Update app.py

app.py

@@ -7,9 +7,13 @@ import gradio as gr
     
 # Definimos una función que se encarga de llevar a cabo las predicciones
 def predict(img):
-    #img = PILImage.create(img)
-    #pred,pred_idx,probs = learn.predict(img)
     return 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)
+    return pred_dict['img']
+    #return img
     
 # Creamos la interfaz y la lanzamos. 
 gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(128, 128)), outputs=gr.outputs.Image(label='Imagen resultado'),examples=['00001.jpg','00002.jpg']).launch(share=False)