未验证 提交 b7aa8a92 编写于 作者: F Feng Ni 提交者: GitHub

update ppyoloe tiny modelzoo (#7687)

上级 e293ffb6
......@@ -48,10 +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 |
|:--------------:|:-----:|:-------:|:----------:|:----------:| :-------:|:--------------------------:|:---------------------------:|:---------:|:--------:|:---------------:| :---------------------: |:------------------------------------------------------------------------------------:|:-------------------------------------------:|
| 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-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 | 300 | 8 | 8 | cspresnet-t | 416 | 36.4 | 52.3 | 6.82 | 8.07 | - | - | [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(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) | 300 | 8 | 8 | cspresnet-t | 416 | 39.0 | 55.1 | 6.00 | 26.13 | - | - | [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) |
### Comprehensive Metrics
......@@ -84,10 +83,10 @@ PP-YOLOE is composed of following methods:
### Model Zoo on Objects365
| Model | Epoch | Machine number | GPU number | images/GPU | backbone | input shape | Box AP<sup>0.5 | Params(M) | FLOPs(G) | V100 FP32(FPS) | V100 TensorRT FP16(FPS) | download | config |
|:---------------:|:-----:|:-----------:|:-----------:|:-----------:|:---------:|:----------:|:--------------:|:---------:|:---------:|:-------------:|:-----------------------:| :--------:|:--------:|
| PP-YOLOE+_s | 60 | 3 | 8 | 8 | cspresnet-s | 640 | 18.1 | 7.93 | 17.36 | 208.3 | 333.3 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_s_obj365_pretrained.pdparams) | [config](./ppyoloe_plus_crn_s_60e_objects365.yml) |
| PP-YOLOE+_m | 60 | 4 | 8 | 8 | cspresnet-m | 640 | 25.0 | 23.43 | 49.91 | 123.4 | 208.3 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_m_obj365_pretrained.pdparams) | [config](./ppyoloe_plus_crn_m_60e_objects365.yml) |
| PP-YOLOE+_l | 60 | 3 | 8 | 8 | cspresnet-l | 640 | 30.8 | 52.20 | 110.07 | 78.1 | 149.2 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_l_obj365_pretrained.pdparams) | [config](./ppyoloe_plus_crn_l_60e_objects365.yml) |
| PP-YOLOE+_x | 60 | 4 | 8 | 8 | cspresnet-x | 640 | 32.7 | 98.42 | 206.59 | 45.0 | 95.2 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_x_obj365_pretrained.pdparams) | [config](./ppyoloe_plus_crn_x_60e_objects365.yml) |
| PP-YOLOE+_s | 60 | 3 | 8 | 8 | cspresnet-s | 640 | 18.1 | 7.93 | 17.36 | 208.3 | 333.3 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_s_obj365_pretrained.pdparams) | [config](./objects365/ppyoloe_plus_crn_s_60e_objects365.yml) |
| PP-YOLOE+_m | 60 | 4 | 8 | 8 | cspresnet-m | 640 | 25.0 | 23.43 | 49.91 | 123.4 | 208.3 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_m_obj365_pretrained.pdparams) | [config](./objects365/ppyoloe_plus_crn_m_60e_objects365.yml) |
| PP-YOLOE+_l | 60 | 3 | 8 | 8 | cspresnet-l | 640 | 30.8 | 52.20 | 110.07 | 78.1 | 149.2 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_l_obj365_pretrained.pdparams) | [config](./objects365/ppyoloe_plus_crn_l_60e_objects365.yml) |
| PP-YOLOE+_x | 60 | 4 | 8 | 8 | cspresnet-x | 640 | 32.7 | 98.42 | 206.59 | 45.0 | 95.2 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_x_obj365_pretrained.pdparams) | [config](./objects365/ppyoloe_plus_crn_x_60e_objects365.yml) |
**Notes:**
......@@ -98,8 +97,8 @@ PP-YOLOE is composed of following methods:
| Model | Epoch | GPU number | images/GPU | backbone | input shape | Box AP<sup>0.5 | Params(M) | FLOPs(G) | V100 FP32(FPS) | V100 TensorRT FP16(FPS) | download | config |
|:---------------:|:-----:|:-----------:|:-----------:|:---------:|:----------:|:--------------:|:---------:|:---------:|:-------------:|:-----------------------:| :-------: |:--------:|
| PP-YOLOE+_s | 30 | 8 | 8 | cspresnet-s | 640 | 86.7 | 7.93 | 17.36 | 208.3 | 333.3 | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_s_30e_voc.pdparams) | [config](./ppyoloe_plus_crn_s_30e_voc.yml) |
| PP-YOLOE+_l | 30 | 8 | 8 | cspresnet-l | 640 | 89.0 | 52.20 | 110.07 | 78.1 | 149.2 | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_l_30e_voc.pdparams) | [config](./ppyoloe_plus_crn_l_30e_voc.yml) |
| PP-YOLOE+_s | 30 | 8 | 8 | cspresnet-s | 640 | 86.7 | 7.93 | 17.36 | 208.3 | 333.3 | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_s_30e_voc.pdparams) | [config](./voc/ppyoloe_plus_crn_s_30e_voc.yml) |
| PP-YOLOE+_l | 30 | 8 | 8 | cspresnet-l | 640 | 89.0 | 52.20 | 110.07 | 78.1 | 149.2 | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_l_30e_voc.pdparams) | [config](./voc/ppyoloe_plus_crn_l_30e_voc.yml) |
### Feature Models
......
