Update handler.py

handler.py

@@ -57,13 +57,11 @@ def classify_image(model, image_processor, class_info, device, image_url, accura
 	# Obtener clases predichas (umbral 0.5)
 	predicted_classes = []
 	predicted_list=[]
-	prob_list=[]
 	for i, prob in enumerate(probabilities):
 		if prob > accuracy:
 			class_name = class_info['class_columns'][i]
 			predicted_classes.append(f"{class_name}: {prob:.3f}")
-			predicted_list.append(class_name)
-			prob_list.append(float(prob))
+			predicted_list.append({"class": class_name, "confidence": float(prob)})
 	
 	# Mostrar resultado
 	if predicted_classes:
@@ -76,9 +74,8 @@ def classify_image(model, image_processor, class_info, device, image_url, accura
 		max_prob = probabilities[max_idx]
 		class_name = class_info['class_columns'][max_idx]
 		print(f"{class_name}: {max_prob:.3f}")
-		predicted_list.append(class_name)
-		prob_list.append(float(max_prob))
-	return {"class": predicted_list, "accuracy":prob_list}	
+		predicted_list.append({"class": class_name, "confidence": float(max_prob)})
+	return predicted_list
 
 class EndpointHandler():
 	def __init__(self, path=""):