Update app.py

app.py

@@ -6,7 +6,7 @@ import PIL
 from PIL import Image
 
 # Cargamos el learner
-model= torch.load('fasterRCNNKangaroo_obligatorio.pth',map_location='cpu')
+learner = torch.load('fasterRCNNKangaroo_obligatorio.pth',map_location='cpu')
     
 # Definimos una función que se encarga de llevar a cabo las predicciones
 def predict(img):
@@ -14,7 +14,7 @@ def predict(img):
     size = 384
     class_map = ClassMap(['kangaroo'])
     infer_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(size),tfms.A.Normalize()])
-    pred_dict  = models.torchvision.faster_rcnn.end2end_detect(img, infer_tfms, model.to("cpu"), class_map=class_map, detection_threshold=0.5)
+    pred_dict  = models.torchvision.faster_rcnn.end2end_detect(img, infer_tfms, learner.to("cpu"), class_map=class_map, detection_threshold=0.5)
     #return pred_dict['img']
     return img