Files
ocr_demo/api/easy_orc_api.py
2025-09-28 13:37:21 +08:00

62 lines
1.8 KiB
Python

import os
import cv2
import easyocr
import numpy as np
from core.response import SuccessResponse
from fastapi import APIRouter, UploadFile, Form
from schemas.orc_result import ResultInfo, ResultMain
app = APIRouter()
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
model_dir = os.path.join(BASE_DIR, 'model')
reader = easyocr.Reader(
['ch_sim', 'en'],
model_storage_directory=model_dir,
download_enabled=False,
gpu=True)
def preprocess_img(image):
# 转为灰度图
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# 二值化
_, binary = cv2.threshold(gray, 150, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
# 去噪声
denoised = cv2.medianBlur(binary, 3)
return denoised
@app.post("/upload")
async def orc(files: list[UploadFile] = Form(...)):
result = []
for file in files:
main = ResultMain()
main.file_name = file.filename
# 读取上传的文件内容
image_data = await file.read()
# 2. 将字节数据转换为 numpy 数组
np_array = np.frombuffer(image_data, np.uint8)
# 3. 使用 cv2.imdecode 解码为 OpenCV 图像
image = cv2.imdecode(np_array, cv2.IMREAD_COLOR)
new_image = preprocess_img(image)
datas = reader.readtext(np.array(new_image))
infos = []
for data in datas:
info = ResultInfo()
bounding_boxs = data[0]
left_up = bounding_boxs[0]
right_down = bounding_boxs[2]
info.bounding_box_left_up = [int(left_up[0]), int(left_up[1])]
info.bounding_box_right_down = [int(right_down[0]), int(right_down[1])]
info.text = data[1]
info.confidence = round(data[2], 4)
infos.append(info)
main.infos = infos
result.append(main.model_dump())
return SuccessResponse(data=result)