-
Notifications
You must be signed in to change notification settings - Fork 535
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
* add cspnext * add neck * update * align s,tiny test * update * update * fix bug of UT * fix typehint * fix resize bug * update s and tiny * update s and tiny link * update convert * add cls config with rtmdet * update config * fix ci error Co-authored-by: wanghonglie <wanghonglie@pjlab.org.cn>
- Loading branch information
1 parent
8ba4979
commit bb3aa48
Showing
26 changed files
with
2,097 additions
and
42 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,26 @@ | ||
# RTMDet | ||
|
||
<!-- [ALGORITHM] --> | ||
|
||
## Abstract | ||
|
||
Our tech-report will be released soon. | ||
|
||
<div align=center> | ||
<img src="https://user-images.githubusercontent.com/12907710/192182907-f9a671d6-89cb-4d73-abd8-c2b9dada3c66.png"/> | ||
</div> | ||
|
||
## Results and Models | ||
|
||
| Backbone | size | SyncBN | ox AP | Params(M) | FLOPS(G) | TRT-FP16-Latency(ms) | Config | Download | | ||
| :---------: | :--: | :----: | ----: | :-------: | :------: | :------------------: | :-----------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | | ||
| RTMDet-tiny | 640 | Yes | 40.9 | 4.8 | 8.1 | 0.98 | [config](./rtmdet_tiny_syncbn_8xb32-300e_coco.py) | [model](https://download.openmmlab.com/mmyolo/v0/rtmdet/rtmdet_tiny_syncbn_8xb32-300e_coco/rtmdet_tiny_syncbn_8xb32-300e_coco_20220902_112414-259f3241.pth) \| [log](https://download.openmmlab.com/mmdetection/v3.0/rtmdet/rtmdet_tiny_8xb32-300e_coco/rtmdet_s_8xb32-300e_coco_20220902_112414.log.json) | | ||
| RTMDet-s | 640 | Yes | 44.5 | 8.89 | 14.8 | 1.22 | [config](./rtmdet_s_syncbn_8xb32-300e_coco.py) | [model](https://download.openmmlab.com/mmyolo/v0/rtmdet/rtmdet_s_syncbn_8xb32-300e_coco/rtmdet_s_syncbn_8xb32-300e_coco_20220905_161602-fd1cacb9.pth) \| [log](https://download.openmmlab.com/mmdetection/v3.0/rtmdet/rtmdet_s_8xb32-300e_coco/rtmdet_s_8xb32-300e_coco_20220905_161602.log.json) | | ||
| RTMDet-m | 640 | Yes | 49.1 | 24.71 | 39.27 | 1.62 | [config](./rtmdet_m_syncbn_8xb32-300e_coco.py) | [model](https://download.openmmlab.com/mmyolo/v0/rtmdet/rtmdet_m_syncbn_8xb32-300e_coco/rtmdet_m_syncbn_8xb32-300e_coco_20220924_132959-d9f2e90d.pth) \| [log](https://download.openmmlab.com/mmdetection/v3.0/rtmdet/rtmdet_m_8xb32-300e_coco/rtmdet_m_8xb32-300e_coco_20220924_132959.log.json) | | ||
| RTMDet-l | 640 | Yes | 51.3 | 52.3 | 80.23 | 2.44 | [config](./rtmdet_l_syncbn_8xb32-300e_coco.py) | [model](https://download.openmmlab.com/mmyolo/v0/rtmdet/rtmdet_l_syncbn_8xb32-300e_coco/rtmdet_l_syncbn_8xb32-300e_coco_20220926_150401-40c754b5.pth) \| [log](https://download.openmmlab.com/mmdetection/v3.0/rtmdet/rtmdet_l_8xb32-300e_coco/rtmdet_l_8xb32-300e_coco_20220926_150401.log.json) | | ||
| RTMDet-x | 640 | Yes | 52.6 | 94.86 | 141.67 | 3.10 | [config](./rtmdet_x_syncbn_8xb32-300e_coco.py) | [model](<>) \| [log](<>) | | ||
|
||
**Note**: | ||
|
||
1. The inference speed is measured on an NVIDIA 3090 GPU with TensorRT 8.4.3, cuDNN 8.2.0, FP16, batch size=1, and without NMS. | ||
2. We still directly use the weights trained by `mmdet` currently. A re-trained model will be released later. |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,53 @@ | ||
