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HEAT / s3d_preprocess /sem_seg_utils.py

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	import numpy as np

	wall_type = 1
	floor_type = 2
	ceil_type = 22

	SCANNET_COLORMAP = [
	[0., 0., 0.],
	[174., 199., 232.],
	[152., 223., 138.],
	[31., 119., 180.],
	[255., 187., 120.],
	[188., 189., 34.],
	[140., 86., 75.],
	[255., 152., 150.],
	[214., 39., 40.],
	[197., 176., 213.],
	[148., 103., 189.],
	[196., 156., 148.],
	[23., 190., 207.],
	[247., 182., 210.],
	[66., 188., 102.],
	[219., 219., 141.],
	[140., 57., 197.],
	[202., 185., 52.],
	[51., 176., 203.],
	[200., 54., 131.],
	[92., 193., 61.],
	[78., 71., 183.],
	[172., 114., 82.],
	[255., 127., 14.],
	[91., 163., 138.],
	[153., 98., 156.],
	[140., 153., 101.],
	[158., 218., 229.],
	[100., 125., 154.],
	[178., 127., 135.],
	[146., 111., 194.],
	[44., 160., 44.],
	[112., 128., 144.],
	[96., 207., 209.],
	[227., 119., 194.],
	[213., 92., 176.],
	[94., 106., 211.],
	[82., 84., 163.],
	[100., 85., 144.]]

	SCANNET_COLORMAP = np.asarray(SCANNET_COLORMAP) / 255.

	class_names = []
	class_name_to_id = {}
	for i, line in enumerate(open("label_names.txt").readlines()):
	class_id = i # starts with -1
	class_name = line.strip()
	class_name_to_id[class_name] = class_id
	class_names.append(class_name)
	class_names = tuple(class_names)

	# color palette for nyu40 labels
	def create_color_palette():
	return [
	(0, 0, 0),
	(174, 199, 232), # wall
	(152, 223, 138), # floor
	(31, 119, 180), # cabinet
	(255, 187, 120), # bed
	(188, 189, 34), # chair
	(140, 86, 75), # sofa
	(255, 152, 150), # table
	(214, 39, 40), # door
	(197, 176, 213), # window
	(148, 103, 189), # bookshelf
	(196, 156, 148), # picture
	(23, 190, 207), # counter
	(178, 76, 76),
	(247, 182, 210), # desk
	(66, 188, 102),
	(219, 219, 141), # curtain
	(140, 57, 197),
	(202, 185, 52),
	(51, 176, 203),
	(200, 54, 131),
	(92, 193, 61),
	(78, 71, 183),
	(172, 114, 82),
	(255, 127, 14), # refrigerator
	(91, 163, 138),
	(153, 98, 156),
	(140, 153, 101),
	(158, 218, 229), # shower curtain
	(100, 125, 154),
	(178, 127, 135),
	(120, 185, 128),
	(146, 111, 194),
	(44, 160, 44), # toilet
	(112, 128, 144), # sink
	(96, 207, 209),
	(227, 119, 194), # bathtub
	(213, 92, 176),
	(94, 106, 211),
	(82, 84, 163), # otherfurn
	(100, 85, 144)
	]