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[Enchance] batch size information in readme #1778

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24 changes: 12 additions & 12 deletions configs/textdet/dbnet/README.md
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Expand Up @@ -16,24 +16,24 @@ Recently, segmentation-based methods are quite popular in scene text detection,

### SynthText

| Method | Backbone | Training set | #iters | Download |
| :-----------------------------------------------------------------------: | :------: | :----------: | :-----: | :--------------------------------------------------------------------------------------------------: |
| [DBNet_r18](/configs/textdet/dbnet/dbnet_resnet18_fpnc_100k_synthtext.py) | ResNet18 | SynthText | 100,000 | [model](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet18_fpnc_100k_synthtext/dbnet_resnet18_fpnc_100k_synthtext-2e9bf392.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet18_fpnc_100k_synthtext/20221214_150351.log) |
| Method | Backbone | Training set | #iters | Download | Batch Size |
| :-----------------------------------------------------------------------: | :------: | :----------: | :-----: | :----------------------------------------------------------------------------------------: | :--------: |
| [DBNet_r18](/configs/textdet/dbnet/dbnet_resnet18_fpnc_100k_synthtext.py) | ResNet18 | SynthText | 100,000 | [model](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet18_fpnc_100k_synthtext/dbnet_resnet18_fpnc_100k_synthtext-2e9bf392.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet18_fpnc_100k_synthtext/20221214_150351.log) | 1xb16 |
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Need to change the batch size format to avoid confusion for beginners:
1xb16 -> 1 x 16.

Same for others.


### ICDAR2015

| Method | Backbone | Pretrained Model | Training set | Test set | #epochs | Test size | Precision | Recall | Hmean | Download |
| :----------------------------: | :------------------------------: | :--------------------------------------: | :-------------: | :------------: | :-----: | :-------: | :-------: | :----: | :----: | :------------------------------: |
| [DBNet_r18](/configs/textdet/dbnet/dbnet_resnet18_fpnc_1200e_icdar2015.py) | ResNet18 | - | ICDAR2015 Train | ICDAR2015 Test | 1200 | 736 | 0.8853 | 0.7583 | 0.8169 | [model](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet18_fpnc_1200e_icdar2015/dbnet_resnet18_fpnc_1200e_icdar2015_20220825_221614-7c0e94f2.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet18_fpnc_1200e_icdar2015/20220825_221614.log) |
| [DBNet_r50](/configs/textdet/dbnet/dbnet_resnet50_1200e_icdar2015.py) | ResNet50 | - | ICDAR2015 Train | ICDAR2015 Test | 1200 | 1024 | 0.8744 | 0.8276 | 0.8504 | [model](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet50_1200e_icdar2015/dbnet_resnet50_1200e_icdar2015_20221102_115917-54f50589.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet50_1200e_icdar2015/20221102_115917.log) |
| [DBNet_r50dcn](/configs/textdet/dbnet/dbnet_resnet50-dcnv2_fpnc_1200e_icdar2015.py) | ResNet50-DCN | [Synthtext](https://download.openmmlab.com/mmocr/textdet/dbnet/tmp_1.0_pretrain/dbnet_r50dcnv2_fpnc_sbn_2e_synthtext_20210325-ed322016.pth) | ICDAR2015 Train | ICDAR2015 Test | 1200 | 1024 | 0.8784 | 0.8315 | 0.8543 | [model](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet50-dcnv2_fpnc_1200e_icdar2015/dbnet_resnet50-dcnv2_fpnc_1200e_icdar2015_20220828_124917-452c443c.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet50-dcnv2_fpnc_1200e_icdar2015/20220828_124917.log) |
| [DBNet_r50-oclip](/configs/textdet/dbnet/dbnet_resnet50-oclip_1200e_icdar2015.py) | [ResNet50-oCLIP](https://download.openmmlab.com/mmocr/backbone/resnet50-oclip-7ba0c533.pth) | - | ICDAR2015 Train | ICDAR2015 Test | 1200 | 1024 | 0.9052 | 0.8272 | 0.8644 | [model](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet50-oclip_1200e_icdar2015/dbnet_resnet50-oclip_1200e_icdar2015_20221102_115917-bde8c87a.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet50-oclip_1200e_icdar2015/20221102_115917.log) |
| Method | Backbone | Pretrained Model | Training set | Test set | #epochs | Test size | Precision | Recall | Hmean | Download | Batch Size |
| :-------------------------: | :---------------------------: | :------------------------------------: | :-------------: | :------------: | :-----: | :-------: | :-------: | :----: | :----: | :----------------------------: | :--------: |
| [DBNet_r18](/configs/textdet/dbnet/dbnet_resnet18_fpnc_1200e_icdar2015.py) | ResNet18 | - | ICDAR2015 Train | ICDAR2015 Test | 1200 | 736 | 0.8853 | 0.7583 | 0.8169 | [model](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet18_fpnc_1200e_icdar2015/dbnet_resnet18_fpnc_1200e_icdar2015_20220825_221614-7c0e94f2.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet18_fpnc_1200e_icdar2015/20220825_221614.log) | 1xb16 |
| [DBNet_r50](/configs/textdet/dbnet/dbnet_resnet50_1200e_icdar2015.py) | ResNet50 | - | ICDAR2015 Train | ICDAR2015 Test | 1200 | 1024 | 0.8744 | 0.8276 | 0.8504 | [model](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet50_1200e_icdar2015/dbnet_resnet50_1200e_icdar2015_20221102_115917-54f50589.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet50_1200e_icdar2015/20221102_115917.log) | 1xb16 |
| [DBNet_r50dcn](/configs/textdet/dbnet/dbnet_resnet50-dcnv2_fpnc_1200e_icdar2015.py) | ResNet50-DCN | [Synthtext](https://download.openmmlab.com/mmocr/textdet/dbnet/tmp_1.0_pretrain/dbnet_r50dcnv2_fpnc_sbn_2e_synthtext_20210325-ed322016.pth) | ICDAR2015 Train | ICDAR2015 Test | 1200 | 1024 | 0.8784 | 0.8315 | 0.8543 | [model](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet50-dcnv2_fpnc_1200e_icdar2015/dbnet_resnet50-dcnv2_fpnc_1200e_icdar2015_20220828_124917-452c443c.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet50-dcnv2_fpnc_1200e_icdar2015/20220828_124917.log) | 1xb16 |
| [DBNet_r50-oclip](/configs/textdet/dbnet/dbnet_resnet50-oclip_1200e_icdar2015.py) | [ResNet50-oCLIP](https://download.openmmlab.com/mmocr/backbone/resnet50-oclip-7ba0c533.pth) | - | ICDAR2015 Train | ICDAR2015 Test | 1200 | 1024 | 0.9052 | 0.8272 | 0.8644 | [model](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet50-oclip_1200e_icdar2015/dbnet_resnet50-oclip_1200e_icdar2015_20221102_115917-bde8c87a.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet50-oclip_1200e_icdar2015/20221102_115917.log) | 1xb16 |

