Add fix for output to PIL image.

app.py

@@ -46,13 +46,15 @@ def inference(img, scale_str, model_name):
     preds = preds.data.cpu().numpy()
     pred = preds[0].transpose((1, 2, 0)) * 255.0
     pred = cv2.cvtColor(pred, cv2.COLOR_BGR2RGB)
-    return Image.fromarray(pred)
+    return pred
 
 
 torch.hub.download_url_to_file('http://people.rennes.inria.fr/Aline.Roumy/results/images_SR_BMVC12/input_groundtruth/baby_mini_d3_gaussian.bmp',
                                'baby.bmp')
 torch.hub.download_url_to_file('http://people.rennes.inria.fr/Aline.Roumy/results/images_SR_BMVC12/input_groundtruth/woman_mini_d3_gaussian.bmp',
                                'woman.bmp')
+torch.hub.download_url_to_file('http://people.rennes.inria.fr/Aline.Roumy/results/images_SR_BMVC12/input_groundtruth/bird_mini_d4_gaussian.bmp',
+                               'bird.bmp')
 models = ['EDSR-base', 'DRLN', 'EDSR', 'MSRN', 'MDSR', 'AWSRN-BAM', 'A2N', 'CARN', 'PAN']
 scales = [2, 3, 4]
 for model_name in models:
@@ -73,7 +75,8 @@ gr.Interface(
     article=article,
     examples=[
         ['baby.bmp', 'x2', 'EDSR-base'],
-        ['woman.bmp', 'x3', 'DRLN']
+        ['woman.bmp', 'x3', 'DRLN'],
+        ['bird.bmp', 'x4', 'EDSR']
     ],
     enable_queue=True,
     allow_flagging=False,