Add basic error handling on input.

app.py

@@ -46,11 +46,15 @@ def inference(img, scale_str, model_name):
     if width > 2048 or height > 2048:
         img = img.thumbnail((2048, 2048), Image.ANTIALIAS)
     model = get_model(model_name, scale)
-    inputs = ImageLoader.load_image(img)
-    preds = model(inputs)
-    preds = preds.data.cpu().numpy()
-    pred = preds[0].transpose((1, 2, 0)) * 255.0
-    return Image.fromarray(pred.astype('uint8'), 'RGB')
+    try:
+        inputs = ImageLoader.load_image(img)
+        preds = model(inputs)
+        preds = preds.data.cpu().numpy()
+        pred = preds[0].transpose((1, 2, 0)) * 255.0
+        return Image.fromarray(pred.astype('uint8'), 'RGB')
+    except Exception as e:
+        print(e)
+        return None
 
 
 torch.hub.download_url_to_file('http://people.rennes.inria.fr/Aline.Roumy/results/images_SR_BMVC12/input_groundtruth/baby_mini_d3_gaussian.bmp',