Update app.py

app.py

@@ -1,20 +1,21 @@
 import gradio as gr
 from transformers import pipeline
+import base64
+from PIL import Image
+import io
 
-# Cargamos un modelo real de detección de emociones faciales
 model = pipeline("image-classification", model="dima806/facial_emotions_image_detection")
 
-def predict_emotion(image):
-    # El modelo procesa la imagen y devuelve una lista de etiquetas y puntajes
+def predict_emotion(image_b64: str):
+    image_data = base64.b64decode(image_b64.split(",")[1] if "," in image_b64 else image_b64)
+    image = Image.open(io.BytesIO(image_data)).convert("RGB")
     predictions = model(image)
-    return predictions
+    return [[{"label": p["label"], "score": p["score"]} for p in predictions]]
 
-# Creamos la interfaz que tu Android consumirá
 demo = gr.Interface(
     fn=predict_emotion,
-    inputs=gr.Image(type="pil"),
+    inputs=gr.Textbox(),
     outputs="json",
-    api_name="predict_emotion"
+    api_name="predict"
 )
-
-demo.launch()
+demo.launch()