......@@ -47,10 +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 |
|:---------------:|:-----:|:---------:|:--------:|:----------:|:----------:|:--------------------------:|:---------------------------:|:---------:|:--------:|:---------------:| :---------------------: |:------------------------------------------------------------------------------------:|:-------------------------------------------:|
| 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-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 | 300 | 8 | 8 | cspresnet-t | 416 | 36.4 | 52.3 | 6.82 | 8.07 | - | - | [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(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) | 300 | 8 | 8 | cspresnet-t | 416 | 39.0 | 55.1 | 6.00 | 26.13 | - | - | [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) |
### 综合指标
......@@ -83,10 +82,10 @@ PP-YOLOE由以下方法组成
### Objects365数据集模型库
| 模型 | Epoch | 机器个数 | GPU个数 | 每GPU图片个数 | 骨干网络 | 输入尺寸 | Box AP<sup>0.5 | Params(M) | FLOPs(G) | V100 FP32(FPS) | V100 TensorRT FP16(FPS) | 模型下载 | 配置文件 |
|:---------------:|:-----:|:-----------:|:-----------:|:-----------:|:---------:|:----------:|:--------------:|:---------:|:---------:|:-------------:|:-----------------------:| :--------:|:--------:|
| PP-YOLOE+_s | 60 | 3 | 8 | 8 | cspresnet-s | 640 | 18.1 | 7.93 | 17.36 | 208.3 | 333.3 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_s_obj365_pretrained.pdparams) | [config](./ppyoloe_plus_crn_s_60e_objects365.yml) |
| PP-YOLOE+_m | 60 | 4 | 8 | 8 | cspresnet-m | 640 | 25.0 | 23.43 | 49.91 | 123.4 | 208.3 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_m_obj365_pretrained.pdparams) | [config](./ppyoloe_plus_crn_m_60e_objects365.yml) |
| PP-YOLOE+_l | 60 | 3 | 8 | 8 | cspresnet-l | 640 | 30.8 | 52.20 | 110.07 | 78.1 | 149.2 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_l_obj365_pretrained.pdparams) | [config](./ppyoloe_plus_crn_l_60e_objects365.yml) |
| PP-YOLOE+_x | 60 | 4 | 8 | 8 | cspresnet-x | 640 | 32.7 | 98.42 | 206.59 | 45.0 | 95.2 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_x_obj365_pretrained.pdparams) | [config](./ppyoloe_plus_crn_x_60e_objects365.yml) |
| PP-YOLOE+_s | 60 | 3 | 8 | 8 | cspresnet-s | 640 | 18.1 | 7.93 | 17.36 | 208.3 | 333.3 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_s_obj365_pretrained.pdparams) | [config](./objects365/ppyoloe_plus_crn_s_60e_objects365.yml) |
| PP-YOLOE+_m | 60 | 4 | 8 | 8 | cspresnet-m | 640 | 25.0 | 23.43 | 49.91 | 123.4 | 208.3 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_m_obj365_pretrained.pdparams) | [config](./objects365/ppyoloe_plus_crn_m_60e_objects365.yml) |
| PP-YOLOE+_l | 60 | 3 | 8 | 8 | cspresnet-l | 640 | 30.8 | 52.20 | 110.07 | 78.1 | 149.2 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_l_obj365_pretrained.pdparams) | [config](./objects365/ppyoloe_plus_crn_l_60e_objects365.yml) |
| PP-YOLOE+_x | 60 | 4 | 8 | 8 | cspresnet-x | 640 | 32.7 | 98.42 | 206.59 | 45.0 | 95.2 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_x_obj365_pretrained.pdparams) | [config](./objects365/ppyoloe_plus_crn_x_60e_objects365.yml) |