### Total Text

| Method | Backbone | Pretrained Model | Training set | Test set | #epochs | Test size | Precision | Recall | Hmean | Download |
| :----------------------------------------------------: | :------: | :--------------: | :-------------: | :------------: | :-----: | :-------: | :-------: | :----: | :----: | :------------------------------------------------------: |
| [DBNet_r18](/configs/textdet/dbnet/dbnet_resnet18_fpnc_1200e_totaltext.py) | ResNet18 | - | Totaltext Train | Totaltext Test | 1200 | 736 | 0.8640 | 0.7770 | 0.8182 | [model](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet18_fpnc_1200e_totaltext/dbnet_resnet18_fpnc_1200e_totaltext-3ed3233c.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet18_fpnc_1200e_totaltext/20221219_201038.log) |
| Method | Backbone | Pretrained Model | Training set | Test set | #epochs | Test size | Precision | Recall | Hmean | Download | Batch Size |
| :-----------------------------------------------: | :------: | :--------------: | :-------------: | :------------: | :-----: | :-------: | :-------: | :----: | :----: | :-------------------------------------------------: | :--------: |
| [DBNet_r18](/configs/textdet/dbnet/dbnet_resnet18_fpnc_1200e_totaltext.py) | ResNet18 | - | Totaltext Train | Totaltext Test | 1200 | 736 | 0.8640 | 0.7770 | 0.8182 | [model](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet18_fpnc_1200e_totaltext/dbnet_resnet18_fpnc_1200e_totaltext-3ed3233c.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnet_resnet18_fpnc_1200e_totaltext/20221219_201038.log) | 1xb16 |

