Update app/apps/emotion_recognition/views.py

app/apps/emotion_recognition/views.py

@@ -1,119 +1,118 @@
-from django.shortcuts import render, redirect
-from django.views.decorators.http import require_http_methods
-from django.http import HttpResponse, StreamingHttpResponse
-from django.contrib.auth.mixins import LoginRequiredMixin
-from django.views.generic import UpdateView, DeleteView
-from django.contrib import messages
-from django.urls import reverse_lazy
-
-from rest_framework.views import APIView
-from rest_framework.response import Response
-from rest_framework import status
-from rest_framework.parsers import MultiPartParser, FormParser
-from .serializers import ImageSerializer
-from PIL import Image
-
-from .models import UserImageRecognition
-from .emotion_recognition import  emotionVideo
-from .tasks import proccess_uploaded_image, process_image_from_api, convert_image_to_bytes
-from .forms import RecognitionEditForm
-
-
-
-@require_http_methods(['GET', 'POST'])
-def index(request):
-    try:
-
-        # GET method, return HTML page
-        if request.method == 'GET':
-            samples = UserImageRecognition.objects.all()
-            return render(request, 'recognition/index.html', {'samples': samples, })
-
-        if request.FILES and request.method == 'POST':
-            for f in request.FILES.getlist('uploaded_file'):
-                uploaded_image = f
-                image_data = UserImageRecognition.objects.create(uploaded_image=uploaded_image)
-
-                proccess_uploaded_image(image_data.id)
-
-        return redirect('recognition:index')
-
-    except Exception as e:
-
-        image_data.status = 'ERR'
-        image_data.error_occurred = True
-        image_data.error_message = str(e)
-        image_data.save()
-
-        return HttpResponse(f'Error: {str(e)}')
-    
-
-
-@require_http_methods(['GET', 'POST'])
-def real_time_recognition(request):
-    return render(request, 'recognition/real_time.html')
-
-def real_time_stream(request):
-    return StreamingHttpResponse(emotionVideo(),content_type="multipart/x-mixed-replace;boundary=frame")
-
-
-class RecognitionUpdateView(LoginRequiredMixin, UpdateView):
-    model = UserImageRecognition
-    form_class = RecognitionEditForm
-    template_name = "recognition/recognition_edit.html"
-
-    def get(self, request, pk):
-        self.object = self.get_object()
-        
-        context = self.get_context_data(object=self.object)
-        return self.render_to_response(context)
-    
-    def get_success_url(self, **kwargs):
-        pk = self.object.pk
-        messages.success(self.request, 'Запись была успешно изменена!')         
-        return reverse_lazy('recognition:recognition_edit', args=(pk,))
-
-
-class RecognitionDeleteView(LoginRequiredMixin, DeleteView):
-    model = UserImageRecognition
-    template_name = "recognition/recognition_delete.html"
-
-    def delete(self, request, pk):
-        return super().delete(request, pk)
-
-    def get_success_url(self, **kwargs):
-        obj = self.get_object()
-        messages.success(self.request, 'Запись  была успешно удалёна!')         
-        return reverse_lazy('recognition:index')
-    
-    
-class ImageProcessingView(APIView):
-    parser_classes = (MultiPartParser, FormParser)  # Для обработки загруженных файлов
-    serializer_class = ImageSerializer
-
-    def post(self, request, format=None):
-        """
-        Обрабатывает изображение, переданное через API, и возвращает финальное изображение с эмоциями.
