| .. _algorithm_formula_recognition: | |
| ============ | |
| Formula Recognition Algorithm | |
| ============ | |
| Introduction | |
| ================= | |
| Formula detection involves recognizing the content of a given input formula image and converting it to ``LaTeX`` format. | |
| Model Usage | |
| ================= | |
| With the environment properly configured, you can run the layout detection algorithm script by executing ``scripts/formula_recognition.py``. | |
| .. code:: shell | |
| $ python scripts/formula_recognition.py --config configs/formula_recognition.yaml | |
| Model Configuration | |
| ----------------- | |
| .. code:: yaml | |
| inputs: assets/demo/formula_recognition | |
| outputs: outputs/formula_recognition | |
| tasks: | |
| formula_recognition: | |
| model: formula_recognition_unimernet | |
| model_config: | |
| cfg_path: pdf_extract_kit/configs/unimernet.yaml | |
| model_path: models/MFR/unimernet_tiny | |
| visualize: False | |
| - inputs/outputs: Define the input file path and the directory for LaTeX prediction results, respectively. | |
| - tasks: Define the task type, currently only containing a formula recognition task. | |
| - model: Define the specific model type: Currently, only the `UniMERNet <https://github.com/opendatalab/UniMERNet>`_ formula recognition model is provided. | |
| - model_config: Define the model configuration. | |
| - cfg_path: Path to the UniMERNet configuration file. | |
| - model_path: Path to the model weights. | |
| - visualize: Whether to visualize the model results. Visualized results will be saved in the outputs directory. | |
| Support for Diverse Inputs | |
| ----------------- | |
| The formula detection script in PDF-Extract-Kit supports ``single formula images`` and ``document images with corresponding formula regions``. | |
| Viewing Visualization Results | |
| ----------------- | |
| When the visualize setting in the config file is set to True, ``LaTeX`` prediction results will be saved in the outputs directory. |