Tested python version: 3.10.12,3.9.16,3.8.16
install the necessary python packages with the following command:
pip install -r requirements.txt
Use jpg's or png's as input images, place them all in a folder (use the "Input" folder or define your own later)
Run the program with python as following:
python predict.py <Input directory>
Or use the predefined input directory:
python predict.py Input
The model output will be placed in the "result" folder, where the output of each seperate image is placed into
a seperate .txt file that has a corresponding name. The inferred text
will be placed as a line in this .txt file. (Note: the files name ends
with _characters if you desire another suffix please change the
variable NAMING in the predict.py file.)
The "Training" folder contains the .ipynb file that was used to train the model on our own dataset. This dataset is available here. This dataset is created on a subset of the IAM dataset along with a script that was used to augment this data. This script is located in the "Augment" folder. The training file runs only with the requirements.txt provided in the "Training" folder.