# CSPNeXt ImageNet Pre-training | ||
|
||
In this folder, we provide the imagenet pre-training config of RTMDet's backbone CSPNeXt. | ||
|
||
## Requirements | ||
|
||
To train with these configs, please install [MMClassification 1.x](https://github.com/open-mmlab/mmclassification/tree/1.x) first. | ||
|
||
Install by MIM: | ||
|
||
```shell | ||
mim install mmcls>=1.0.0rc0 | ||
``` | ||
|
||
or install by pip: | ||
|
||
```shell | ||
pip install mmcls>=1.0.0rc0 | ||
``` | ||
|
||
## Prepare Dataset | ||
|
||
To pre-train on ImageNet, you need to prepare the dataset first. Please refer to the [guide](https://mmclassification.readthedocs.io/en/1.x/user_guides/dataset_prepare.html#imagenet). | ||
|
||
## How to Train | ||
|
||
You can use the classification config in the same way as the detection config. | ||
|
||
For single-GPU training, run: | ||
|
||
```shell | ||
python tools/train.py \ | ||
${CONFIG_FILE} \ | ||
[optional arguments] | ||
``` | ||
|
||
For multi-GPU training, run: | ||
|
||
```shell | ||
bash ./tools/dist_train.sh \ | ||
${CONFIG_FILE} \ | ||
${GPU_NUM} \ | ||
[optional arguments] | ||
``` | ||
|
||
More details can be found in [user guides](https://mmdetection.readthedocs.io/en/3.x/user_guides/train.html). | ||
|
||
## Results and Models | ||
|
||
| Model | resolution | Params(M) | Flops(G) | Top-1 (%) | Top-5 (%) | Download | | ||
| :----------: | :--------: | :-------: | :------: | :-------: | :-------: | :-----------------------------------------------------------------------------------------------------------------: | | ||
| CSPNeXt-tiny | 224x224 | 2.73 | 0.339 | 69.44 | 89.45 | [model](https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth) | | ||
| CSPNeXt-s | 224x224 | 4.89 | 0.664 | 74.41 | 92.23 | [model](https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-s_imagenet_600e.pth) | |
67 changes: 67 additions & 0 deletions
67
configs/rtmdet/cspnext_imagenet_pretrain/cspnext-s_8xb256-rsb-a1-600e_in1k.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,67 @@ | ||
_base_ = [ | ||
'mmcls::_base_/datasets/imagenet_bs256_rsb_a12.py', | ||
'mmcls::_base_/schedules/imagenet_bs2048_rsb.py', | ||
'mmcls::_base_/default_runtime.py' | ||
] | ||
|
||
custom_imports = dict( | ||
imports=['mmdet.models', 'mmyolo.models'], allow_failed_imports=False) | ||
|
||
model = dict( | ||
type='ImageClassifier', | ||
backbone=dict( | ||
type='mmyolo.CSPNeXt', | ||
arch='P5', | ||
out_indices=(4, ), | ||
expand_ratio=0.5, | ||
deepen_factor=0.33, | ||
widen_factor=0.5, | ||
channel_attention=True, | ||
norm_cfg=dict(type='BN'), | ||
act_cfg=dict(type='mmyolo.SiLU')), | ||
neck=dict(type='GlobalAveragePooling'), | ||
head=dict( | ||
type='LinearClsHead', | ||
num_classes=1000, | ||
in_channels=512, | ||
loss=dict( | ||
type='LabelSmoothLoss', | ||
label_smooth_val=0.1, | ||
mode='original', | ||
loss_weight=1.0), | ||
topk=(1, 5)), | ||
train_cfg=dict(augments=[ | ||
dict(type='Mixup', alpha=0.2, num_classes=1000), | ||
dict(type='CutMix', alpha=1.0, num_classes=1000) | ||
])) | ||
|
||
# dataset settings | ||
train_dataloader = dict(sampler=dict(type='RepeatAugSampler', shuffle=True)) | ||
|
||
# schedule settings | ||
optim_wrapper = dict( | ||
