) | [配置文件](./ppyoloe_crn_s_36e_pphuman.yml) | |PP-YOLOE-s| 业务数据集 | 53.2 | - | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_s_36e_pipeline.zip) | [配置文件](./ppyoloe_crn_s_36e_pphuman.yml) |
|PP-YOLOE-l| 业务数据集 | 57.8 | - | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip) | [配置文件](./ppyoloe_crn_l_36e_pphuman.yml) | |PP-YOLOE-l| 业务数据集 | 57.8 | - | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip) | [配置文件](./ppyoloe_crn_l_36e_pphuman.yml) |
|PP-YOLOE+_t-P2(320)| 业务数据集 | 49.8 | - | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_t_p2_60e_pipeline.zip) | [配置文件](./ppyoloe_plus_crn_t_p2_60e_pphuman.yml) | |PP-YOLOE+_t-P2-aux(320)| 业务数据集 | 49.8 | 85.0 | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/pphuman/ppyoloe_plus_crn_t_p2_auxhead_320_60e_pphuman.zip) | [配置文件](./ppyoloe_plus_crn_t_p2_auxhead_320_60e_pphuman.yml) |
|PP-YOLOE+_t-P2(416)| 业务数据集 | 52.2 | - | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_t_p2_60e_pipeline.zip) | [配置文件](./ppyoloe_plus_crn_t_p2_60e_pphuman.yml) | |PP-YOLOE+_t-aux(320)| 业务数据集 | 45.7 | 81.2 | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/pphuman/ppyoloe_plus_crn_t_auxhead_320_60e_pphuman.zip) | [配置文件](./ppyoloe_plus_crn_t_auxhead_320_60e_pphuman.yml) |
**注意:** **注意:**
......
...@@ -3,14 +3,14 @@ _BASE_: [ ...@@ -3,14 +3,14 @@ _BASE_: [
'../runtime.yml', '../runtime.yml',
'../ppyoloe/_base_/optimizer_300e.yml', '../ppyoloe/_base_/optimizer_300e.yml',
'../ppyoloe/_base_/ppyoloe_plus_crn_tiny_auxhead.yml', '../ppyoloe/_base_/ppyoloe_plus_crn_tiny_auxhead.yml',
'../ppyoloe/_base_/ppyoloe_plus_reader_tiny.yml', '../ppyoloe/_base_/ppyoloe_plus_reader_320.yml',
] ]
log_iter: 100 log_iter: 100
snapshot_epoch: 4 snapshot_epoch: 4
weights: output/ppyoloe_plus_crn_tiny_60e_pphuman/model_final weights: output/ppyoloe_plus_crn_t_auxhead_320_60e_pphuman/model_final
pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_tiny_auxhead_300e_coco.pdparams pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_auxhead_300e_coco.pdparams # 640*640 COCO mAP 39.7
depth_mult: 0.33 depth_mult: 0.33
width_mult: 0.375 width_mult: 0.375
......
_BASE_: [
'../datasets/coco_detection.yml',
'../runtime.yml',
'../ppyoloe/_base_/optimizer_300e.yml',
'../ppyoloe/_base_/ppyoloe_plus_crn_tiny_auxhead.yml',
'../ppyoloe/_base_/ppyoloe_plus_reader_320.yml',
]
log_iter: 100
snapshot_epoch: 4
weights: output/ppyoloe_plus_crn_t_p2_auxhead_320_60e_pphuman/model_final
pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_p2_auxhead_320_300e_coco.pdparams # 320*320 COCO mAP 36.3
depth_mult: 0.33
width_mult: 0.375
num_classes: 1
TrainDataset:
!COCODataSet
image_dir: ""
anno_path: annotations/train.json
dataset_dir: dataset/pphuman
data_fields: ['image', 'gt_bbox', 'gt_class', 'is_crowd']
EvalDataset:
!COCODataSet
image_dir: ""
anno_path: annotations/val.json
dataset_dir: dataset/pphuman
TestDataset:
!ImageFolder
anno_path: annotations/val.json
dataset_dir: dataset/pphuman
TrainReader:
batch_size: 8
epoch: 60
LearningRate:
base_lr: 0.001
schedulers:
- !CosineDecay
max_epochs: 72
- !LinearWarmup
start_factor: 0.