**注意:**
......@@ -96,8 +95,8 @@ PP-YOLOE由以下方法组成
### VOC数据集模型库
| 模型 | Epoch | GPU个数 | 每GPU图片个数 | 骨干网络 | 输入尺寸 | Box AP<sup>0.5 | Params(M) | FLOPs(G) | V100 FP32(FPS) | V100 TensorRT FP16(FPS) | 模型下载 | 配置文件 |
|:---------------:|:-----:|:-----------:|:-----------:|:---------:|:----------:|:--------------:|:---------:|:---------:|:-------------:|:-----------------------:| :-------: |:--------:|
| PP-YOLOE+_s | 30 | 8 | 8 | cspresnet-s | 640 | 86.7 | 7.93 | 17.36 | 208.3 | 333.3 | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_s_30e_voc.pdparams) | [config](./ppyoloe_plus_crn_s_30e_voc.yml) |
| PP-YOLOE+_l | 30 | 8 | 8 | cspresnet-l | 640 | 89.0 | 52.20 | 110.07 | 78.1 | 149.2 | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_l_30e_voc.pdparams) | [config](./ppyoloe_plus_crn_l_30e_voc.yml) |
| PP-YOLOE+_s | 30 | 8 | 8 | cspresnet-s | 640 | 86.7 | 7.93 | 17.36 | 208.3 | 333.3 | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_s_30e_voc.pdparams) | [config](./voc/ppyoloe_plus_crn_s_30e_voc.yml) |
| PP-YOLOE+_l | 30 | 8 | 8 | cspresnet-l | 640 | 89.0 | 52.20 | 110.07 | 78.1 | 149.2 | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_l_30e_voc.pdparams) | [config](./voc/ppyoloe_plus_crn_l_30e_voc.yml) |
### 垂类应用模型
......
# PP-YOLOE
## 模型库
### Objects365数据集模型库
| 模型 | Epoch | 机器个数 | GPU个数 | 每GPU图片个数 | 骨干网络 | 输入尺寸 | Box AP<sup>0.5 | Params(M) | FLOPs(G) | V100 FP32(FPS) | V100 TensorRT FP16(FPS) | 模型下载 | 配置文件 |
|:---------------:|:-----:|:-----------:|:-----------:|:-----------:|:---------:|:----------:|:--------------:|:---------:|:---------:|:-------------:|:-----------------------:| :--------:|:--------:|
| PP-YOLOE+_s | 60 | 3 | 8 | 8 | cspresnet-s | 640 | 18.1 | 7.93 | 17.36 | 208.3 | 333.3 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_s_obj365_pretrained.pdparams) | [config](./ppyoloe_plus_crn_s_60e_objects365.yml) |
| PP-YOLOE+_m | 60 | 4 | 8 | 8 | cspresnet-m | 640 | 25.0 | 23.43 | 49.91 | 123.4 | 208.3 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_m_obj365_pretrained.pdparams) | [config](./ppyoloe_plus_crn_m_60e_objects365.yml) |
| PP-YOLOE+_l | 60 | 3 | 8 | 8 | cspresnet-l | 640 | 30.8 | 52.20 | 110.07 | 78.1 | 149.2 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_l_obj365_pretrained.pdparams) | [config](./ppyoloe_plus_crn_l_60e_objects365.yml) |
| PP-YOLOE+_x | 60 | 4 | 8 | 8 | cspresnet-x | 640 | 32.7 | 98.42 | 206.59 | 45.0 | 95.2 | [model](https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_x_obj365_pretrained.pdparams) | [config](./ppyoloe_plus_crn_x_60e_objects365.yml) |
**注意:**
- 多机训练细节见[文档](../../../docs/tutorials/DistributedTraining_cn.md)
_BASE_: [
'../datasets/objects365_detection.yml',
'../runtime.yml',
'./_base_/optimizer_60e.yml',
'./_base_/ppyoloe_plus_crn.yml',
'./_base_/ppyoloe_plus_reader.yml',
'../../datasets/objects365_detection.yml',
'../../runtime.yml',
'../_base_/optimizer_60e.yml',
'../_base_/ppyoloe_plus_crn.yml',
'../_base_/ppyoloe_plus_reader.yml',
]
log_iter: 100
......
