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from fastapi import FastAPI, File, UploadFile
import numpy as np
from PIL import Image
from paddleocr import PaddleOCR
from doctr.io import DocumentFile
from doctr.models import ocr_predictor
import io
import os
app = FastAPI()
# Load the doctr OCR model
os.environ['USE_TORCH'] = 'YES'
os.environ['USE_TF'] = 'NO'
ocr_model = ocr_predictor(pretrained=True)
def ocr_with_doctr(file):
text_output = ''
# Load the document
doc = DocumentFile.from_pdf(file)
# Perform OCR
result = ocr_model(doc)
# Extract text from OCR result
for page in result.pages:
for block in page.blocks:
for line in block.lines:
text_output += " ".join([word.value for word in line.words]) + "\n"
return text_output
def ocr_with_paddle(img):
finaltext = ''
ocr = PaddleOCR(lang='en', use_angle_cls=True)
result = ocr.ocr(img)
for i in range(len(result[0])):
text = result[0][i][1][0]
finaltext += ' ' + text
return finaltext
def generate_text_from_image(img):
text_output = ''
text_output = ocr_with_paddle(img)
return text_output
@app.post("/ocr/")
async def perform_ocr(file: UploadFile = File(...)):
file_bytes = await file.read()
if file.filename.endswith('.pdf'):
text_output = ocr_with_doctr(io.BytesIO(file_bytes))
else:
img = np.array(Image.open(io.BytesIO(file_bytes)))
text_output = generate_text_from_image(img)
return {"ocr_text": text_output}
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