Fix RMBG loading with torch.device(cpu) context; fix None fallback alpha shape [1,1,H,W]

app.py

@@ -197,13 +197,13 @@ def load_triposg():
     _ip_path = triposg_src / "scripts" / "image_process.py"
     if _ip_path.exists():
         _ip_text = _ip_path.read_text()
-        if "rmbg_net_none_guard" not in _ip_text:
+        if "rmbg_net_none_guard_v2" not in _ip_text:
             _ip_text = _ip_text.replace(
                 "        # seg from rmbg\n        alpha_gpu_rmbg = rmbg(rgb_image_resized)",
                 "        # seg from rmbg\n"
-                "        if rmbg_net is None:  # rmbg_net_none_guard\n"
+                "        if rmbg_net is None:  # rmbg_net_none_guard_v2\n"
                 "            alpha_gpu_rmbg = torch.ones(\n"
-                "                1, rgb_image_resized.shape[1], rgb_image_resized.shape[2],\n"
+                "                1, 1, rgb_image_resized.shape[1], rgb_image_resized.shape[2],\n"
                 "                device=rgb_image_resized.device)\n"
                 "        else:\n"
                 "            alpha_gpu_rmbg = rmbg(rgb_image_resized)",
@@ -249,9 +249,14 @@ def load_triposg():
 
     try:
         from transformers import AutoModelForImageSegmentation
-        _rmbg_net = AutoModelForImageSegmentation.from_pretrained(
-            "1038lab/RMBG-2.0", trust_remote_code=True
-        )
+        # torch.device('cpu') context forces all tensor creation to real CPU memory,
+        # bypassing any meta-device context left active by TripoSGPipeline loading.
+        # BiRefNet's __init__ creates Config() instances and calls eval() on class
+        # names — these fire during meta-device init and crash with .item() errors.
+        with torch.device("cpu"):
+            _rmbg_net = AutoModelForImageSegmentation.from_pretrained(
+                "1038lab/RMBG-2.0", trust_remote_code=True, low_cpu_mem_usage=False
+            )
         torch.set_float32_matmul_precision("high")
         _rmbg_net.to(DEVICE)
         _rmbg_net.eval()