Add output PIL rather than file.

app.py

@@ -1,4 +1,5 @@
 import torch
+from torchvision import transforms
 import gradio as gr
 from random import randint
 from pathlib import Path
@@ -42,14 +43,14 @@ def inference(img, scale_str, model_name):
  _id = randint(1, 1000)
  output_dir = Path('./tmp/')
  output_dir.mkdir(parents=True, exist_ok=True)
- output_file = output_dir / ('output_image' + str(_id) + '.jpg')
+ # output_file = output_dir / ('output_image' + str(_id) + '.jpg')
  scale = int(scale_str.replace('x', ''))
  model = get_model(model_name, scale)
  inputs = ImageLoader.load_image(img)
  preds = model(inputs)
- output_file_str = str(output_file.resolve())
- ImageLoader.save_image(preds, output_file_str)
- return output_file_str
+ # output_file_str = str(output_file.resolve())
+ # ImageLoader.save_image(preds, output_file_str)
+ return transforms.ToPILImage(mode='RGB')(preds)
 
 
 torch.hub.download_url_to_file('http://people.rennes.inria.fr/Aline.Roumy/results/images_SR_BMVC12/input_groundtruth/baby_mini_d3_gaussian.bmp',
@@ -70,7 +71,7 @@ gr.Interface(
  gr.inputs.Dropdown(choices=models,
  label='Model')
  ],
- gr.outputs.Image(type="file", label="Output"),
+ gr.outputs.Image(type="pil", label="Output"),
  title=title,
  description=description,
  article=article,