change route

API/app.py

 from flask import Flask, redirect, url_for, render_template, request, jsonify, make_response
-
+import random
+import os
 from API.model.colorModel import get_color_activities, get_color_activity_result
 from API.model.readModel import get_reading_activities
 from API.routers.router import funtion_one
+from backend.IT18218640.keyword_spotting_service import Keyword_Spotting_service
 
 app = Flask(__name__)
 
@@ -23,6 +25,43 @@ def getColorActivitiesResult():
     # print("data_dic")
     return get_color_activity_result()
 
+@app.route("/predict", methods=["POST"])
+def predict():
+    # get audio file and save it
+    audio_file = request.files["file"]
+
+    print(f"{request.files['file']}")
+    # print(f"{request.files['name']}")
+
+    ######################################
+    print(f"{request.form['name']}")
+    #####################################
+    # print(f"{request.json}")
+
+    file_name = str(random.randint(0, 100000))
+    # audio_file.save((file_name))
+
+    # get file name
+    # predict_file_name = audio_file.filename
+    # predict_file_name = predict_file_name.split("/")
+    # new_predict_file_name = predict_file_name[1]
+    # new_predict_file_name = new_predict_file_name.split(".")
+    # FPFN = new_predict_file_name[0]
+    # print(f"{FPFN}")
+
+    # invoke keyword spotting service
+    kss = Keyword_Spotting_service()
+
+    # make a prediction
+    predicted_keyword = kss.predict(file_name, request.form['name'])
+
+    # remove the audio file
+    os.remove(file_name)
+
+    # send back the predicted keword in json format
+    data = {"Keyword": predicted_keyword}
+    return jsonify(data)
+    # return "audio_file"
 
 # Read Function Route (IT)
 

backend/IT18218640/client.py

 import requests
 
-URL = "http://192.168.8.101:5000/predict"
+URL = "http://192.168.8.100:5000/predict"
 TEST_AUDIO_FILE_PATH = "test/red.wav"
 
 if __name__ == "__main__":

backend/IT18218640/keyword_spotting_service.py

@@ -17,9 +17,11 @@ class _Keyword_Spotting_Service:
         "yellow"
     ]
     _instance = None
-
+    # 78293
     def predict(self, file_path, FPFN):
 
+        print(f"{file_path}")
+
         # extract MFCCs
         MFCCs = self.preprocess(file_path) # (# segment, # coefficients)
 

backend/IT18218640/server.py

@@ -7,25 +7,26 @@ app = Flask(__name__)
 
 @app.route("/predict", methods=["POST"])
 def predict():
+
     # get audio file and save it
     audio_file = request.files["file"]
-
-    # print(f"{request.files['file']}")
-    # print(f"{request.files['name']}")
     file_name = str(random.randint(0, 100000))
     audio_file.save((file_name))
 
     # get file name
-    predict_file_name = audio_file.filename
-    predict_file_name = predict_file_name.split("/")
-    new_predict_file_name = predict_file_name[1]
-    new_predict_file_name = new_predict_file_name.split(".")
-    FPFN = new_predict_file_name[0]
+    # predict_file_name = audio_file.filename
+    # predict_file_name = predict_file_name.split("/")
+    # new_predict_file_name = predict_file_name[1]
+    # new_predict_file_name = new_predict_file_name.split(".")
+    # FPFN = new_predict_file_name[0]
+
+    FPFN = request.form['name']
     # print(f"{FPFN}")
 
     # invoke keyword spotting service
     kss = Keyword_Spotting_service()
 
+
     # make a prediction
     predicted_keyword = kss.predict(file_name, FPFN)
 
@@ -33,10 +34,11 @@ def predict():
     os.remove(file_name)
 
     # send back the predicted keword in json format
-    data = {"Keyword": predicted_keyword}
+    data = {"Keyword" : predicted_keyword}
     return jsonify(data)
 
+
 if __name__ == "__main__":
-    app.run(host='192.168.8.101')
+    app.run(host='192.168.8.100')
     #app.run(host='192.168.8.100,port='5000', debug=True)
     # app.run(debug=False)
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