Update app.py

app.py

@@ -145,8 +145,7 @@ def param2img_serial(
                                            device=this_canvas.device)
         selected_alphas = torch.zeros(selected_param.shape[0], 3, patch_size_y, patch_size_x, device=this_canvas.device)
         if selected_param[selected_decision, :].shape[0] > 0:
-            selected_foregrounds[selected_decision, :, :, :], selected_alphas[selected_decision, :, :, :] = \
-                param2stroke(selected_param[selected_decision, :], patch_size_y, patch_size_x, meta_brushes)
+            selected_foregrounds[selected_decision, :, :, :], selected_alphas[selected_decision, :, :, :] = \\n                param2stroke(selected_param[selected_decision, :], patch_size_y, patch_size_x, meta_brushes)
         selected_foregrounds = selected_foregrounds.view(
             b, selected_h, selected_w, 3, patch_size_y, patch_size_x).contiguous()
         selected_alphas = selected_alphas.view(b, selected_h, selected_w, 3, patch_size_y, patch_size_x).contiguous()
@@ -516,8 +515,8 @@ def gradio_inference(image):
          model_path='model.pth',
          output_dir='output/',
          need_animation=True,  # whether need intermediate results for animation.
-         resize_h=512,         # resize original input to this size. None means do not resize.
-         resize_w=512,         # resize original input to this size. None means do not resize.
+         resize_h=400,         # resize original input to this size. None means do not resize.
+         resize_w=400,         # resize original input to this size. None means do not resize.
          serial=True)          # if need animation, serial must be True.
 
 title = "Anime2Sketch"