Fix4

app.py

@@ -1,19 +1,18 @@
 import gradio as gr
-from fastbook import load_learner
-from PIL import Image
+from fastbook import PILImage, load_learner
 
 labels = [
-    'Tom Cruise', 'Dwayne Johnson', 'Tom Hanks', 'Brad Pitt',
-    'Denzel Washington', 'Julia Roberts', 'Will Smith', 'Leonardo DiCaprio',
-    'Johnny Depp',  'Kevin Hart', 'Keanu Reeves', 'Sandra Bullock',
-    'Ryan Reynolds', 'Adam Sandler', 'Harrison Ford', 'George Clooney',
-    'Robert Downey Jr', 'Angelina Jolie', 'Morgan Freeman', 'Chris Hemsworth',
+    'Adam Sandler', 'Angelina Jolie', 'Brad Pitt', 'Chris Hemsworth',
+    'Denzel Washington', 'Dwayne Johnson', 'George Clooney', 'Harrison Ford',
+    'Johnny Depp', 'Julia Roberts', 'Keanu Reeves', 'Kevin Hart',
+    'Leonardo DiCaprio', 'Morgan Freeman', 'Robert Downey Jr', 'Ryan Reynolds',
+    'Sandra Bullock', 'Tom Cruise', 'Tom Hanks', 'Will Smith',
 ]
 
 
 def predict(img):
     learn = load_learner("convnext_small.pkl")
-    img = Image.create(img)
+    img = PILImage.create(img)
     learn.predict(img)
     pred, pred_idx, probs = learn.predict(img)
     return {labels[i]: float(probs[i]) for i in range(len(labels))}