text: import os
  import json
  
  import torch
  from PIL import Image
  from torchvision import transforms
  import matplotlib.pyplot as plt
  
  from model import swin_tiny_patch4_window7_224 as create_model
  
  
  def main():
      device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
  
      img_size = 224
      data_transform = transforms.Compose(
          [transforms.Resize(int(img_size * 1.14)),
           transforms.CenterCrop(img_size),
           transforms.ToTensor(),
           transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])])
  
      # load image
      img_path = "../tulip.jpg"
      assert os.path.exists(img_path), "file: '{}' dose not exist.".format(img_path)
      img = Image.open(img_path)
      plt.imshow(img)
      # [N, C, H, W]
      img = data_transform(img)
      # expand batch dimension
      img = torch.unsqueeze(img, dim=0)
  
      # read class_indict
      json_path = './class_indices.json'
      assert os.path.exists(json_path), "file: '{}' dose not exist.".format(json_path)
  
      json_file = open(json_path, "r")
      class_indict = json.load(json_file)
  
      # create model
      model = create_model(num_classes=5).to(device)
      # load model weights
      model_weight_path = "./weights/model-9.pth"
      model.load_state_dict(torch.load(model_weight_path, map_location=device))
      model.eval()
      with torch.no_grad():
          # predict class
          output = torch.squeeze(model(img.to(device))).cpu()
          predict = torch.softmax(output, dim=0)
          predict_cla = torch.argmax(predict).numpy()
  
      print_res = "class: {}   prob: {:.3}".format(class_indict[str(predict_cla)],
                                                   predict[predict_cla].numpy())
      plt.title(print_res)
      for i in range(len(predict)):
          print("class: {:10}   prob: {:.3}".format(class_indict[str(i)],
                                                    predict[i].numpy()))
      plt.show()
  
  
  if __name__ == '__main__':
      main()
  