Update handler.py

handler.py

@@ -56,23 +56,29 @@ 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(prob)
 	
 	# Mostrar resultado
 	if predicted_classes:
 		for prediction in predicted_classes:
 			print(prediction)
-		return predicted_classes    
+   
 	else:
 		# Si ninguna clase supera 0.5, mostrar la más probable
 		max_idx = probabilities.argmax()
 		max_prob = probabilities[max_idx]
 		class_name = class_info['class_columns'][max_idx]
 		print(f"{class_name}: {max_prob:.3f}")
-		return [class_name, max_prob]
+		predicted_list.append(class_name)
+		prob_list.append(max_prob)
+	return {"class": predicted_list, "accuracy":prob_list}	
 
 class EndpointHandler():
 	def __init__(self, path=""):