## Citation

Expand Down
16 changes: 8 additions & 8 deletions configs/textdet/dbnetpp/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -16,17 +16,17 @@ Recently, segmentation-based scene text detection methods have drawn extensive a

### SynthText

| Method | BackBone | Training set | #iters | Download |
| :--------------------------------------------------------------------------------: | :------------: | :----------: | :-----: | :-----------------------------------------------------------------------------------: |
| [DBNetpp_r50dcn](/configs/textdet/dbnetpp/dbnetpp_resnet50-dcnv2_fpnc_100k_synthtext.py) | ResNet50-dcnv2 | SynthText | 100,000 | [model](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50-dcnv2_fpnc_100k_synthtext/dbnetpp_resnet50-dcnv2_fpnc_100k_synthtext-00f0a80b.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50-dcnv2_fpnc_100k_synthtext/20221215_013531.log) |
| Method | BackBone | Training set | #iters | Download | Batch Size |
| :---------------------------------------------------------------------------: | :------------: | :----------: | :-----: | :------------------------------------------------------------------------------: | :--------: |
| [DBNetpp_r50dcn](/configs/textdet/dbnetpp/dbnetpp_resnet50-dcnv2_fpnc_100k_synthtext.py) | ResNet50-dcnv2 | SynthText | 100,000 | [model](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50-dcnv2_fpnc_100k_synthtext/dbnetpp_resnet50-dcnv2_fpnc_100k_synthtext-00f0a80b.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50-dcnv2_fpnc_100k_synthtext/20221215_013531.log) | 1xb16 |

### ICDAR2015

| Method | BackBone | Pretrained Model | Training set | Test set | #epochs | Test size | Precision | Recall | Hmean | Download |
| :----------------------------: | :------------------------------: | :--------------------------------------: | :-------------: | :------------: | :-----: | :-------: | :-------: | :----: | :----: | :------------------------------: |
| [DBNetpp_r50](/configs/textdet/dbnetpp/dbnetpp_resnet50_fpnc_1200e_icdar2015.py) | ResNet50 | - | ICDAR2015 Train | ICDAR2015 Test | 1200 | 1024 | 0.9079 | 0.8209 | 0.8622 | [model](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50_fpnc_1200e_icdar2015/dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550-013730aa.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50_fpnc_1200e_icdar2015/20221025_185550.log) |
| [DBNetpp_r50dcn](/configs/textdet/dbnetpp/dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015.py) | ResNet50-dcnv2 | [Synthtext](/configs/textdet/dbnetpp/dbnetpp_resnet50-dcnv2_fpnc_100k_synthtext.py) ([model](https://download.openmmlab.com/mmocr/textdet/dbnetpp/tmp_1.0_pretrain/dbnetpp_r50dcnv2_fpnc_100k_iter_synthtext-20220502-352fec8a.pth)) | ICDAR2015 Train | ICDAR2015 Test | 1200 | 1024 | 0.9116 | 0.8291 | 0.8684 | [model](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015/dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108-f289bd20.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015/20220829_230108.log) |
| [DBNetpp_r50-oclip](/configs/textdet/dbnetpp/dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015.py) | [ResNet50-oCLIP](https://download.openmmlab.com/mmocr/backbone/resnet50-oclip-7ba0c533.pth) | - | ICDAR2015 Train | ICDAR2015 Test | 1200 | 1024 | 0.9174 | 0.8609 | 0.8882 | [model](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015/dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139-4ecb39ac.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015/20221101_124139.log) |
| Method | BackBone | Pretrained Model | Training set | Test set | #epochs | Test size | Precision | Recall | Hmean | Download | Batch Size |
| :-------------------------: | :---------------------------: | :------------------------------------: | :-------------: | :------------: | :-----: | :-------: | :-------: | :----: | :----: | :----------------------------: | :--------: |
| [DBNetpp_r50](/configs/textdet/dbnetpp/dbnetpp_resnet50_fpnc_1200e_icdar2015.py) | ResNet50 | - | ICDAR2015 Train | ICDAR2015 Test | 1200 | 1024 | 0.9079 | 0.8209 | 0.8622 | [model](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50_fpnc_1200e_icdar2015/dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550-013730aa.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50_fpnc_1200e_icdar2015/20221025_185550.log) | 1xb16 |
| [DBNetpp_r50dcn](/configs/textdet/dbnetpp/dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015.py) | ResNet50-dcnv2 | [Synthtext](/configs/textdet/dbnetpp/dbnetpp_resnet50-dcnv2_fpnc_100k_synthtext.py) ([model](https://download.openmmlab.com/mmocr/textdet/dbnetpp/tmp_1.0_pretrain/dbnetpp_r50dcnv2_fpnc_100k_iter_synthtext-20220502-352fec8a.pth)) | ICDAR2015 Train | ICDAR2015 Test | 1200 | 1024 | 0.9116 | 0.8291 | 0.8684 | [model](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015/dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108-f289bd20.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015/20220829_230108.log) | 1xb16 |
| [DBNetpp_r50-oclip](/configs/textdet/dbnetpp/dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015.py) | [ResNet50-oCLIP](https://download.openmmlab.com/mmocr/backbone/resnet50-oclip-7ba0c533.pth) | - | ICDAR2015 Train | ICDAR2015 Test | 1200 | 1024 | 0.9174 | 0.8609 | 0.8882 | [model](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015/dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139-4ecb39ac.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnetpp/dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015/20221101_124139.log) | 1xb16 |

