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authorSonja Galovic <galovicsonja@gmail.com>2022-05-06 21:46:36 +0200
committerSonja Galovic <galovicsonja@gmail.com>2022-05-06 21:46:36 +0200
commit21fb702db98de85a75ce1abda898b89968aef91d (patch)
tree4b9f9aa65339fb581ededc844107fb8107c39e05 /backend/microservice
parent802634b0d74232a20db63d22e7003c9148baaba3 (diff)
parent4578d218ba7caeb27277041db37a0601ebcefef0 (diff)
Merge branch 'redesign' of http://gitlab.pmf.kg.ac.rs/igrannonica/neuronstellar into redesign
Diffstat (limited to 'backend/microservice')
-rw-r--r--backend/microservice/api/controller.py23
1 files changed, 19 insertions, 4 deletions
diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py
index 988ad987..8d49fcc4 100644
--- a/backend/microservice/api/controller.py
+++ b/backend/microservice/api/controller.py
@@ -54,12 +54,20 @@ class train_callback(tf.keras.callbacks.Callback):
@app.route('/train', methods = ['POST'])
def train():
print("******************************TRAIN*************************************************")
-
- f = request.files.get("file")
- data = pd.read_csv(f)
paramsModel = json.loads(request.form["model"])
paramsExperiment = json.loads(request.form["experiment"])
paramsDataset = json.loads(request.form["dataset"])
+ f = request.files.get("file")
+ if(paramsDataset['delimiter']=='novi red'):
+ separation='\n'
+
+ elif(paramsDataset['delimiter']=='razmak'):
+ separation=' '
+ else:
+ separation=paramsDataset['delimiter']
+ data = pd.read_csv(f,sep=separation)
+
+
#dataset, paramsModel, paramsExperiment, callback)
filepath,result = newmlservice.train(data, paramsModel, paramsExperiment,paramsDataset, train_callback)
"""
@@ -110,7 +118,14 @@ def returnColumnsInfo():
dataset = json.loads(request.form["dataset"])
file = request.files.get("file")
- data=pd.read_csv(file)
+ if(dataset['delimiter']=='novi red'):
+ separation='\n'
+
+ elif(dataset['delimiter']=='razmak'):
+ separation=' '
+ else:
+ separation=dataset['delimiter']
+ data=pd.read_csv(file,sep=separation)
'''
#f = request.json['filepath']
#data=pd.read_csv(f)