-        """
-        serializer = self.serializer_class(data=request.data)
-        if serializer.is_valid():
-            image_file = serializer.validated_data['image']
-            
-            try:
-                # Обработка изображения
-                final_image, predicted_emotions, recognized_emotion = process_image_from_api(image_file)
-                output_image = convert_image_to_bytes(final_image)
-
-                # Формируем ответ
-                response_data = {
-                    "predicted_emotions": predicted_emotions,
-                    "recognized_emotion": recognized_emotion,
-                }
-                response = Response(response_data, status=status.HTTP_200_OK)
-                response['Content-Type'] = 'image/jpeg'
-                response.content = output_image.getvalue()
-                return response
-            except Exception as e:
-                return Response({"error": str(e)}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
-
+from django.shortcuts import render, redirect
+from django.views.decorators.http import require_http_methods
+from django.http import HttpResponse, StreamingHttpResponse
+from django.contrib.auth.mixins import LoginRequiredMixin
+from django.views.generic import UpdateView, DeleteView
+from django.contrib import messages
+from django.urls import reverse_lazy
+
+from rest_framework.views import APIView
+from rest_framework.response import Response
+from rest_framework import status
+from rest_framework.parsers import MultiPartParser, FormParser
+from .serializers import ImageSerializer
+from PIL import Image
+
+from .models import UserImageRecognition
+from .tasks import proccess_uploaded_image, process_image_from_api, convert_image_to_bytes
+from .forms import RecognitionEditForm
+
+
+
+@require_http_methods(['GET', 'POST'])
+def index(request):
+    try:
+
+        # GET method, return HTML page
+        if request.method == 'GET':
+            samples = UserImageRecognition.objects.all()
+            return render(request, 'recognition/index.html', {'samples': samples, })
+
+        if request.FILES and request.method == 'POST':
+            for f in request.FILES.getlist('uploaded_file'):
+                uploaded_image = f
+                image_data = UserImageRecognition.objects.create(uploaded_image=uploaded_image)
+
+                proccess_uploaded_image(image_data.id)
+
+        return redirect('recognition:index')
+
+    except Exception as e:
+
+        image_data.status = 'ERR'
+        image_data.error_occurred = True
+        image_data.error_message = str(e)
+        image_data.save()
+
+        return HttpResponse(f'Error: {str(e)}')
+    
+
+
+# @require_http_methods(['GET', 'POST'])
+# def real_time_recognition(request):
+#     return render(request, 'recognition/real_time.html')
+
+# def real_time_stream(request):
+#     return StreamingHttpResponse(emotionVideo(),content_type="multipart/x-mixed-replace;boundary=frame")
+
+
+class RecognitionUpdateView(LoginRequiredMixin, UpdateView):
+    model = UserImageRecognition
+    form_class = RecognitionEditForm
+    template_name = "recognition/recognition_edit.html"
+
+    def get(self, request, pk):
+        self.object = self.get_object()
+        
+        context = self.get_context_data(object=self.object)
+        return self.render_to_response(context)
+    
+    def get_success_url(self, **kwargs):
+        pk = self.object.pk
+        messages.success(self.request, 'Запись была успешно изменена!')         
+        return reverse_lazy('recognition:recognition_edit', args=(pk,))
+
+
+class RecognitionDeleteView(LoginRequiredMixin, DeleteView):
+    model = UserImageRecognition
+    template_name = "recognition/recognition_delete.html"
+
+    def delete(self, request, pk):
+        return super().delete(request, pk)
+
+    def get_success_url(self, **kwargs):
+        obj = self.get_object()
+        messages.success(self.request, 'Запись  была успешно удалёна!')         
+        return reverse_lazy('recognition:index')
+    
+    
+class ImageProcessingView(APIView):
+    parser_classes = (MultiPartParser, FormParser)  # Для обработки загруженных файлов
+    serializer_class = ImageSerializer
+
+    def post(self, request, format=None):
+        """
+        Обрабатывает изображение, переданное через API, и возвращает финальное изображение с эмоциями.
+        """
+        serializer = self.serializer_class(data=request.data)
+        if serializer.is_valid():
+            image_file = serializer.validated_data['image']
+            
+            try:
+                # Обработка изображения
+                final_image, predicted_emotions, recognized_emotion = process_image_from_api(image_file)
+                output_image = convert_image_to_bytes(final_image)
+
+                # Формируем ответ
+                response_data = {
+                    "predicted_emotions": predicted_emotions,
+                    "recognized_emotion": recognized_emotion,
+                }
+                response = Response(response_data, status=status.HTTP_200_OK)
+                response['Content-Type'] = 'image/jpeg'
+                response.content = output_image.getvalue()
+                return response
+            except Exception as e:
+                return Response({"error": str(e)}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
+
         return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)