text: from torchvision import transforms
  import json
  
  class Preprocessador:
      def __init__(self):
          self.preprocessamento = transforms.Compose([
                              transforms.Resize(256),
                              transforms.CenterCrop(224),
                              transforms.ToTensor(),
                              transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
                          ])
      def executa(self, imagem):
          return self.preprocessamento(imagem)
  
  # Obtem o label de acordo com o indice melhor classificado.
  def getLabel(index):
      class_idx = json.load(open("./labels/imagenet_class_index.json"))
      idx2label = [class_idx[str(k)][1] for k in range(len(class_idx))]
      return idx2label[index]
  