semantic-segmentation-pytorch
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AssertionError: Torch not compiled with CUDA enabled
Dear all, I am trying to the Section "Quick start: Test on an image using our trained model".
[2020-06-09 12:28:55,641 INFO test.py line 172 138659] Loaded configuration file config/ade20k-resnet50dilated-ppm_deepsup.yaml [2020-06-09 12:28:55,642 INFO test.py line 173 138659] Running with config: DATASET: imgMaxSize: 1000 imgSizes: (300, 375, 450, 525, 600) list_train: ./data/training.odgt list_val: ./data/validation.odgt num_class: 150 padding_constant: 8 random_flip: True root_dataset: ./data/ segm_downsampling_rate: 8 DIR: ade20k-resnet50dilated-ppm_deepsup MODEL: arch_decoder: ppm_deepsup arch_encoder: resnet50dilated fc_dim: 2048 weights_decoder: weights_encoder: TEST: batch_size: 1 checkpoint: epoch_20.pth result: ./ TRAIN: batch_size_per_gpu: 2 beta1: 0.9 deep_sup_scale: 0.4 disp_iter: 20 epoch_iters: 5000 fix_bn: False lr_decoder: 0.02 lr_encoder: 0.02 lr_pow: 0.9 num_epoch: 20 optim: SGD seed: 304 start_epoch: 0 weight_decay: 0.0001 workers: 16 VAL: batch_size: 1 checkpoint: epoch_20.pth visualize: False Loading weights for net_encoder Loading weights for net_decoder
samples: 1
Traceback (most recent call last):
File "test.py", line 198, in
And my laptop is Ubuntu 20.04 without GPU. How can I fix this issue? Many thanks!