forked from mrq/DL-Art-School
test w/o GT
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@ -11,6 +11,7 @@ class LQDataset(data.Dataset):
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def __init__(self, opt):
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super(LQDataset, self).__init__()
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self.opt = opt
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self.data_type = self.opt['data_type']
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self.paths_LQ, self.paths_GT = None, None
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self.LQ_env = None # environment for lmdb
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@ -27,7 +28,7 @@ class LQDataset(data.Dataset):
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LQ_path = None
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# get LQ image
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LQ_path = self.LQ_path[index]
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LQ_path = self.paths_LQ[index]
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resolution = [int(s) for s in self.sizes_LQ[index].split('_')
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] if self.data_type == 'lmdb' else None
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img_LQ = util.read_img(self.LQ_env, LQ_path, resolution)
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26
codes/options/test/test_ESRGAN_woGT.yml
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26
codes/options/test/test_ESRGAN_woGT.yml
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@ -0,0 +1,26 @@
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name: RRDB_ESRGAN_x4
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suffix: ~ # add suffix to saved images
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model: sr
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distortion: sr
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scale: 4
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crop_border: ~ # crop border when evaluation. If None(~), crop the scale pixels
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gpu_ids: [0]
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datasets:
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test_1: # the 1st test dataset
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name: set14
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mode: LQ
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dataroot_LQ: ../datasets/val_set14/Set14_bicLRx4
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#### network structures
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network_G:
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which_model_G: RRDBNet
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in_nc: 3
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out_nc: 3
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nf: 64
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nb: 23
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upscale: 4
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#### path
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path:
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pretrain_model_G: ../experiments/pretrained_models/RRDB_ESRGAN_x4.pth
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