app.py

import uvicorn
from fastapi.staticfiles import StaticFiles
import hashlib
from enum import Enum
from fastapi import FastAPI, UploadFile, File
from paddleocr import PaddleOCR, PPStructure, save_structure_res
from PIL import Image
import io
import numpy as np

app = FastAPI(docs_url='/')
use_gpu = False
output_dir = 'output'

class LangEnum(str, Enum):
    ch = "ch"
    en = "en"

# cache with ocr
ocr_cache = {}

# get ocr ins
def get_ocr(lang, use_gpu=False):
    if not ocr_cache.get(lang):
        ocr_cache[lang] = PaddleOCR(use_angle_cls=True, lang=lang, use_gpu=use_gpu)
    
    return ocr_cache.get(lang)

    
@app.post("/ocr")
async def create_upload_file(
    file: UploadFile = File(...),
    lang: LangEnum = LangEnum.ch,
    # use_gpu: bool = False
):
    contents = await file.read()
    image = Image.open(io.BytesIO(contents))
    ocr = get_ocr(lang=lang, use_gpu=use_gpu)
    img2np = np.array(image)
    result = ocr.ocr(img2np, cls=True)[0]

    boxes = [line[0] for line in result]
    txts = [line[1][0] for line in result]
    scores = [line[1][1] for line in result]

    # 识别结果
    final_result = [dict(boxes=box, txt=txt, score=score) for box, txt, score in zip(boxes, txts, scores)]
    return final_result


@app.post("/ocr_table")
async def create_upload_file(
    file: UploadFile = File(...),
    lang: LangEnum = LangEnum.ch,
    # use_gpu: bool = False
):
    table_engine = PPStructure(show_log=True, table=True, lang=lang)

    contents = await file.read()
    # 计算文件内容的哈希值
    file_hash = hashlib.sha256(contents).hexdigest()

    image = Image.open(io.BytesIO(contents))
    img2np = np.array(image)
    result = table_engine(img2np)

    save_structure_res(result, output_dir, f'{file_hash}')

    htmls = []
    types = []
    bboxes = []

    for item in result:
        item_res = item.get('res', {})
        htmls.append(item_res.get('html', ''))
        types.append(item.get('type', ''))
        bboxes.append(item.get('bbox', ''))

    return {
        'htmls': htmls,
        'hash': file_hash,
        'bboxes': bboxes,
        'types': types,
    }


if __name__ == '__main__':
    app.mount("/output", StaticFiles(directory="output", follow_symlink=True, html=True), name="output")
    uvicorn.run(app=app, port=7860)