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/mlsd.py

@@ -0,0 +1,31 @@
+from ..utils import common_annotator_call, define_preprocessor_inputs, INPUT
+import comfy.model_management as model_management
+import numpy as np
+
+class MLSD_Preprocessor:
+    @classmethod
+    def INPUT_TYPES(s):
+        return define_preprocessor_inputs(
+            score_threshold=INPUT.FLOAT(default=0.1, min=0.01, max=2.0),
+            dist_threshold=INPUT.FLOAT(default=0.1, min=0.01, max=20.0),
+            resolution=INPUT.RESOLUTION()
+        )
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "execute"
+
+    CATEGORY = "ControlNet Preprocessors/Line Extractors"
+
+    def execute(self, image, score_threshold, dist_threshold, resolution=512, **kwargs):
+        from custom_controlnet_aux.mlsd import MLSDdetector
+
+        model = MLSDdetector.from_pretrained().to(model_management.get_torch_device())
+        out = common_annotator_call(model, image, resolution=resolution, thr_v=score_threshold, thr_d=dist_threshold)
+        return (out, )
+
+NODE_CLASS_MAPPINGS = {
+    "M-LSDPreprocessor": MLSD_Preprocessor
+}
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "M-LSDPreprocessor": "M-LSD Lines"
+}