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rapidocr/ocrweb/task.py
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Python

# !/usr/bin/env python
# -*- encoding: utf-8 -*-
# @File: worker.py
# @Time: 2021/03/07 20:29:32
# @Author: Max
import json
import base64
import cv2
import time
import numpy as np
import redis
from rq import Worker, Queue, Connection
from resources.bpocr import TextSystem, draw_text_det_res
listen = ['default']
redis_url = "redis://localhost:6379" # redis server 默认地址
conn = redis.from_url(redis_url)
# 实例化模型
det_model_path = 'resources/models/ch_ppocr_server_v2.0_det_infer.onnx'
cls_model_path = 'resources/models/ch_ppocr_mobile_v2.0_cls_infer.onnx'
rec_model_path = 'resources/models/ch_ppocr_mobile_v2.0_rec_infer.onnx'
text_sys = TextSystem(det_model_path,
rec_model_path,
use_angle_cls=True,
cls_model_path=cls_model_path)
def detect_recognize(image_path):
if isinstance(image_path, str):
image = cv2.imread(image_path)
elif isinstance(image_path, np.ndarray):
image = image_path
t1 = time.time()
dt_boxes, rec_res, img = text_sys(image)
t2 = time.time()
if dt_boxes is None or rec_res is None:
temp_rec_res = []
rec_res_data = json.dumps(temp_rec_res,
indent=2,
ensure_ascii=False)
elapse = 0
image = cv2.imencode('.jpg', img)[1]
img = str(base64.b64encode(image))[2:-1]
else:
temp_rec_res = []
for i, value in enumerate(rec_res):
temp_rec_res.append([i, value[0], value[1]])
temp_rec_res = np.array(temp_rec_res)
rec_res_data = json.dumps(temp_rec_res.tolist(),
indent=2,
ensure_ascii=False)
det_im = draw_text_det_res(dt_boxes, img)
image = cv2.imencode('.jpg', det_im)[1]
img = str(base64.b64encode(image))[2:-1]
elapse = f'{t2-t1:.3f}'
return json.dumps({'image': img,
'elapse': elapse,
'rec_res': rec_res_data})
if __name__ == '__main__':
with Connection(conn): # 建立与redis server的连接
worker = Worker(list(map(Queue, listen))) # 建立worker监听给定的队列
worker.work()