debuggin huggin

app.py

@@ -84,10 +84,10 @@ try:
 except:
     pass
 
-try:
-    from interrogate import Interrogator
-except:
-    Interrogator = DummyInterrogator
+# try:
+#     from interrogate import Interrogator
+# except:
+#     Interrogator = DummyInterrogator
 
 USE_NEW_DIFFUSERS = True
 RUN_IN_SPACE = "RUN_IN_HG_SPACE" in os.environ
@@ -887,25 +887,25 @@ def run_outpaint(
 ):
     data = base64.b64decode(str(sel_buffer_str))
     pil = Image.open(io.BytesIO(data))
-    if interrogate_mode:
-        if "interrogator" not in model:
-            model["interrogator"] = Interrogator()
-        interrogator = model["interrogator"]
-        # possible point to integrate
-        img = np.array(pil)[:, :, 0:3]
-        mask = np.array(pil)[:, :, -1]
-        x, y = np.nonzero(mask)
-        if len(x) > 0:
-            x0, x1 = x.min(), x.max() + 1
-            y0, y1 = y.min(), y.max() + 1
-            img = img[x0:x1, y0:y1, :]
-        pil = Image.fromarray(img)
-        interrogate_ret = interrogator.interrogate(pil)
-        return (
-            gr.update(value=",".join([sel_buffer_str]),),
-            gr.update(label="Prompt", value=interrogate_ret),
-            state,
-        )
+    # if interrogate_mode:
+    #     if "interrogator" not in model:
+    #         model["interrogator"] = Interrogator()
+    #     interrogator = model["interrogator"]
+    #     # possible point to integrate
+    #     img = np.array(pil)[:, :, 0:3]
+    #     mask = np.array(pil)[:, :, -1]
+    #     x, y = np.nonzero(mask)
+    #     if len(x) > 0:
+    #         x0, x1 = x.min(), x.max() + 1
+    #         y0, y1 = y.min(), y.max() + 1
+    #         img = img[x0:x1, y0:y1, :]
+    #     pil = Image.fromarray(img)
+    #     interrogate_ret = interrogator.interrogate(pil)
+    #     return (
+    #         gr.update(value=",".join([sel_buffer_str]),),
+    #         gr.update(label="Prompt", value=interrogate_ret),
+    #         state,
+    #     )
     width, height = pil.size
     sel_buffer = np.array(pil)
     cur_model = get_model()