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| from ocr.inference import OCRInference | |
| import os | |
| # Determine the absolute path to the model | |
| # Assuming the script is run from the root of draft_computation | |
| # or that the ocr_placeholder.py is called in a way that its parent directory is in sys.path | |
| # For direct import from draft_computation_app, the path needs to be relative to the project root. | |
| # The model path in ocr/inference.py is "./ocr_model_output/checkpoint-441" | |
| # Relative to draft_computation_app, this would be "../ocr/ocr_model_output/checkpoint-441" | |
| # Let's make it absolute for robustness. | |
| # Get the directory of the current script (ocr_placeholder.py) | |
| current_script_dir = os.path.dirname(os.path.abspath(__file__)) | |
| # Navigate up to the project root (c:\Users\dev-n\OneDrive\Desktop\draft_computation) | |
| project_root = os.path.abspath(os.path.join(current_script_dir, "..")) | |
| # Construct the absolute path to the OCR model | |
| OCR_MODEL_PATH = os.path.join(project_root, "ocr", "ocr_model_output", "checkpoint-441") | |
| print(f"OCR Model Path: {OCR_MODEL_PATH}") | |
| # Initialize the OCRInference engine globally or as a singleton if preferred | |
| # For simplicity, initializing here. Consider lazy loading or a proper singleton pattern for production. | |
| ocr_engine = OCRInference(model_path=OCR_MODEL_PATH) | |
| def perform_ocr(image_input): | |
| """ | |
| Performs OCR using the integrated OCRInference engine. | |
| Args: | |
| image_input: Path to the image file or a NumPy array representing the image. | |
| Returns: | |
| The predicted text from the image. | |
| """ | |
| return ocr_engine.perform_inference(image_input) | |