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+Only tested on
+* Anaconda3
+* Python 3.7.1
+* PyTorch 1.0.1

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+* Change the ```evaluate/gt.zip``` if you test on other datasets.
+* Modify the parameters in ```eval.py``` and run:
+```
+CUDA_VISIBLE_DEVICES=0 python eval.py

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+## [EAST Description](#contents)

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+				layers += [conv2d, nn.ReLU(inplace=True)]
+				# layers += [conv2d, nn.ReLU(inplace=False)]	# for graph mode accelerating
+			in_channels = v
+	return nn.ModuleList(layers)

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+
+	device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+	model = EAST(False).to(device)
+	model.load_state_dict(torch.load(model_name, map_location='cpu'))

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+	
+	device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+	model = EAST().to(device)
+	model.load_state_dict(torch.load(model_path, map_location='cpu'))

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+from PIL import Image
+import math
+import os
+from msadapter.pytorch.utils import data