56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
from core.response import SuccessResponse
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from fastapi import APIRouter, UploadFile, Form
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from schemas.orc_result import ResultInfo, ResultMain
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from paddleocr import PaddleOCR
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import numpy as np
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import cv2
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app = APIRouter()
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paddle_ocr = PaddleOCR(lang='ch')
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def enhance_image(img):
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"""增强亮部和暗部，提升数字清晰度"""
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lab = cv2.cvtColor(img, cv2.COLOR_BGR2LAB)
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l, a, b = cv2.split(lab)
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clahe = cv2.createCLAHE(clipLimit=3.0, tileGridSize=(8,8))
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cl = clahe.apply(l)
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enhanced = cv2.merge((cl, a, b))
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return cv2.cvtColor(enhanced, cv2.COLOR_LAB2BGR)
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@app.post("/upload")
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async def orc(files: list[UploadFile] = Form(...)):
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result = []
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for file in files:
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main = ResultMain()
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main.file_name = file.filename
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# 读取上传的文件内容
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image_data = await file.read()
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# 从字节数据读取图像
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np_array = np.frombuffer(image_data, np.uint8)
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img = cv2.imdecode(np_array, cv2.IMREAD_COLOR)
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# 图像增强
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img = enhance_image(img)
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# 4. 调用 OCR 模型进行识别
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datas = paddle_ocr.ocr(img, cls=False)
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infos = []
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if datas:
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for data in datas[0]:
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info = ResultInfo()
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bounding_boxs = data[0]
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left_up = bounding_boxs[0]
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right_down = bounding_boxs[2]
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info.bounding_box_left_up = [int(left_up[0]), int(left_up[1])]
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info.bounding_box_right_down = [int(right_down[0]), int(right_down[1])]
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info.text = data[1][0]
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info.confidence = round(data[1][1], 4)
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infos.append(info)
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main.infos = infos
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result.append(main.model_dump())
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return SuccessResponse(data=result)
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