Update app.py

app.py

@@ -36,8 +36,9 @@ labels = [
 ]
 
 def classify_image(image):
+    # Redimensionar la imagen a (224, 224) antes de la predicción
     image = tf.image.resize(image, (224, 224))
-    image = tf.expand_dims(image, axis=0)
+    image = tf.expand_dims(image, axis=0)  # Añadir una dimensión para el batch
     prediction = model.predict(image).flatten()
     confidences = {labels[i]: float(prediction[i]) for i in range(len(labels))}
     return confidences
@@ -97,7 +98,8 @@ gr.Interface(
     title=title,
     article=article,
     description=description,
-    inputs=gr.Image(shape=(224, 224)),
+    inputs=gr.Image(),
     outputs=gr.Label(num_top_classes=4),
     examples=examples
 ).launch()
+