Update app.py

app.py

@@ -3,15 +3,30 @@ import torch
 import numpy as np
 from PIL import Image
 from huggingface_hub import hf_hub_download
+from fastai.vision.all import *
 
-# Descargar modelo TorchScript
+# --- Clases dummy necesarias para deserializar ---
+class TargetMaskConvertTransform(ItemTransform):
+    def encodes(self, x): return x
+
+class SegmentationAlbumentationsTransform(ItemTransform):
+    def __init__(self, aug=None): pass
+    def encodes(self, x): return x
+
+def get_y_fn(x): return x
+def ParentSplitter(x): return x
+
+# --- Descargar modelo ---
 REPO_ID = "rugarce/model_practica3"
 FILENAME = "model.pkl"
 
 model_path = hf_hub_download(repo_id=REPO_ID, filename=FILENAME)
-model = torch.jit.load(model_path, map_location="cpu")
+
+learn = load_learner(model_path, cpu=True)
+model = learn.model
 model.eval()
 
+# --- Inferencia simple ---
 def predict(image):
     image = image.resize((640,480))
     image = np.array(image).astype(np.float32) / 255.0
@@ -30,4 +45,4 @@ demo = gr.Interface(
     title="Segmentación U-Net",
 )
 
-demo.launch()
+demo.launch()