Apsis-net is a Bengali language ocr system for Printed Documents developed at Apsis Solutions limited
The full system is focused on bengali text recognition only
- Text recognition:
pip install apsisnet
It is recommended to use conda environment . Specially for GPU.
- installing cudatoolkit and cudnn:
conda install cudatoolkit
conda install cudnn
- installing packages
pip install apsisnet
- exporting environment variables
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
It is recommended to use conda environment .
- clone the repository :
git clone https://github.com/mnansary/apsisnet.git
cd apsisnet
- create a conda environment:
conda create -n apsisnet python=3.9
- activate conda environment:
conda activate apsisnet
- cpu installation :
bash install.sh cpu
- gpu installation :
bash install.sh gpu
- useage
from apsisnet import ApsisNet
bnocr=ApsisNet()
bnocr.infer(crops)
- docstring for
ApsisNet.infer
"""
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
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
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).