Add custom nodes, Civitai loras (LFS), and vast.ai setup script

Includes 30 custom nodes committed directly, 7 Civitai-exclusive
loras stored via Git LFS, and a setup script that installs all
dependencies and downloads HuggingFace-hosted models on vast.ai.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

custom_nodes/comfyui_controlnet_aux/node_wrappers/dsine.py

@@ -0,0 +1,31 @@
+from ..utils import common_annotator_call, define_preprocessor_inputs, INPUT
+import comfy.model_management as model_management
+
+class DSINE_Normal_Map_Preprocessor:
+    @classmethod
+    def INPUT_TYPES(s):
+        return define_preprocessor_inputs(
+            fov=INPUT.FLOAT(max=365.0, default=60.0),
+            iterations=INPUT.INT(min=1, max=20, default=5),
+            resolution=INPUT.RESOLUTION()
+        )
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "execute"
+
+    CATEGORY = "ControlNet Preprocessors/Normal and Depth Estimators"
+
+    def execute(self, image, fov=60.0, iterations=5, resolution=512, **kwargs):
+        from custom_controlnet_aux.dsine import DsineDetector
+
+        model = DsineDetector.from_pretrained().to(model_management.get_torch_device())
+        out = common_annotator_call(model, image, fov=fov, iterations=iterations, resolution=resolution)
+        del model
+        return (out,)
+
+NODE_CLASS_MAPPINGS = {
+    "DSINE-NormalMapPreprocessor": DSINE_Normal_Map_Preprocessor
+}
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "DSINE-NormalMapPreprocessor": "DSINE Normal Map"
+}