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| import layoutparser as lp | |
| import pytesseract | |
| import json | |
| from pdf2image import convert_from_path | |
| from PIL import Image | |
| def convert_pdf_to_images(pdf_path): | |
| return convert_from_path(pdf_path) | |
| def analyze_layout(image): | |
| model = lp.Detectron2LayoutModel( | |
| config_path='lp://PubLayNet/faster_rcnn_R_50_FPN_3x/config', | |
| extra_config=["MODEL.ROI_HEADS.SCORE_THRESH_TEST", 0.8], | |
| label_map={0: "Text", 1: "Title", 2: "List", 3: "Table", 4: "Figure"} | |
| ) | |
| layout = model.detect(image) | |
| return layout | |
| def extract_text_from_blocks(image, layout): | |
| blocks = [] | |
| for block in layout: | |
| segment_image = block.crop_image(image) | |
| text = pytesseract.image_to_string(segment_image) | |
| blocks.append({ | |
| "type": block.type, | |
| "text": text.strip(), | |
| "coordinates": block.coordinates | |
| }) | |
| return blocks | |
| def extract_key_values(blocks): | |
| data = {} | |
| for block in blocks: | |
| text = block["text"] | |
| if "invoice" in text.lower(): | |
| data["invoice_number"] = text | |
| elif "total" in text.lower(): | |
| data["total_amount"] = text | |
| elif "customer" in text.lower(): | |
| data["customer_name"] = text | |
| return data | |