LUCAS M MORGAN
dfd7e68cbb
Merge LoadSharpModel and SharpPredict into this pack; register all nodes from __init__.py. Bundle web/js/gsplat-bundle.js and resolve viewer load via import.meta.url. Add LICENSE, THIRD_PARTY_NOTICES, and GPL-3.0 text. Update README and requirements (huggingface-hub). Remove GeometryPack runtime dependency for the WebGL viewer. Made-with: Cursor
40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
"""Image conversion utilities for ComfyUI-Sharp."""
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import numpy as np
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import torch
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def comfy_to_numpy_rgb(image_tensor: torch.Tensor) -> np.ndarray:
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"""Convert ComfyUI image tensor to numpy RGB array.
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Args:
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image_tensor: ComfyUI image tensor with shape [B, H, W, C] in range [0, 1].
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Returns:
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Numpy array with shape [H, W, C] in range [0, 255] as uint8.
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"""
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if image_tensor.dim() == 4:
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img = image_tensor[0] # Take first image from batch
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else:
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img = image_tensor
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img_np = img.cpu().numpy()
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img_np = (img_np * 255).astype(np.uint8)
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return img_np
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def convert_focallength(width: float, height: float, f_mm: float = 30.0) -> float:
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"""Convert focal length from mm (35mm film equivalent) to pixels.
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Args:
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width: Image width in pixels.
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height: Image height in pixels.
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f_mm: Focal length in mm (35mm film equivalent). Default 30mm.
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Returns:
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Focal length in pixels.
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"""
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# 35mm film dimensions: 36mm x 24mm
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return f_mm * np.sqrt(width**2 + height**2) / np.sqrt(36**2 + 24**2)
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