epochs: 1
architecture: PPYOLOEWithAuxHead
PPYOLOEWithAuxHead:
backbone: CSPResNet
neck: CustomCSPPAN
yolo_head: PPYOLOEHead
aux_head: SimpleConvHead
post_process: ~
CSPResNet:
return_idx: [0, 1, 2, 3] # index 0 stands for P2
CustomCSPPAN:
out_channels: [384, 384, 384, 384]
SimpleConvHead:
fpn_strides: [32, 16, 8, 4]
PPYOLOEHead:
fpn_strides: [32, 16, 8, 4]
static_assigner_epoch: -1
nms:
name: MultiClassNMS
nms_top_k: 1000
keep_top_k: 300
score_threshold: 0.01
nms_threshold: 0.7
...@@ -19,8 +19,8 @@ PaddleDetection团队提供了针对自动驾驶场景的基于PP-YOLOE的检测 ...@@ -19,8 +19,8 @@ PaddleDetection团队提供了针对自动驾驶场景的基于PP-YOLOE的检测
|PP-YOLOE-s| PPVehicle9cls | 9 | 35.3 | [下载链接](https://paddledet.bj.bcebos.com/models/mot_ppyoloe_s_36e_ppvehicle9cls.pdparams) | [配置文件](./mot_ppyoloe_s_36e_ppvehicle9cls.yml) | |PP-YOLOE-s| PPVehicle9cls | 9 | 35.3 | [下载链接](https://paddledet.bj.bcebos.com/models/mot_ppyoloe_s_36e_ppvehicle9cls.pdparams) | [配置文件](./mot_ppyoloe_s_36e_ppvehicle9cls.yml) |
|PP-YOLOE-l| PPVehicle | 1 | 63.9 | [下载链接](https://paddledet.bj.bcebos.com/models/mot_ppyoloe_l_36e_ppvehicle.pdparams) | [配置文件](./mot_ppyoloe_l_36e_ppvehicle.yml) | |PP-YOLOE-l| PPVehicle | 1 | 63.9 | [下载链接](https://paddledet.bj.bcebos.com/models/mot_ppyoloe_l_36e_ppvehicle.pdparams) | [配置文件](./mot_ppyoloe_l_36e_ppvehicle.yml) |
|PP-YOLOE-s| PPVehicle | 1 | 61.3 | [下载链接](https://paddledet.bj.bcebos.com/models/mot_ppyoloe_s_36e_ppvehicle.pdparams) | [配置文件](./mot_ppyoloe_s_36e_ppvehicle.yml) | |PP-YOLOE-s| PPVehicle | 1 | 61.3 | [下载链接](https://paddledet.bj.bcebos.com/models/mot_ppyoloe_s_36e_ppvehicle.pdparams) | [配置文件](./mot_ppyoloe_s_36e_ppvehicle.yml) |
|PP-YOLOE+_t-P2(320)| PPVehicle | 1 | 58.2 | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_t_p2_60e_ppvehicle.zip) | [配置文件](./ppyoloe_plus_crn_t_p2_60e_ppvehicle.yml) | |PP-YOLOE+_t-P2-aux(320)| PPVehicle | 1 | 58.2 | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/ppvehicle/ppyoloe_plus_crn_t_p2_auxhead_320_60e_ppvehicle.zip) | [配置文件](./ppyoloe_plus_crn_t_p2_auxhead_320_60e_ppvehicle.yml) |
|PP-YOLOE+_t-P2(416)| PPVehicle | 1 | 60.5 | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_t_p2_60e_ppvehicle.zip) | [配置文件](./ppyoloe_plus_crn_t_p2_60e_ppvehicle.yml) | |PP-YOLOE+_t-aux(320)| PPVehicle | 1 | 53.5 | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/ppvehicle/ppyoloe_plus_crn_t_auxhead_320_60e_ppvehicle.zip) | [配置文件](./ppyoloe_plus_crn_t_auxhead_320_60e_ppvehicle.yml) |
**注意:** **注意:**
......
