47 lines
1.3 KiB
Python
47 lines
1.3 KiB
Python
|
import toml
|
||
|
|
from loguru import logger
|
||
|
|
import logging
|
||
|
|
import zmq
|
||
|
|
from paddleocr import PaddleOCR
|
||
|
|
import cv2
|
||
|
|
logging.getLogger('paddleocr').setLevel(logging.CRITICAL)
|
||
|
|
|
||
|
|
if __name__ == "__main__":
|
||
|
|
|
||
|
|
cfg = toml.load('../cfg_infer_server.toml')
|
||
|
|
|
||
|
|
# 配置日志输出
|
||
|
|
logger.add(cfg['debug']['logger_filename'], format=cfg['debug']['logger_format'], retention = 5, level="INFO")
|
||
|
|
|
||
|
|
# 连接摄像头
|
||
|
|
cap = cv2.VideoCapture(4)
|
||
|
|
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 320)
|
||
|
|
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 240)
|
||
|
|
|
||
|
|
# 初始化 paddle 推理器
|
||
|
|
predictor = PaddleOCR(use_angle_cls=False, use_gpu=True)
|
||
|
|
logger.info("ocr model load success")
|
||
|
|
|
||
|
|
# 初始化 server
|
||
|
|
context = zmq.Context()
|
||
|
|
# 启动 server
|
||
|
|
socket = context.socket(zmq.REP)
|
||
|
|
socket.bind(f"tcp://*:{cfg['server']['ocr_infer_port']}")
|
||
|
|
|
||
|
|
while True:
|
||
|
|
socket.recv_string("")
|
||
|
|
ret, frame = cap.read()
|
||
|
|
try:
|
||
|
|
if ret:
|
||
|
|
result = predictor.ocr(frame)
|
||
|
|
response = {'code': 0, 'data': result}
|
||
|
|
socket.send_pyobj(response)
|
||
|
|
else:
|
||
|
|
socket.send_pyobj({'code': -1, 'data': None})
|
||
|
|
except:
|
||
|
|
socket.send_pyobj({'code': -1, 'data': None})
|
||
|
|
if cv2.waitKey(1) == 27:
|
||
|
|
break
|
||
|
|
logger.info("ocr infer server exit")
|
||
|
|
|