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-Impact-Pack/modules/impact/impact_onnx.py

@@ -0,0 +1,39 @@
+import impact.additional_dependencies
+import numpy as np
+from impact import utils
+import logging
+
+impact.additional_dependencies.ensure_onnx_package()
+
+try:
+    import onnxruntime
+
+    def onnx_inference(image, onnx_model):
+        # prepare image
+        pil = utils.tensor2pil(image)
+        image = np.ascontiguousarray(pil)
+        image = image[:, :, ::-1]  # to BGR image
+        image = image.astype(np.float32)
+        image -= [103.939, 116.779, 123.68]  # 'caffe' mode image preprocessing
+
+        # do detection
+        onnx_model = onnxruntime.InferenceSession(onnx_model, providers=["CPUExecutionProvider"])
+        outputs = onnx_model.run(
+            [s_i.name for s_i in onnx_model.get_outputs()],
+            {onnx_model.get_inputs()[0].name: np.expand_dims(image, axis=0)},
+        )
+
+        labels = [op for op in outputs if op.dtype == "int32"][0]
+        scores = [op for op in outputs if isinstance(op[0][0], np.float32)][0]
+        boxes = [op for op in outputs if isinstance(op[0][0], np.ndarray)][0]
+
+        # filter-out useless item
+        idx = np.where(labels[0] == -1)[0][0]
+
+        labels = labels[0][:idx]
+        scores = scores[0][:idx]
+        boxes = boxes[0][:idx].astype(np.uint32)
+
+        return labels, scores, boxes
+except Exception:
+    logging.error("[Impact Pack] ComfyUI-Impact-Pack: 'onnxruntime' package doesn't support 'python 3.11', yet.\t{e}")