...@@ -3,14 +3,14 @@ _BASE_: [ ...@@ -3,14 +3,14 @@ _BASE_: [
'../runtime.yml', '../runtime.yml',
'../ppyoloe/_base_/optimizer_300e.yml', '../ppyoloe/_base_/optimizer_300e.yml',
'../ppyoloe/_base_/ppyoloe_plus_crn_tiny_auxhead.yml', '../ppyoloe/_base_/ppyoloe_plus_crn_tiny_auxhead.yml',
'../ppyoloe/_base_/ppyoloe_plus_reader_tiny.yml', '../ppyoloe/_base_/ppyoloe_plus_reader_320.yml',
] ]
log_iter: 100 log_iter: 100
snapshot_epoch: 4 snapshot_epoch: 4
weights: output/ppyoloe_plus_crn_tiny_60e_ppvehicle/model_final weights: output/ppyoloe_plus_crn_t_auxhead_320_60e_ppvehicle/model_final
pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_tiny_auxhead_300e_coco.pdparams pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_auxhead_300e_coco.pdparams # 640*640 COCO mAP 39.7
depth_mult: 0.33 depth_mult: 0.33
width_mult: 0.375 width_mult: 0.375
......
_BASE_: [
'../datasets/coco_detection.yml',
'../runtime.yml',
'../ppyoloe/_base_/optimizer_300e.yml',
'../ppyoloe/_base_/ppyoloe_plus_crn_tiny_auxhead.yml',
'../ppyoloe/_base_/ppyoloe_plus_reader_320.yml',
]
log_iter: 100
snapshot_epoch: 4
weights: output/ppyoloe_plus_crn_t_p2_auxhead_320_60e_ppvehicle/model_final
pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_t_p2_auxhead_320_300e_coco.pdparams # 320*320 COCO mAP 36.3
depth_mult: 0.33
width_mult: 0.375
num_classes: 1
TrainDataset:
!COCODataSet
image_dir: ""
anno_path: annotations/train_all.json
dataset_dir: dataset/ppvehicle
data_fields: ['image', 'gt_bbox', 'gt_class', 'is_crowd']
allow_empty: true
EvalDataset:
!COCODataSet
image_dir: ""
anno_path: annotations/val_all.json
dataset_dir: dataset/ppvehicle
TestDataset:
!ImageFolder
anno_path: annotations/val_all.json
dataset_dir: dataset/ppvehicle
TrainReader:
batch_size: 8
epoch: 60
LearningRate:
base_lr: 0.001
schedulers:
- !CosineDecay
max_epochs: 72
- !LinearWarmup
start_factor: 0.
epochs: 1
architecture: PPYOLOEWithAuxHead
PPYOLOEWithAuxHead:
backbone: CSPResNet
neck: CustomCSPPAN
yolo_head: PPYOLOEHead
aux_head: SimpleConvHead
post_process: ~
CSPResNet:
return_idx: [0, 1, 2, 3] # index 0 stands for P2
CustomCSPPAN:
out_channels: [384, 384, 384, 384]
SimpleConvHead:
fpn_strides: [32, 16, 8, 4]
PPYOLOEHead:
fpn_strides: [32, 16, 8, 4]
static_assigner_epoch: -1
nms:
name: MultiClassNMS
nms_top_k: 1000
keep_top_k: 300
score_threshold: 0.01
nms_threshold: 0.7
...@@ -48,9 +48,9 @@ PP-YOLOE is composed of following methods: ...@@ -48,9 +48,9 @@ PP-YOLOE is composed of following methods:
| 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 | | 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)| 300 | 8 | 8 | cspresnet-t | 640 | 39.5 | 51.7 | 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) | 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 | 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_300e_coco.pdparams) | [config](./ppyoloe_crn_t_p2_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) | 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_300e_coco.pdparams) | [config](./ppyoloe_plus_crn_t_p2_auxhead_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) |
### Comprehensive Metrics ### Comprehensive Metrics
......
