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deep-text-recognition-benchmark
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Mapping loaded, pretrained model to actual device. Required for CPU only inference.

This commit is contained in:
akarazniewicz 2019-11-11 12:36:06 +01:00
parent 603d463e83
commit be128d4d9f
2 changed files with 2 additions and 2 deletions
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2
demo.py
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@ -30,7 +30,7 @@ def demo(opt):
# load model
print('loading pretrained model from %s' % opt.saved_model)
model.load_state_dict(torch.load(opt.saved_model))
model.load_state_dict(torch.load(opt.saved_model, map_location=device))
# prepare data. two demo images from https://github.com/bgshih/crnn#run-demo
AlignCollate_demo = AlignCollate(imgH=opt.imgH, imgW=opt.imgW, keep_ratio_with_pad=opt.PAD)

2
test.py
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@ -165,7 +165,7 @@ def test(opt):
# load model
print('loading pretrained model from %s' % opt.saved_model)
model.load_state_dict(torch.load(opt.saved_model))
model.load_state_dict(torch.load(opt.saved_model, map_location=device))
opt.experiment_name = '_'.join(opt.saved_model.split('/')[1:])
# print(model)