def post(self, request):
image_serializer = ImageSerializer(data=request.data)
if image_serializer.is_valid() and request.FILES.get("image", None):
image_id = str(uuid.uuid4())
#request_id = request.data.get("request_id")
#callback_url = request.data.get("callback_url")
name = upload_image(request, image_id)
image = Image_object()
image.image_id = image_id
#image.request_id = request_id
#image.callback_url = callback_url
image.name = name
image.save()
print("-----------image_id---------------")
print(image_id)
detected_faces2 = detect_faces_retina(image_id)
detect_faces_callback_retina(image_id)
#detect_faces(image_id)
#detect_faces_callback(image_id)
return Response({"status": detected_faces2},
status=status.HTTP_202_ACCEPTED)
else:
if not request.FILES.get("image", None):
return Response({'`image` is required'},
status=status.HTTP_400_BAD_REQUEST)
return Response(image_serializer.errors,
status=status.HTTP_400_BAD_REQUEST)
def post(self, request):
image_serializer = ImageSerializer(data=request.data)
if image_serializer.is_valid() and request.FILES.get("image", None):
image_id = str(uuid.uuid4())
request_id = request.data.get("request_id")
callback_url = request.data.get("callback_url")
name = upload_image(request, image_id)
image = Image_object()
image.image_id = image_id
image.request_id = request_id
image.callback_url = callback_url
image.name = name
image.save()
chain(
detect_faces.s(image_id=image_id)
| detect_faces_callback.s(image_id=image_id)).delay()
return Response({"status": "ok"}, status=status.HTTP_202_ACCEPTED)
else:
if not request.FILES.get("image", None):
return Response({'`image` is required'},
status=status.HTTP_400_BAD_REQUEST)
return Response(image_serializer.errors,
status=status.HTTP_400_BAD_REQUEST)
def post(self, request, *args, **kwargs):
device_id = request.POST.get('device_id')
min_temperature = request.POST.get('min_temperature')
max_temperature = request.POST.get('max_temperature')
# image_id = str(uuid.uuid4())
num_imgs = Image_object.objects.filter(device_id=device_id).count()
if (num_imgs > 1000): # max buffering images
num_imgs = 0
imageid = "{:05d}".format(num_imgs)
photo_filename = upload_photo_image(request, device_id, imageid)
thermal_filename = upload_thermal_image(request, device_id, imageid)
name, ext = os.path.splitext(photo_filename)
photo_preprocessed_filename = name + '_pre' + ext
photo_output_filename = name + '_out' + ext
name, ext = os.path.splitext(thermal_filename)
thermal_preprocessed_filename = name + '_pre' + ext
thermal_output_filename = name + '_out' + ext
### Check if the image_id is already exist in the database
image_object = None
try:
image_object = Image_object.objects.filter(
device_id=device_id).get(image_id=imageid)
except Image_object.DoesNotExist:
image_object = None
if image_object: # update the record in the database
image_object.device_id = device_id
image_object.image_id = imageid
image_object.min_temperature = min_temperature
image_object.max_temperature = max_temperature
image_object.photo_filename = photo_filename
image_object.thermal_filename = thermal_filename
image_object.photo_preprocessed_filename = photo_preprocessed_filename
image_object.thermal_preprocessed_filename = thermal_preprocessed_filename
image_object.photo_output_filename = photo_output_filename
image_object.thermal_output_filename = thermal_output_filename
image_object.status = ''
image_object.date_created = datetime.now()
image_object.save()
else: # create a new record in the database
image = Image_object()
image.device_id = device_id
image.image_id = imageid
image.min_temperature = min_temperature
image.max_temperature = max_temperature
image.photo_filename = photo_filename
image.thermal_filename = thermal_filename
image.photo_preprocessed_filename = photo_preprocessed_filename
image.thermal_preprocessed_filename = thermal_preprocessed_filename
image.photo_output_filename = photo_output_filename
image.thermal_output_filename = thermal_output_filename
image.status = ''
image.save()
# detect_faces.s(device_id=device_id, image_id=imageid).delay()
chain(
preprocessing_image.s(device_id=device_id, image_id=imageid)
| detect_faces.s(device_id=device_id, image_id=imageid)
| form_bounding_boxes.s(device_id=device_id, image_id=imageid)
).delay()
return Response({"status": "ok"}, status=status.HTTP_202_ACCEPTED)
