# apsis-net
Apsis-net is a Bengali language ocr system for Printed Documents developed at [Apsis Solutions limited](https://apsissolutions.com/)
The full system is focused on bengali text recognition only
* Text recognition:
* Bangla Text : ApsisNet
* ApsisNet is a model developed at Apsis Solutions Limited.
* It is used by [bbOCR](https://github.com/BengaliAI/bbocr/blob/dev/modules.md) as the recognition model
* ApsisNet is found to be the best among other available recognition models (such as tesseract and easyOCR) in the linked [paper](https://arxiv.org/abs/2308.10647)
# **Installation**
## **As module/pypi package**
### **cpu installation**
```bash
pip install apsisnet
```
### **gpu installation**
It is recommended to use conda environment . Specially for GPU.
* **installing cudatoolkit and cudnn**:
```bash
conda install cudatoolkit
conda install cudnn
```
* **installing packages**
```bash
pip install apsisnet
```
* **exporting environment variables**
```bash
mkdir -p $CONDA_PREFIX/etc/conda/activate.d
echo 'export LD_LIBRARY_PATH=$CUDNN_PATH/lib:$CONDA_PREFIX/lib/:$LD_LIBRARY_PATH' >> $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh
```
## **Building from source : Linux/Ubuntu**
It is recommended to use conda environment .
* **clone the repository** :
```bash
git clone https://github.com/mnansary/apsisnet.git
cd apsisnet
```
* **create a conda environment**:
```bash
conda create -n apsisnet python=3.9
```
* **activate conda environment**:
```bash
conda activate apsisnet
```
* **cpu installation** :
```bash
bash install.sh cpu
```
* **gpu installation** :
```bash
bash install.sh gpu
```
# Useage
## Apsisnet : Bangla Recognizer
* useage
```python
from apsisnet import ApsisNet
bnocr=ApsisNet()
bnocr.infer(crops)
```
* docstring for ```ApsisNet.infer```
```python
"""
Perform inference on image crops.
Args:
crops (list[np.ndarray]): List of image crops.
batch_size (int): Batch size for inference (default: 32).
normalize_unicode (bool): Flag to normalize unicode (default: True).
Returns:
list[str]: List of inferred texts.
"""
```
**check ```useage/useage.ipynb``` for examples**
**TESTED GPU INFERENCE SERVER CONFIG**
```python
OS : Ubuntu 20.04.6 LTS
Memory : 62.4 GiB
Processor : Intel® Xeon(R) Silver 4214R CPU @ 2.40GHz × 24
Graphics : NVIDIA RTX A6000/PCIe/SSE2
Gnome : 3.36.8
```
# License
Contents of this repository are restricted to non-commercial research purposes only under the [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/).
<a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png" /></a>
25-04-2024
----------------
* changed onnxruntime-gpu version
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"description": "# apsis-net\n \n\nApsis-net is a Bengali language ocr system for Printed Documents developed at [Apsis Solutions limited](https://apsissolutions.com/)\n\nThe full system is focused on bengali text recognition only \n* Text recognition:\n * Bangla Text : ApsisNet \n * ApsisNet is a model developed at Apsis Solutions Limited. \n * It is used by [bbOCR](https://github.com/BengaliAI/bbocr/blob/dev/modules.md) as the recognition model \n * ApsisNet is found to be the best among other available recognition models (such as tesseract and easyOCR) in the linked [paper](https://arxiv.org/abs/2308.10647)\n\n\n# **Installation**\n\n\n## **As module/pypi package**\n### **cpu installation**\n\n```bash\npip install apsisnet\n```\n\n### **gpu installation**\n\nIt is recommended to use conda environment . Specially for GPU.\n\n* **installing cudatoolkit and cudnn**: \n\n```bash\nconda install cudatoolkit\nconda install cudnn\n```\n\n* **installing packages**\n\n```bash\npip install apsisnet\n```\n\n* **exporting environment variables**\n\n```bash\nmkdir -p $CONDA_PREFIX/etc/conda/activate.d\necho 'export LD_LIBRARY_PATH=$CUDNN_PATH/lib:$CONDA_PREFIX/lib/:$LD_LIBRARY_PATH' >> $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh\n```\n\n## **Building from source : Linux/Ubuntu**\nIt is recommended to use conda environment .\n\n* **clone the repository** : \n```bash\ngit clone https://github.com/mnansary/apsisnet.git\ncd apsisnet\n```\n\n\n* **create a conda environment**: \n\n```bash\nconda create -n apsisnet python=3.9\n```\n\n* **activate conda environment**: \n\n```bash\nconda activate apsisnet\n\n```\n* **cpu installation** :\n\n```bash\nbash install.sh cpu\n``` \n* **gpu installation** :\n \n```bash\nbash install.sh gpu\n``` \n\n# Useage\n\n\n## Apsisnet : Bangla Recognizer\n\n* useage\n```python\nfrom apsisnet import ApsisNet\nbnocr=ApsisNet()\nbnocr.infer(crops)\n```\n* docstring for ```ApsisNet.infer```\n\n```python\n\"\"\"\nPerform inference on image crops.\n\nArgs:\n crops (list[np.ndarray]): List of image crops.\n batch_size (int): Batch size for inference (default: 32).\n normalize_unicode (bool): Flag to normalize unicode (default: True).\n\nReturns:\n list[str]: List of inferred texts.\n\"\"\"\n```\n\n\n**check ```useage/useage.ipynb``` for examples**\n\n\n**TESTED GPU INFERENCE SERVER CONFIG** \n\n```python\nOS : Ubuntu 20.04.6 LTS \nMemory : 62.4\u00a0GiB \nProcessor : Intel\u00ae Xeon(R) Silver 4214R CPU @ 2.40GHz \u00d7 24 \nGraphics : NVIDIA RTX A6000/PCIe/SSE2\nGnome : 3.36.8\n```\n# License\nContents of this repository are restricted to non-commercial research purposes only under the [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/). \n\n<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-sa/4.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png\" /></a>\n\n\n\n25-04-2024\n----------------\n* changed onnxruntime-gpu version\n",
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