<jupyter_start><jupyter_text>Config / Load Model<jupyter_code>device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')

num_classes = DENSE.num_classes()
model = WeatherNet(num_classes)
model.load_state_dict(torch.load('checkpoints/model_epoch2_mIoU=73.7.pth'))
model.eval()<jupyter_output><empty_output><jupyter_text>Load in Sample File<jupyter_code>sample_file = 'data/DENSE/test_01/2018-11-29_114626_Static2-Day-Clear/LidarImage_000000607.hdf5'
sample_file = h5py.File(sample_file, 'r')

#distance = sample_file['distance_m_1']
#reflexivity = sample_file['intensity_1']

output = model(sample_file, 1)
#prediction = torch.argmax(output)<jupyter_output><empty_output>
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