Update app.py

app.py

@@ -108,7 +108,7 @@ def inference(image, upscale, large_input_flag, color_fix):
 	if upscale is None or not isinstance(upscale, (int, float)) or upscale == 3.:
 		upscale = 2
 		
-	upscale = int(upscale) # convert type to int
+	upscale = int(upscale)
 
 	model = set_safmn(upscale)
 
@@ -116,7 +116,7 @@ def inference(image, upscale, large_input_flag, color_fix):
 	# print(f'input size: {img.shape}')
 
 	# img2tensor
-	y = image.astype(np.float32) / 255.
+	y = np.array(image).astype(np.float32) / 255.
 	y = torch.from_numpy(np.transpose(y[:, :, [2, 1, 0]], (2, 0, 1))).float()
 	y = y.unsqueeze(0).to(device)