docker部署detection模型样例

本样例采用flask端口映射方式进行部署

import os
import threading
import datetime
import time
import requests
import logging
import io
import numpy as np

import dnn_conf as conf

if not os.path.isdir(conf.LOG_PATH):
    os.makedirs(conf.LOG_PATH)        

log_file = conf.LOG_PATH + "/" + conf.LOG_FILE
logging.basicConfig(filename=log_file,level=logging.DEBUG, format='%(asctime)s.%(msecs)03d %(threadName)s %(levelname)-8s %(message)s', datefmt='%Y-%m-%d %H:%M:%S')


from flask import Flask
from flask import send_file, send_from_directory
from flask import jsonify
from flask import request


import detect_ctrl as ctrl


app = Flask(__name__)


def get_request_file(request):
    if 'file' not in request.files:
        return None

    file = request.files['file']
    input_file = io.BytesIO()
    file.save(input_file)
    return np.fromstring(input_file.getvalue(), dtype=np.uint8)


def send_blob(blob, mime_type):
    out_file = io.BytesIO()
    out_file.write(blob)
    out_file.seek(0)
    return send_file(out_file, mimetype=mime_type)



@app.route('/')
def index():
    return 'DNN REST Service'



@app.route('/detect', methods=['POST'])
def detect():
    data = get_request_file(request)
    if data is None:
        "file", requests.codes.bad_request

    rc, ret = ctrl.detect(data)
    if not rc:
        return jsonify({"error" : ret}), requests.codes.bad_request
    return jsonify(ret), requests.codes.ok


@app.route('/ddetect', methods=['POST'])
def detect_draw():
    data = get_request_file(request)
    if data is None:
        "file", requests.codes.bad_request

    rc, jpg = ctrl.detect_draw(data)
    if not rc:
        return ret, requests.codes.bad_request
    return send_blob(jpg, "image/jpeg")





if __name__ == '__main__':
    app.run(host='0.0.0.0', port=80, debug=True, threaded=False, use_reloader=False)

Dockfile方式：

FROM python:3.7-stretch

RUN pip3 install flask
RUN pip3 install protobuf
RUN pip3 install requests
RUN pip3 install opencv_python

ADD http://download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_coco_11_06_2017.tar.gz /
RUN tar -xvf /ssd_mobilenet_v1_coco_11_06_2017.tar.gz

ADD https://github.com/tprlab/docker-detect/archive/master.zip /
RUN unzip /master.zip

EXPOSE 80

#CMD ["python3", "/docker-detect-master/detect-app/dnn_ctrl.py", "/docker-detect-master/detect-app/data/pic.jpg"]
CMD ["python3", "/docker-detect-master/detect-app/app.py"]