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main.py
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main.py
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import json
from flask import request, Response, render_template, Flask
from wsgiref import simple_server
from train_validate import train_validate
from train_model import train_model
from pred_validate import pred_validate
from predict_from_model import predict_from_model
from create_log_directories import create_log_directories
app = Flask(__name__)
@app.route('/')
def home():
return render_template('index.html')
@app.route('/train', methods=['POST'])
def training():
# step 0 if folder path is none then raise error else do step 1 & 2
try:
if request.json['folderPath'] is not None:
path = request.json['folderPath']
print(path)
# step 1 validate the data
val_obj = train_validate(path) # object initialization
val_obj.training_validation() # call to method in the class
# step2 train the model
train_model_obj = train_model() # object initialize
train_model_obj.training_model()
except ValueError:
return Response("Error Occurred %s" % ValueError)
except KeyError:
return Response("Error Occurred %s" % KeyError)
except Exception as e:
return Response("Error Occurred %s" % e)
return Response("Training is Successful.")
@app.route('/predict', methods=['POST'])
def predict():
try:
if request.json is not None:
path = request.json['filepath']
# step1 validate the data
pred_obj = pred_validate(path)
pred_obj.pred_validation()
# step2 predict from model (gives path of file where prediction is saved + top 5 predictions in json
pred_from_model_obj = predict_from_model()
path, demo_json_predictions = pred_from_model_obj.get_prediction_from_model()
return Response("Prediction file create at " + str(path) + ' and few of the predictions are ' + str(
json.loads(demo_json_predictions)))
# if prediction request is coming from form
elif request.form is not None:
path = request.form['filepath']
# step1 validate the data
pred_obj = pred_validate(path)
pred_obj.pred_validation()
# step2 predict from model (gives path of file where prediction is saved + top 5 predictions in json
pred_from_model_obj = predict_from_model()
path, demo_json_predictions = pred_from_model_obj.get_prediction_from_model()
return Response("Prediction file create at " + str(path) + ' and few of the predictions are ' + str(
json.loads(demo_json_predictions)))
except ValueError:
return Response("Error Occurred %s" % ValueError)
except KeyError:
return Response("Error Occurred %s" % KeyError)
except Exception as e:
return Response("Error Occurred %s" % e)
if __name__ == "__main__":
host = '127.0.0.1'
port = 5000
#to ensure all log files are in place
obj=create_log_directories()
obj.create_directories()
server = simple_server.make_server(host, port, app)
server.serve_forever()
# app.run(debug=True)