Update app.py

app.py

@@ -6,10 +6,6 @@ import gradio as gr
 # Cargamos el learner
 learn = load_learner('model.pth')
 
-# Definimos las etiquetas de nuestro modelo
-labels = learn.dls.vocab
-
-
 # Definimos una función que se encarga de llevar a cabo las predicciones
 def predict(img):
     class_map = ['Kangaroo']
@@ -20,7 +16,7 @@ def predict(img):
     infer_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(size),tfms.A.Normalize()])
     
     img = PIL.Image.open('kangarooc.jpg')
-    pred_dict  = models.torchvision.faster_rcnn.end2end_detect(img, infer_tfms, learn.model.to("cpu"), class_map=class_map, detection_threshold=0.5)
+    pred_dict  = models.torchvision.faster_rcnn.end2end_detect(img, infer_tfms, model.to("cpu"), class_map=class_map, detection_threshold=0.5)
     return pred_dict['img']
     
 # Creamos la interfaz y la lanzamos.