def copy(wb):
w = XLWTWriter()
process(
XLRDReader(wb,'unknown.xls'),
w
)
return w.output[0][1]
def post(self):
fileinfo = self.request.files['image'][0]
fname = fileinfo['filename']
extn = os.path.splitext(fname)[1]
cname = str(uuid.uuid4()) + extn
fh = open('images/' + cname, 'wb')
fh.write(fileinfo['body'])
process('images/' + cname, 'results/' + cname)
self.render('result.html', name=cname)
def post(self):
fileinfo = self.request.files['image'][0]
fname = fileinfo['filename']
extn = os.path.splitext(fname)[1]
cname = str(uuid.uuid4()) + extn
fh = open('images/' + cname, 'wb')
fh.write(fileinfo['body'])
process('images/' + cname, 'results/' + cname)
self.render('result.html', name=cname)
def save(wb,filename_or_stream):
if isinstance(filename_or_stream,basestring):
filename = os.path.split(filename_or_stream)[1]
stream = open(filename_or_stream,'wb')
close = True
else:
filename = 'unknown.xls'
stream = filename_or_stream
close = False
process(
XLRDReader(wb,filename),
StreamWriter(stream)
)
if close:
stream.close()
def predictml():
db.stream.drop()
json = request.json
df = pd.get_dummies(pd.DataFrame(json))
df = process(df)
prediction = ml_model.predict(df).tolist()
db.stream.insert_one({"data": json, 'state': prediction[0]})
return jsonify(1)