...@@ -47,9 +47,9 @@ PP-YOLOE由以下方法组成 ...@@ -47,9 +47,9 @@ PP-YOLOE由以下方法组成
| 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 | | 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)| 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) | 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 | 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_300e_coco.pdparams) | [config](./ppyoloe_crn_t_p2_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) | 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_300e_coco.pdparams) | [config](./ppyoloe_plus_crn_t_p2_auxhead_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) |
### 综合指标 ### 综合指标
......
...@@ -8,11 +8,10 @@ PaddleDetection提供了对PPYOLOE+ 进行模型蒸馏的方案,结合了logit ...@@ -8,11 +8,10 @@ PaddleDetection提供了对PPYOLOE+ 进行模型蒸馏的方案,结合了logit
| ----------------- | ----------- | ------ | :----: | :-----------: | :--------------: | :------------: | | ----------------- | ----------- | ------ | :----: | :-----------: | :--------------: | :------------: |
| PP-YOLOE+_x | teacher | 640 | 80e | 54.7 | [config](../ppyoloe_plus_crn_x_80e_coco.yml) | [model](https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_x_80e_coco.pdparams) | | PP-YOLOE+_x | teacher | 640 | 80e | 54.7 | [config](../ppyoloe_plus_crn_x_80e_coco.yml) | [model](https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_x_80e_coco.pdparams) |
| PP-YOLOE+_l | student | 640 | 80e | 52.9 | [config](../ppyoloe_plus_crn_l_80e_coco.yml) | [model](https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_l_80e_coco.pdparams) | | PP-YOLOE+_l | student | 640 | 80e | 52.9 | [config](../ppyoloe_plus_crn_l_80e_coco.yml) | [model](https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_l_80e_coco.pdparams) |
| PP-YOLOE+_l | distill | 640 | 80e | 54.0(+1.1) | [config](./ppyoloe_plus_crn_l_80e_coco_distill.yml),[slim_config](../../slim/distill/ppyoloe_plus_distill_x_distill_l.yml) | [model](https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_l_80e_coco_distill.pdparams) | | PP-YOLOE+_l | distill | 640 | 80e | **54.0(+1.1)** | [config](./ppyoloe_plus_crn_l_80e_coco_distill.yml),[slim_config](../../slim/distill/ppyoloe_plus_distill_x_distill_l.yml) | [model](https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_l_80e_coco_distill.pdparams) |
| PP-YOLOE+_l | teacher | 640 | 80e | 52.9 | [config](../ppyoloe_plus_crn_l_80e_coco.yml) | [model](https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_l_80e_coco.pdparams) | | PP-YOLOE+_l | teacher | 640 | 80e | 52.9 | [config](../ppyoloe_plus_crn_l_80e_coco.yml) | [model](https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_l_80e_coco.pdparams) |
| PP-YOLOE+_m | student | 640 | 80e | 49.8 | [config](../ppyoloe_plus_crn_m_80e_coco.yml) | [model](https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_m_80e_coco.pdparams) | | PP-YOLOE+_m | student | 640 | 80e | 49.8 | [config](../ppyoloe_plus_crn_m_80e_coco.yml) | [model](https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_m_80e_coco.pdparams) |
| PP-YOLOE+_m | distill | 640 | 80e | 50.7(+0.9) | [config](./ppyoloe_plus_crn_m_80e_coco_distill.yml),[slim_config](../../slim/distill/ppyoloe_plus_distill_l_distill_m.yml) | [model](https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_m_80e_coco_distill.pdparams) | | PP-YOLOE+_m | distill | 640 | 80e | **51.0(+1.2)** | [config](./ppyoloe_plus_crn_m_80e_coco_distill.yml),[slim_config](../../slim/distill/ppyoloe_plus_distill_l_distill_m.yml) | [model](https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_m_80e_coco_distill.pdparams) |
## 快速开始 ## 快速开始
......
