45 lines
1.7 KiB
Python
45 lines
1.7 KiB
Python
from .builder import ITEMS
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from .clothing import Clothing
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import random
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@ITEMS.register_module()
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class Bag(Clothing):
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def __init__(self, **kwargs):
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pipeline = [
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dict(type='LoadImageFromFile', path=kwargs['path'], color=kwargs['color']),
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dict(type='KeypointDetection'),
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dict(type='ContourDetection'),
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dict(type='Painting'),
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dict(type='Scaling'),
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dict(type='Split'),
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# dict(type='ImageShow', key=['image', 'mask', 'pattern_image']),
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]
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kwargs.update(pipeline=pipeline)
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super(Bag, self).__init__(**kwargs)
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@staticmethod
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def calculate_start_point(keypoint_type, scale, clothes_point, body_point):
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"""
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align left
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Args:
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keypoint_type: string, "hand_point"
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scale: float
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clothes_point: dict{'left': [x1, y1, z1], 'right': [x2, y2, z2]}
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body_point: dict, containing keypoint data of body figure
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Returns:
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start_point: tuple (y', x')
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x' = y_body - y1 * scale
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y' = x_body - x1 * scale
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"""
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location = random.choice(seq=['left', 'right'])
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if location == 'left':
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side_indicator = f'{keypoint_type}_left'
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else:
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side_indicator = f'{keypoint_type}_right'
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# clothes_point = {k: tuple(map(lambda x: int(scale * x), v[0: 2])) for k, v in clothes_point.items()}
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start_point = (body_point[side_indicator][1] - int(int(clothes_point[keypoint_type].split("_")[1]) * scale),
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body_point[side_indicator][0] - int(int(clothes_point[keypoint_type].split("_")[0]) * scale))
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return start_point
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