def api():
r = request
data = r.data
z = np.fromstring(data, dtype=np.float64).reshape((1, 100))
output_data = get_model_api(z)
data_path = hashlib.sha256(output_data.tostring()).hexdigest() + '.png'
scipy.misc.imsave('img/{}'.format(data_path), output_data[0, :, :, :])
return send_file(os.path.join('img', data_path), mimetype='image/png')
def upload():
if "file" not in request.files:
return "No file found!"
file = request.files["file"]
print(file)
file.save(file.filename)
global algorithm
global simExperiment
simExperiment, algorithm = get_model_api(file)
return "File Uploaded successfully!"
def predict_api():
"""API function that recevies forms input and sends predictions to frontend
"""
if request.method == 'GET':
# Show the upload form.
return render_template('simple_client.html')
pdf_file = request.files['pdf_file']
modelPath = request.form['dname']
if pdf_file.filename == '':
return '''No file selected.<a href="/predict">Click here to go back.</a>'''
elif modelPath == '':
return '''No model selected.<a href="/predict">Click here to go back.</a>'''
try:
model = request.form['model']
except:
return '''No model selected.<a href="/predict">Click here to go back.</a>'''
model_dir = modelPath + model
filename = secure_filename(pdf_file.filename)
abs_fpath = filename
session['currentFile'] = filename
session['modelDirectory'] = model_dir
pdf_file.save(abs_fpath)
app.logger.info("api_input: " + str(model_dir))
model_api = serve.get_model_api(model_dir, abs_fpath)
os.remove(abs_fpath)
if (len(model_api) == 0):
return '''Not Supported.<a href="/predict">Click here to go back.</a>'''
else:
return model_api[0].to_json(orient='records', lines=True) + '''
parser = optparse.OptionParser()
parser.add_option('-m', '--model', default=os.path.join('pretrained', 'baseline'), help='path/name of the pretrained model to use (default: pretrained/baseline), the conll2003 pretrained model')
parser.add_option('-l', '--language', default='fr', help='Spacy language model for tokenizer (default: en)')
option, args = parser.parse_args()
modelpath = option.model
LANGUAGE = option.language
path2xpt = modelpath+'.xpt'
path2model = modelpath+'.model'
# define the app
app = Flask(__name__)
CORS(app) # cross-domain requests, allow everything by default
# loading model once and for all the api
model_api = get_model_api(path2xpt, path2model)
# loading tokenizer once and for all for the api
print('Loading spacy tokenizer in '+ LANGUAGE+'....')
tokenizer = myTokenizer(LANGUAGE)
#STATUS = 'live' # live/file
# API live demo route
@app.route('/api', methods=['POST'])
def api():
input_data = request.json
app.logger.info('api_input: ' + str(input_data))
input_client, output_client = model_api(input_data, tokenizer = tokenizer)
app.logger.info('api_output: ' + str(output_client))
response = jsonify(input= input_client, output = output_client)
#coding:utf-8
from flask import Flask, request, jsonify
from flask_restful import Api, Resource, reqparse
from serve import get_model_api
# define the app
app = Flask(__name__)
# 先绑定一个api，进行初始化操作
api = Api(app)
model_api = get_model_api()
class NerView(Resource):
def post(self):
parser = reqparse.RequestParser()
# reqparse 是一个类似于WTforms验证的一个模板，用这个模板的时候，需要先进行引用，然后和WTForms的功能就差不了，就是一个验证用户输入的功能。
parser.add_argument(
'input_conll',
type=str,
help='please input the conll string for entity recognition!',
required=True)
# 定义一个username,说明用户需要传入关于username的一个值()后面的都是参数.括号里面的参数可以先不考虑
args = parser.parse_args()
# 对用户传入的参数进行解析，不解析的话，是会报错的
input_conll = args['input_conll']
output_conll = model_api(input_conll)
return {"output_conll": output_conll}
import os
import sys
import logging
from flask import Flask, request, jsonify
from flask_cors import CORS
from serve import get_model_api
app = Flask(__name__)
CORS(app)
# Initialise model object
model_api = get_model_api(sys.argv[1])
@app.route('/api', methods=['POST'])
def api():
# Data from the API POST request will be request.json
input_data = request.json
app.logger.info('api_input: ' + str(input_data))
# Feeding input data to output
output_data = model_api(input_data)
app.logger.info('api_output: ' + str(output_data))
response = jsonify(output_data)
return response
@app.route('/')
def index():
return 'It Works!'
