def predict_csv(request):
if request.method == 'POST':
# file = request.FILES['fXTest'].read()
myfile = request.FILES['fXTest']
fs = FileSystemStorage()
filename = fs.save(myfile.name, myfile)
uploaded_file_url = fs.url(filename)
print(myfile.name, uploaded_file_url)
dataset = open(os.path.join(settings.MEDIA_ROOT, myfile.name),
'r').read()
# dataset = [dataset.split()]
# for data in dataset:
# dta = data.split(',')
# print(dta)
dataset = StringIO(dataset)
dataset = pd.read_csv(dataset, sep=',')
# print(dataset)
filename = os.path.join(os.path.dirname(__file__), 'static/model.sav')
# with open(filename, 'rb') as f:
# model = pickle.load(f)
classifier = getattr(settings, 'MODEL')
result = dataset.assign(
CLASS=classifier.predict(classifier.scaler.transform(dataset)))
path = os.path.join(
os.path.dirname(__file__),
'../media/result_' + uploaded_file_url.split('/')[-1])
# file=open(djangoSettings.STATIC_ROOT+'/game'+name+'.json','w')
result.to_csv(path)
rows = []
for i, row in result.iterrows():
rows.append({
'AREA': row.AREA,
'PERIMETER': row.PERIMETER,
'MAJORAXIS': row.MAJORAXIS,
'MINORAXIS': row.MINORAXIS,
'ECCENTRICITY': row.ECCENTRICITY,
'CONVEX_AREA': row.CONVEX_AREA,
'EXTENT': row.EXTENT,
'CLASS': row.CLASS,
})
# return HttpResponse(result)
# json_records = result.reset_index().to_json(orient='records')
# result = [json.loads(json_records)]
# context = {'d': result}
# print(result)
res = {'rows': rows, "path": path.split('/')[-1]}
return JsonResponse(res, safe=False)