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Update nodes.py
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nodes.py
37
nodes.py
@ -3364,6 +3364,27 @@ def interpolate_coordinates(coordinates_dict, batch_size):
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return interpolated
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from scipy.interpolate import CubicSpline
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import numpy as np
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def interpolate_coordinates_with_curves(coordinates_dict, batch_size):
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sorted_coords = sorted(coordinates_dict.items())
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x_coords, y_coords = zip(*[coord for index, coord in sorted_coords])
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# Create the spline curve functions
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indices = np.array([index for index, coord in sorted_coords])
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cs_x = CubicSpline(indices, x_coords)
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cs_y = CubicSpline(indices, y_coords)
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# Generate interpolated coordinates using the spline functions
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interpolated_indices = np.arange(0, batch_size)
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interpolated_x = cs_x(interpolated_indices)
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interpolated_y = cs_y(interpolated_indices)
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# Round the interpolated coordinates and create the dictionary
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interpolated = {i: (round(x), round(y)) for i, (x, y) in enumerate(zip(interpolated_x, interpolated_y))}
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return interpolated
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def plot_to_tensor(coordinates_dict, interpolated_dict, height, width, box_size):
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from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
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import matplotlib.patches as patches
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@ -3411,6 +3432,14 @@ class GLIGENTextBoxApplyBatch:
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"width": ("INT", {"default": 64, "min": 8, "max": MAX_RESOLUTION, "step": 8}),
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"height": ("INT", {"default": 64, "min": 8, "max": MAX_RESOLUTION, "step": 8}),
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"coordinates": ("STRING", {"multiline": True}),
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"interpolation": (
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[
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'straight',
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'CubicSpline',
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],
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{
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"default": 'CubicSpline'
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}),
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}}
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RETURN_TYPES = ("CONDITIONING", "IMAGE",)
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FUNCTION = "append"
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@ -3419,7 +3448,7 @@ class GLIGENTextBoxApplyBatch:
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def append(self, latents, conditioning_to, clip, gligen_textbox_model, text, width, height, coordinates):
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def append(self, latents, conditioning_to, clip, gligen_textbox_model, text, width, height, coordinates, interpolation):
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coordinates_dict = parse_coordinates(coordinates)
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batch_size = sum(tensor.size(0) for tensor in latents.values())
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@ -3427,7 +3456,11 @@ class GLIGENTextBoxApplyBatch:
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cond, cond_pooled = clip.encode_from_tokens(clip.tokenize(text), return_pooled=True)
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# Interpolate coordinates for the entire batch
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interpolated_coords = interpolate_coordinates(coordinates_dict, batch_size)
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if interpolation == 'CubicSpline':
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interpolated_coords = interpolate_coordinates_with_curves(coordinates_dict, batch_size)
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if interpolation == 'straight':
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interpolated_coords = interpolate_coordinates(coordinates_dict, batch_size)
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plot_image_tensor = plot_to_tensor(coordinates_dict, interpolated_coords, 512, 512, height)
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for t in conditioning_to:
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n = [t[0], t[1].copy()]
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