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authorDanijel Andjelkovic <adanijel99@gmail.com>2022-04-06 13:14:00 +0200
committerDanijel Andjelkovic <adanijel99@gmail.com>2022-04-06 13:14:00 +0200
commit1b235bb4317477e673806ab9d2835a4dca48f88e (patch)
treeccc776c46e2f68e4285c7298f10ea8f591058e50 /backend/microservice/api/controller.py
parentaf3333a77e254b3268de38ec397921b43f357949 (diff)
parent480eb6a4e07b130129171d83ca9ba263dfba32c3 (diff)
Merge branch 'dev' of http://gitlab.pmf.kg.ac.rs/igrannonica/neuronstellar into dev
# Conflicts: # frontend/src/app/_pages/add-model/add-model.component.html # frontend/src/app/_pages/add-model/add-model.component.ts # frontend/src/app/app.module.ts
Diffstat (limited to 'backend/microservice/api/controller.py')
-rw-r--r--backend/microservice/api/controller.py22
1 files changed, 17 insertions, 5 deletions
diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py
index 059af317..1b17f727 100644
--- a/backend/microservice/api/controller.py
+++ b/backend/microservice/api/controller.py
@@ -1,7 +1,7 @@
import flask
from flask import request, jsonify
import ml_socket
-import ml_service
+import newmlservice
import tensorflow as tf
import pandas as pd
@@ -25,7 +25,7 @@ def train():
f = request.json["dataset"]
dataset = pd.read_csv(f)
#
- result = ml_service.train(dataset, request.json["model"], train_callback)
+ result = newmlservice.train(dataset, request.json["model"], train_callback)
print(result)
return jsonify(result)
@@ -34,10 +34,22 @@ def predict():
f = request.json['filepath']
dataset = pd.read_csv(f)
m = request.json['modelpath']
- #model = tf.keras.models.load_model(m)
- #
- #model.predict?
+ model = tf.keras.models.load_model(m)
+ print("********************************model loaded*******************************")
+ newmlservice.manageH5(dataset,request.json['model'],model)
+ return "done"
+
+@app.route('/preprocess',methods=['POST'])
+def returnColumnsInfo():
+ f=request.json['filepathcolinfo']
+ dataset=pd.read_csv(f)
+
+ result=newmlservice.returnColumnsInfo(dataset)
+
+ return jsonify(result)
+
+
print("App loaded.")
ml_socket.start()
app.run() \ No newline at end of file