Allow weighting of input data
This essentially allows you to give some datasets more importance than others for the purposes of reaching a more refined network.
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@ -29,7 +29,7 @@ class LQGTDataset(data.Dataset):
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self.paths_PIX, self.sizes_PIX = None, None
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self.LQ_env, self.GT_env, self.PIX_env = None, None, None # environments for lmdbs
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self.paths_GT, self.sizes_GT = util.get_image_paths(self.data_type, opt['dataroot_GT'])
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self.paths_GT, self.sizes_GT = util.get_image_paths(self.data_type, opt['dataroot_GT'], opt['dataroot_GT_weights'])
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if 'dataroot_LQ' in opt.keys():
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self.paths_LQ = []
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if isinstance(opt['dataroot_LQ'], list):
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@ -42,7 +42,7 @@ def _get_paths_from_lmdb(dataroot):
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return paths, sizes
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def get_image_paths(data_type, dataroot):
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def get_image_paths(data_type, dataroot, weights=[]):
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"""get image path list
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support lmdb or image files"""
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paths, sizes = None, None
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@ -52,7 +52,14 @@ def get_image_paths(data_type, dataroot):
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elif data_type == 'img':
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if isinstance(dataroot, list):
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paths = []
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for r in dataroot:
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for i in range(len(dataroot)):
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r = dataroot[i]
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extends = 1
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# Weights have the effect of repeatedly adding the paths from the given root to the final product.
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if weights:
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extends = weights[i]
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for j in range(extends):
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paths.extend(_get_paths_from_images(r))
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paths = sorted(paths)
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else:
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