optimizer=dict(weight_decay=0.01), | ||
paramwise_cfg=dict(bias_decay_mult=0., norm_decay_mult=0.), | ||
) | ||
|
||
param_scheduler = [ | ||
# warm up learning rate scheduler | ||
dict( | ||
type='LinearLR', | ||
start_factor=0.0001, | ||
by_epoch=True, | ||
begin=0, | ||
end=5, | ||
# update by iter | ||
convert_to_iter_based=True), | ||
# main learning rate scheduler | ||
dict( | ||
type='CosineAnnealingLR', | ||
T_max=595, | ||
eta_min=1.0e-6, | ||
by_epoch=True, | ||
begin=5, | ||
end=600) | ||
] | ||
|
||
train_cfg = dict(by_epoch=True, max_epochs=600) |
5 changes: 5 additions & 0 deletions
5
configs/rtmdet/cspnext_imagenet_pretrain/cspnext-tiny_8xb256-rsb-a1-600e_in1k.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,5 @@ | ||
_base_ = './cspnext-s_8xb256-rsb-a1-600e_in1k.py' | ||
|
||
model = dict( | ||
backbone=dict(deepen_factor=0.167, widen_factor=0.375), | ||
head=dict(in_channels=384)) |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,68 @@ | ||
Collections: | ||
- Name: RTMDet | ||
Metadata: | ||
Training Data: COCO | ||
Training Techniques: | ||
- AdamW | ||
- Flat Cosine Annealing | ||
Training Resources: 8x A100 GPUs | ||
Architecture: | ||
- CSPNeXt | ||
- CSPNeXtPAFPN | ||
README: configs/rtmdet/README.md | ||
Code: | ||
URL: https://github.com/open-mmlab/mmyolo/blob/main/mmyolo/models/detectors/yolo_detector.py#L12 | ||
Version: v0.1.1 | ||
|
||
Models: | ||
- Name: rtmdet_tiny_syncbn_8xb32-300e_coco | ||
In Collection: RTMDet | ||
Config: configs/rtmdet/rtmdet_tiny_syncbn_8xb32-300e_coco.py | ||
Metadata: | ||
Training Memory (GB): 7.6 | ||
Epochs: 300 | ||
Results: | ||
- Task: Object Detection | ||
Dataset: COCO | ||
Metrics: | ||
box AP: 40.9 | ||
Weights: https://download.openmmlab.com/mmyolo/v0/rtmdet/rtmdet_tiny_syncbn_8xb32-300e_coco/rtmdet_tiny_syncbn_8xb32-300e_coco_20220902_112414-259f3241.pth | ||
|
||
- Name: rtmdet_s_syncbn_8xb32-300e_coco | ||
In Collection: RTMDet | ||
Config: configs/rtmdet/rtmdet_s_syncbn_8xb32-300e_coco.py | ||
Metadata: | ||
Training Memory (GB): 7.6 | ||
Epochs: 300 | ||
Results: | ||
- Task: Object Detection | ||
Dataset: COCO | ||
Metrics: | ||
box AP: 44.5 | ||
Weights: https://download.openmmlab.com/mmyolo/v0/rtmdet/rtmdet_s_syncbn_8xb32-300e_coco/rtmdet_s_syncbn_8xb32-300e_coco_20220905_161602-fd1cacb9.pth | ||
|
||
- Name: rtmdet_m_syncbn_8xb32-300e_coco | ||
In Collection: RTMDet | ||
Config: configs/rtmdet/rtmdet_m_syncbn_8xb32-300e_coco.py | ||
Metadata: | ||
Training Memory (GB): 7.6 | ||
Epochs: 300 | ||
Results: | ||
- Task: Object Detection | ||
Dataset: COCO | ||
Metrics: | ||
box AP: 49.1 | ||
Weights: https://download.openmmlab.com/mmyolo/v0/rtmdet/rtmdet_m_syncbn_8xb32-300e_coco/rtmdet_m_syncbn_8xb32-300e_coco_20220924_132959-d9f2e90d.pth | ||
|
||
- Name: rtmdet_l_syncbn_8xb32-300e_coco | ||
In Collection: RTMDet | ||
Config: configs/rtmdet/rtmdet_l_syncbn_8xb32-300e_coco.py | ||
Metadata: | ||
Training Memory (GB): 7.6 | ||
Epochs: 300 | ||
Results: | ||
- Task: Object Detection | ||
Dataset: COCO | ||
Metrics: | ||
box AP: 51.3 | ||
Weights: https://download.openmmlab.com/mmyolo/v0/rtmdet/rtmdet_l_syncbn_8xb32-300e_coco/rtmdet_l_syncbn_8xb32-300e_coco_20220926_150401-40c754b5.pth |
Oops, something went wrong.