_BASE_: [
'../datasets/objects365_detection.yml',
'../runtime.yml',
'./_base_/optimizer_60e.yml',
'./_base_/ppyoloe_plus_crn.yml',
'./_base_/ppyoloe_plus_reader.yml',
'../../datasets/objects365_detection.yml',
'../../runtime.yml',
'../_base_/optimizer_60e.yml',
'../_base_/ppyoloe_plus_crn.yml',
'../_base_/ppyoloe_plus_reader.yml',
]
log_iter: 100
......
_BASE_: [
'../datasets/objects365_detection.yml',
'../runtime.yml',
'./_base_/optimizer_60e.yml',
'./_base_/ppyoloe_plus_crn.yml',
'./_base_/ppyoloe_plus_reader.yml',
'../../datasets/objects365_detection.yml',
'../../runtime.yml',
'../_base_/optimizer_60e.yml',
'../_base_/ppyoloe_plus_crn.yml',
'../_base_/ppyoloe_plus_reader.yml',
]
log_iter: 100
......
_BASE_: [
'../datasets/objects365_detection.yml',
'../runtime.yml',
'./_base_/optimizer_60e.yml',
'./_base_/ppyoloe_plus_crn.yml',
'./_base_/ppyoloe_plus_reader.yml',
'../../datasets/objects365_detection.yml',
'../../runtime.yml',
'../_base_/optimizer_60e.yml',
'../_base_/ppyoloe_plus_crn.yml',
'../_base_/ppyoloe_plus_reader.yml',
]
log_iter: 100
......
......@@ -3,7 +3,7 @@ _BASE_: [
'../runtime.yml',
'./_base_/optimizer_300e.yml',
'./_base_/ppyoloe_plus_crn_tiny_auxhead.yml',
'./_base_/ppyoloe_plus_tiny_reader.yml',
'./_base_/ppyoloe_plus_reader.yml', # 640
]
log_iter: 100
......
# PP-YOLOE
## 模型库
### VOC数据集模型库
| 模型 | Epoch | GPU个数 | 每GPU图片个数 | 骨干网络 | 输入尺寸 | Box AP<sup>0.5 | Params(M) | FLOPs(G) | V100 FP32(FPS) | V100 TensorRT FP16(FPS) | 模型下载 | 配置文件 |
|:---------------:|:-----:|:-----------:|:-----------:|:---------:|:----------:|:--------------:|:---------:|:---------:|:-------------:|:-----------------------:| :-------: |:--------:|
| PP-YOLOE+_s | 30 | 8 | 8 | cspresnet-s | 640 | 86.7 | 7.93 | 17.36 | 208.3 | 333.3 | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_s_30e_voc.pdparams) | [config](./ppyoloe_plus_crn_s_30e_voc.yml) |
| PP-YOLOE+_l | 30 | 8 | 8 | cspresnet-l | 640 | 89.0 | 52.20 | 110.07 | 78.1 | 149.2 | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_l_30e_voc.pdparams) | [config](./ppyoloe_plus_crn_l_30e_voc.yml) |
_BASE_: [
'../datasets/voc.yml',
'../runtime.yml',
'./_base_/optimizer_80e.yml',
'./_base_/ppyoloe_plus_crn.yml',
'./_base_/ppyoloe_plus_reader.yml',
'../../datasets/voc.yml',
'../../runtime.yml',
'../_base_/optimizer_80e.yml',
'../_base_/ppyoloe_plus_crn.yml',
'../_base_/ppyoloe_plus_reader.yml',
]
log_iter: 100
......
_BASE_: [
'../datasets/voc.yml',
'../runtime.yml',
'./_base_/optimizer_80e.yml',
'./_base_/ppyoloe_plus_crn.yml',
'./_base_/ppyoloe_plus_reader.yml',
'../../datasets/voc.yml',
'../../runtime.yml',
'../_base_/optimizer_80e.yml',
'../_base_/ppyoloe_plus_crn.yml',
'../_base_/ppyoloe_plus_reader.yml',
]
log_iter: 100
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册