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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 | |