Upload app.py

app.py

@@ -70,9 +70,9 @@ class SAMAPI:
  def get_instance(sam_checkpoint=None):
  if SAMAPI.predictor is None:
  if sam_checkpoint is None:
- sam_checkpoint = "tmp/sam_vit_h_4b8939.pth"
+ sam_checkpoint = "./sam_pt/sam_vit_h_4b8939.pth"
  if not os.path.exists(sam_checkpoint):
- os.makedirs('tmp', exist_ok=True)
+ os.makedirs('sam_pt', exist_ok=True)
  urllib.request.urlretrieve(
  "https://dl.fbaipublicfiles.com/segment_anything/sam_vit_h_4b8939.pth",
  sam_checkpoint
@@ -353,8 +353,6 @@ with results_container:
  torch.manual_seed(seed)
  img = Image.open(pic)
 
- data = prepare_data(img)
-
  if max(img.size) > 1280:
  w, h = img.size
  w = round(1280 / max(img.size) * w)
@@ -374,6 +372,7 @@ with results_container:
  img = expand2square(img, (127, 127, 127, 0))
  # pipeline.set_progress_bar_config(disable=True)
  prog.progress(0.3, "Run cross-domain diffusion model")
+ data = prepare_data(img)
  normals_pred, images_pred = run_pipeline(pipeline, data, cfg_scale, seed)
  prog.progress(0.9, "finishing")
  left, right = st.columns(2)