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三洋三洋
2024-02-12 11:40:51 +00:00
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README.md
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@@ -1,6 +1,6 @@
<div align="center">
<h1><img src="./assets/fire.svg" width=30, height=30>
𝐓𝐞𝐱𝐓𝐞𝐥𝐥𝐞𝐫 <img src="./assets/fire.svg" width=30, height=30> </h1>
𝚃𝚎𝚡𝚃𝚎𝚕𝚕𝚎𝚛 <img src="./assets/fire.svg" width=30, height=30> </h1>
<p align="center">
English | <a href="./assests/README_zh.md">中文版本</a>
@@ -23,7 +23,7 @@ python=3.10
pytorch
> Note: CUDA version >= 12.0 have been fully tested.
> Note: Only CUDA version >= 12.0 have been fully tested, so we recommend using CUDA version>=12.0
## Getting Started
@@ -33,7 +33,7 @@ pytorch
git clone https://github.com/OleehyO/TexTeller
```
2. After [pytorch installation](https://pytorch.org/get-started), install the required packages:
2. After [pytorch installation](https://pytorch.org/get-started/locally/#start-locally), install the required packages:
```bash
pip install -r requirements.txt
@@ -47,7 +47,7 @@ pytorch
#+e.g. python inference.py -img "./img.jpg" -cuda
```
> chekpoints will be downloaded in your first run.
> Checkpoints will be downloaded in your first run.
## Web Demo
@@ -57,9 +57,9 @@ You can also run the web demo by navigating to the `TexTeller/src` directory and
./start_web.sh
```
Then go to `http://localhost:8000` in your browser to run TexTeller in the web.
Then go to `http://localhost:8501` in your browser to run TexTeller in the web.
> You can change the default settings in start_web.sh, such as inference with GPU(e.g. `USE_CUDA=True`) or increase the number of beams(e.g. `NUM_BEAM=3`) for higher accuracy.
> You can change the default settings in `start_web.sh`, such as inference with GPU(e.g. `USE_CUDA=True`) or increase the number of beams(e.g. `NUM_BEAM=3`) for higher accuracy.
## API
@@ -82,13 +82,13 @@ You can pass the following arguments to the `serve.py` script to get custom infe
| `--ncpu_per_replica` | Number of CPU cores to use per replica, *default is 1*. |
| `--ngpu_per_replica` | Number of GPUs to use per replica, *default is 1*. You can set this to 0~1 to run multiple replicas on a single GPU(if --num_replicas 2, --ngpu_per_replica 0.7, then 2 gpus are required) |
> Client demo can be found in `TexTeller/client/demo.py`.
> Client demo can be found in `TexTeller/client/demo.py`, you can refer to `demo.py` to send requests to the server.
## Training
### Dataset
We provide a dataset example in `TexTeller/src/models/ocr_model/train/dataset`, and you can place your own images in the `images` directory and annotate the corresponding formula for each image in `formulas.jsonl`
We provide a dataset example in `TexTeller/src/models/ocr_model/train/dataset`, and you can place your own images in the `images` directory and annotate the corresponding formula for each image in `formulas.jsonl`.
After the dataset is ready, you should **change the `DIR_URL` variable** in `.../dataset/loader.py` to the path of your dataset.
@@ -96,7 +96,7 @@ After the dataset is ready, you should **change the `DIR_URL` variable** in `...
If you are using a different dataset, you may need to retrain the tokenizer to match your specific vocabulary. After setting up the dataset, you can do this by:
1. Change the line `new_tokenizer.save_pretrained('./your_dir_name')` in `TexTeller/src/models/ocr_model/tokenizer/train.py` to your desired output directory name.`
1. Change the line `new_tokenizer.save_pretrained('./your_dir_name')` in `TexTeller/src/models/ocr_model/tokenizer/train.py` to your desired output directory name.
> To use a different vocabulary size, you should modify the `VOCAB_SIZE` parameter in the `TexTeller/src/models/globals.py`.
2. Running the following command **under `TexTeller/src` directory**:
@@ -114,6 +114,7 @@ python -m models.ocr_model.train.train
```
You can set your own tokenizer and checkpoint path(or fine-tune the default model checkpoint if you don't use your own tokenizer while keeping the same model architecture) in `TexTeller/src/models/ocr_model/train/train.py`.
> Please refer to `train.py` for more details.
Model architecture and training hyperparameters can be adjusted in `TexTeller/src/globals.py` and `TexTeller/src/models/ocr_model/train/train_args.py`.