...@@ -3,12 +3,12 @@ _BASE_: [ ...@@ -3,12 +3,12 @@ _BASE_: [
'../runtime.yml', '../runtime.yml',
'./_base_/optimizer_300e.yml', './_base_/optimizer_300e.yml',
'./_base_/ppyoloe_crn.yml', './_base_/ppyoloe_crn.yml',
'./_base_/ppyoloe_plus_tiny_reader.yml', # 320*320 './_base_/ppyoloe_plus_reader_320.yml',
] ]
log_iter: 100 log_iter: 100
snapshot_epoch: 10 snapshot_epoch: 10
weights: output/ppyoloe_crn_t_p2_300e_coco/model_final weights: output/ppyoloe_crn_t_p2_320_300e_coco/model_final
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/CSPResNetb_t_pretrained.pdparams pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/CSPResNetb_t_pretrained.pdparams
depth_mult: 0.33 depth_mult: 0.33
......
...@@ -3,12 +3,12 @@ _BASE_: [ ...@@ -3,12 +3,12 @@ _BASE_: [
'../runtime.yml', '../runtime.yml',
'./_base_/optimizer_300e.yml', './_base_/optimizer_300e.yml',
'./_base_/ppyoloe_plus_crn_tiny_auxhead.yml', './_base_/ppyoloe_plus_crn_tiny_auxhead.yml',
'./_base_/ppyoloe_plus_tiny_reader.yml', # 320*320 './_base_/ppyoloe_plus_reader_320.yml',
] ]
log_iter: 100 log_iter: 100
snapshot_epoch: 10 snapshot_epoch: 10
weights: output/ppyoloe_plus_crn_t_p2_auxhead_300e_coco/model_final weights: output/ppyoloe_plus_crn_t_p2_auxhead_320_300e_coco/model_final
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/CSPResNetb_t_pretrained.pdparams pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/CSPResNetb_t_pretrained.pdparams
depth_mult: 0.33 depth_mult: 0.33
......
...@@ -37,8 +37,10 @@ class ESEAttn(nn.Layer): ...@@ -37,8 +37,10 @@ class ESEAttn(nn.Layer):
self.fc = nn.Conv2D(feat_channels, feat_channels, 1) self.fc = nn.Conv2D(feat_channels, feat_channels, 1)
if attn_conv == 'convbn': if attn_conv == 'convbn':
self.conv = ConvBNLayer(feat_channels, feat_channels, 1, act=act) self.conv = ConvBNLayer(feat_channels, feat_channels, 1, act=act)
else: elif attn_conv == 'repvgg':
self.conv = RepVggBlock(feat_channels, feat_channels, act=act) self.conv = RepVggBlock(feat_channels, feat_channels, act=act)
else:
self.conv = None
self._init_weights() self._init_weights()
def _init_weights(self): def _init_weights(self):
...@@ -46,7 +48,10 @@ class ESEAttn(nn.Layer): ...@@ -46,7 +48,10 @@ class ESEAttn(nn.Layer):
def forward(self, feat, avg_feat): def forward(self, feat, avg_feat):
weight = F.sigmoid(self.fc(avg_feat)) weight = F.sigmoid(self.fc(avg_feat))
if self.conv:
return self.conv(feat * weight) return self.conv(feat * weight)
else:
return feat * weight
@register @register
......
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