## Citation

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8 changes: 4 additions & 4 deletions configs/textdet/drrg/README.md
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Expand Up @@ -16,10 +16,10 @@ Arbitrary shape text detection is a challenging task due to the high variety and

### CTW1500

| Method | BackBone | Pretrained Model | Training set | Test set | #epochs | Test size | Precision | Recall | Hmean | Download |
| :-------------------------------------: | :---------------------------------------: | :--------------: | :-----------: | :----------: | :-----: | :-------: | :-------: | :----: | :----: | :----------------------------------------: |
| [DRRG](/configs/textdet/drrg/drrg_resnet50_fpn-unet_1200e_ctw1500.py) | ResNet50 | - | CTW1500 Train | CTW1500 Test | 1200 | 640 | 0.8775 | 0.8179 | 0.8467 | [model](https://download.openmmlab.com/mmocr/textdet/drrg/drrg_resnet50_fpn-unet_1200e_ctw1500/drrg_resnet50_fpn-unet_1200e_ctw1500_20220827_105233-d5c702dd.pth) \\ [log](https://download.openmmlab.com/mmocr/textdet/drrg/drrg_resnet50_fpn-unet_1200e_ctw1500/20220827_105233.log) |
| [DRRG_r50-oclip](/configs/textdet/drrg/drrg_resnet50-oclip_fpn-unet_1200e_ctw1500.py) | [ResNet50-oCLIP](https://download.openmmlab.com/mmocr/backbone/resnet50-oclip-7ba0c533.pth) | - | CTW1500 Train | CTW1500 Test | 1200 | | | | | [model](<>) \\ [log](<>) |
| Method | BackBone | Pretrained Model | Training set | Test set | #epochs | Test size | Precision | Recall | Hmean | Download | Batch Size |
| :----------------------------------: | :------------------------------------: | :--------------: | :-----------: | :----------: | :-----: | :-------: | :-------: | :----: | :----: | :------------------------------------: | :--------: |
| [DRRG](/configs/textdet/drrg/drrg_resnet50_fpn-unet_1200e_ctw1500.py) | ResNet50 | - | CTW1500 Train | CTW1500 Test | 1200 | 640 | 0.8775 | 0.8179 | 0.8467 | [model](https://download.openmmlab.com/mmocr/textdet/drrg/drrg_resnet50_fpn-unet_1200e_ctw1500/drrg_resnet50_fpn-unet_1200e_ctw1500_20220827_105233-d5c702dd.pth) \\ [log](https://download.openmmlab.com/mmocr/textdet/drrg/drrg_resnet50_fpn-unet_1200e_ctw1500/20220827_105233.log) | 4xb4 |
| [DRRG_r50-oclip](/configs/textdet/drrg/drrg_resnet50-oclip_fpn-unet_1200e_ctw1500.py) | [ResNet50-oCLIP](https://download.openmmlab.com/mmocr/backbone/resnet50-oclip-7ba0c533.pth) | - | CTW1500 Train | CTW1500 Test | 1200 | | | | | [model](<>) \\ [log](<>) | |

## Citation

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