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https://github.com/eurus-holmes/chabcnet
[CHABCNet] ABCNet on the Chinese dataset, building on Detectron2 (Facebook AI Research)
https://github.com/eurus-holmes/chabcnet
chinese-dataset detectron2 icdar2019 rects text-detection-recognition text-spotting
Last synced: 2 days ago
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[CHABCNet] ABCNet on the Chinese dataset, building on Detectron2 (Facebook AI Research)
- Host: GitHub
- URL: https://github.com/eurus-holmes/chabcnet
- Owner: Eurus-Holmes
- License: bsd-2-clause
- Created: 2019-11-09T04:14:58.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2023-10-03T23:44:15.000Z (about 1 year ago)
- Last Synced: 2023-10-20T19:44:45.569Z (about 1 year ago)
- Topics: chinese-dataset, detectron2, icdar2019, rects, text-detection-recognition, text-spotting
- Language: Python
- Homepage:
- Size: 3.32 MB
- Stars: 11
- Watchers: 2
- Forks: 0
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# CHABCNet
> [ABCNet](https://github.com/aim-uofa/AdelaiDet) on the Chinese dataset.
## Installation
```shell script
git clone https://github.com/aim-uofa/AdelaiDet.git
cd AdelaiDet
python -m venv env
source env/bin/activate
pip install --upgrade pip
```
First install Detectron2 following the official guide: [INSTALL.md](https://github.com/facebookresearch/detectron2/blob/master/INSTALL.md). Then build AdelaiDet with:
```shell script
pip install -U torch==1.5 torchvision==0.6 -f https://download.pytorch.org/whl/cu101/torch_stable.html
pip install opencv-python
pip install cython pyyaml==5.1
pip install -U 'git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI'
pip install detectron2==0.1.3 -f https://dl.fbaipublicfiles.com/detectron2/wheels/cu101/torch1.5/index.html
python setup.py build develop
```
Some projects may require special setup, please follow their own `README.md` in [configs](configs).
## Quick Start
### Inference with our trained Models
1. Select the model and config file above, for example, `configs/BAText/CTW1500/attn_R_50.yaml`.
2. Run the demo with
```
wget -O ctw1500_attn_R_50.pth https://universityofadelaide.box.com/shared/static/1bqpg9hijtn2rcooqjpffateguh9eeme.pth
python demo/demo.py \
--config-file configs/BAText/CTW1500/attn_R_50.yaml \
--input ./input/ \
--output ./output/ \
--opts MODEL.WEIGHTS ctw1500_attn_R_50.pth
```
or
```
wget -O tt_attn_R_50.pth https://cloudstor.aarnet.edu.au/plus/s/t2EFYGxNpKPUqhc/download
python demo/demo.py \
--config-file configs/BAText/TotalText/attn_R_50.yaml \
--input ./input/ \
--output ./output/ \
--opts MODEL.WEIGHTS tt_attn_R_50.pth
```
### Train Your Own Models
1. Step one: [Data processing](https://github.com/Eurus-Holmes/CHABCNet/tree/master/data_processing)
2. Step two: Put the ReCTS dataset to `dataset` folder
```
ReCTS:
.
├── images
│ ├── 000001.jpg
│ ├── 000002.jpg
├── annotations
│ ├── train.json
```
3. Step three: specify train img and annotations in `adet/data/builtin.py`:
Add the ReCTS dataset:
```
_PREDEFINED_SPLITS_TEXT = {
"totaltext_train": ("totaltext/train_images", "totaltext/train.json"),
"totaltext_val": ("totaltext/test_images", "totaltext/test.json"),
"ctw1500_word_train": ("CTW1500/ctwtrain_text_image", "CTW1500/annotations/train_ctw1500_maxlen100_v2.json"),
"ctw1500_word_test": ("CTW1500/ctwtest_text_image","CTW1500/annotations/test_ctw1500_maxlen100.json"),
"syntext1_train": ("syntext1/images", "syntext1/annotations/train.json"),
"syntext2_train": ("syntext2/images", "syntext2/annotations/train.json"),
"mltbezier_word_train": ("mlt2017/images","mlt2017/annotations/train.json"),
"ReCTS_train": ("ReCTS/train_images","ReCTS/annotations/train.json"),
"ReCTS_test": ("ReCTS/test_images","ReCTS/annotations/test.json"),
}
```
4. Step four: specify train config in `configs/BAText/TotalText/Base-TotalText.yaml`:
Add the ReCTS dataset:
```
DATASETS:
TRAIN: ("ReCTS_train",)
TEST: ("ReCTS_test",)
```
5. Step five: run
`OMP_NUM_THREADS=1 python tools/train_net2.py --config-file configs/BAText/CTW1500/attn_R_50.yaml --num-gpus 1`
`OMP_NUM_THREADS=1 python tools/train_net.py --config-file configs/BAText/TotalText/attn_R_50.yaml --num-gpus 1`
`OMP_NUM_THREADS=1 python tools/train_net2.py --config-file configs/BAText/Pretrain/attn_R_50.yaml --num-gpus 1`