Merge branch 'IT18094664' of http://gitlab.sliit.lk/2022-240/240 into IT18094664

backend/backend/cms/model/predict.py

-# import pickle
-# from keras.models import load_model
+import pickle
+from keras.models import load_model
 
+import numpy as np
 
-# import numpy as np
+import IPython.display as ipd
 
+import random
 
-# import IPython.display as ipd
+from sklearn.model_selection import train_test_split
+from sklearn.preprocessing import LabelEncoder
 
-# import random
+def predict(samples):
+    #load the trained model
+    model=load_model(r'./best_model_final.hdf5')
 
-# from sklearn.model_selection import train_test_split
-# from sklearn.preprocessing import LabelEncoder
+    #load labels
+    f1 = open('all_label.txt', 'rb')
+    all_label = pickle.load(f1)
+    print('loaded labels')
 
+    #preprocess recorded audio
+    le = LabelEncoder()
+    y = le.fit_transform(all_label)
+    classes = list(le.classes_)
 
-# def predict(samples):
-#     model=load_model(r'./best_model_final.hdf5')
+    def predictSamples(audio):
+        prob=model.predict(audio.reshape(1,8000,1))
+        index=np.argmax(prob[0])
+        return classes[index]
 
-#     f1 = open('all_label.txt', 'rb')
-#     all_label = pickle.load(f1)
-#     print('loaded labels')
+    ipd.Audio(samples, rate=8000)
 
-#     # f2 = open('all_waves_file.txt', 'rb')
-#     # all_wave = pickle.load(f2)
-#     # print('loaded waves')
+    #run the prediction
+    result = predictSamples(samples)
 
-#     le = LabelEncoder()
-#     y = le.fit_transform(all_label)
-#     classes = list(le.classes_)
+    print("Text:",result)
 
-#     # train_data_file = open("train_data_file.txt", 'rb')
-#     # [x_tr, x_val, y_tr, y_val] = np.load(train_data_file, allow_pickle=True)
-#     # train_data_file.close()
-
-#     def predictSamples(audio):
-#         prob=model.predict(audio.reshape(1,8000,1))
-#         index=np.argmax(prob[0])
-#         return classes[index]
-
-        
-#     # index=random.randint(0,len(x_val)-1)
-#     # samples=x_val[index].ravel()
-#     print(samples)
-#     # print("Audio:",classes[np.argmax(y_val[index])])
-#     ipd.Audio(samples, rate=8000)
-
-#     result = predictSamples(samples)
-
-#     print("Text:",result)
-
-#     return result
\ No newline at end of file
+    return result
\ No newline at end of file

backend/backend/cms/views.py

@@ -16,26 +16,23 @@ import librosa
 
 from django.db.models import Q
 
-
 from django.core.files.storage import FileSystemStorage
 
 from .models import Chat, Conversation, MlModel
 from rest_framework_simplejwt.views import TokenObtainPairView
 
-# from .model.train import train
-
-# from .model.predict import predict
-
+from .model.train import train
+from .model.predict import predict
 
 from pydub import AudioSegment
 import numpy as np
 
 
+#Custom Viewset to get auth token
 class ObtainTokenPairWithUserView(TokenObtainPairView):
     permission_classes = (permissions.AllowAny,)
     serializer_class = MyTokenObtainPairSerializer
 
-
 class UserViewSet(viewsets.ModelViewSet):
     """
     API endpoint that allows users to be viewed or edited.
@@ -70,9 +67,9 @@ class MlModelViewSet(viewsets.ViewSet):
     permission_classes = [permissions.AllowAny]
     parser_classes = [MultiPartParser]
 
+    #Custom api to add sample chats
     @action(detail=False)
     def addChats(*args, **kwargs):
-
         admin = User.objects.get(username='admin')
         user2 = User.objects.get(username='user2')
 
@@ -106,6 +103,7 @@ class MlModelViewSet(viewsets.ViewSet):
                 conversation=convo, from_user_id=chat['from'], to_user_id=chat['to'], messsage=chat['message'])
             object.save()
 
+    #Custom api to train the model
     @action(detail=False)
     def train(*args, **kwargs):
         print('Function ran')
@@ -113,6 +111,7 @@ class MlModelViewSet(viewsets.ViewSet):
         print(results)
         return Response({'success': True})
 
+    #Custom api to convert audio to text
     @action(detail=False, methods=["POST"])
     def detect(self, request, *args, **kwargs):
         print('Function ran')
@@ -135,7 +134,7 @@ class MlModelViewSet(viewsets.ViewSet):
 
         print('---------------------------------------------------------')
         if(samples.shape[0] > 8000):
-            print('grateer -------------------------------------')
+            print('grater -------------------------------------')
             samples = samples[-8000:]
             print(samples.shape)
         else:
@@ -144,57 +143,17 @@ class MlModelViewSet(viewsets.ViewSet):
             samples = np.concatenate((samples, new_arr))
             print(samples.shape)
 
-        # audio_file = request.data
-
-        # # Using File storage to save file for future converting
-        # fs = FileSystemStorage()
-        # file_name = fs.save(audio_file.name, audio_file)
-        # audio_file_url = fs.url(file_name)
-
-        # # Preparing paths for convertion
-        # upstream = os.path.dirname(os.path.dirname(os.path.dirname(
-        #     os.path.abspath(__file__))))
-        # path = os.path.join(upstream, 'media', audio_file.name)
-        # mp3_filename = '.'.join([audio_file.name.split('.')[0], 'mp3'])
-        # new_path = os.path.join(
-        #     upstream, 'media', mp3_filename)
-
-        # # Converting to mp3 here
-        # wma_version = AudioSegment.from_file(path, "wav")
-        # wma_version.export(new_path, format="mp3")
-
-        # user_id = self.request.user.id
-
-        # # I was trying to create a Track instance, the mp3 get's saved but it is not being saved using location specified in models.
-        # track = Track.objects.create(user_id=user_id)
-        # track.file.name = mp3_filename
-        # track.save()
-
-        results = {}  # predict(samples)
+        results = predict(samples)
         print(results)
         return Response({'success': True, 'result': results})
 
-
 class ChatViewSet(viewsets.ModelViewSet):
     queryset = Chat.objects.all().order_by('-timestamp')
     serializer_class = ChatSerializer
-    permission_classes = [permissions.IsAuthenticated] #change to permissions.isAutheniticated
-
-    @action(methods='POST', detail=True)
-    def getChats(self, request, *args, **kwargs):
-        #conversation_id hardcoded as we dont have many conversations at the moment
-        chats = Chat.objects \
-        .filter(conversation_id=1) \
-        .filter(
-            (Q(from_user__user_id=request.user.id) 
-            | Q(to_user__user_id=request.user.id))
-            ).order_by('-timestamp').values()
-
-        return Response({chats})
+    permission_classes = [permissions.IsAuthenticated]
 
+    #ovveride defualt list action to get chats of specific user conversation
     def list(self, request, pk=None):
-
-
         if pk == None:
             chats = Chat.objects \
             .filter(conversation_id=1) \
@@ -210,7 +169,6 @@ class ChatViewSet(viewsets.ModelViewSet):
 
         serializer = self.get_serializer(page, many=True)
         result_set = serializer.data
-
         return Response(result_set)
 
     def get_result_set(self, chats):
@@ -218,7 +176,6 @@ class ChatViewSet(viewsets.ModelViewSet):
 
         return result_set
 
-
 class ConversationViewSet(viewsets.ModelViewSet):
     queryset = Conversation.objects.all().order_by('id')
     serializer_class = ConversationSerializer