(-215:Assertion failed) !ssize.empty() in function 'resize'

[Linda-L]

/home/ll/anaconda3/envs/t1.2/bin/python /media/ll/L/Efficient-Segmentation-Networks/train.py 1.2 =====> input size:(512, 1024) Namespace(batch_size=4, classes=19, cuda=True, dataset='cityscapes', gpus='0', input_size='512,1024', logFile='log.txt', lr=0.0005, lr_schedule='warmpoly', max_epochs=1000, model='FastSCNN', num_cycles=1, num_workers=4, optim='adam', poly_exp=0.9, random_mirror=True, random_scale=True, resume='', savedir='./checkpoint/', train_type='trainval', use_focal=True, use_label_smoothing=False, use_lovaszsoftmax=False, use_ohem=False, warmup_factor=0.3333333333333333, warmup_iters=500) =====> use gpu id: '0' =====> set Global Seed: 1234 =====> building network =====> computing network parameters and FLOPs the number of parameters: 1138051 ==> 1.14 M find file: ./dataset/inform/cityscapes_inform.pkl length of dataset: 122 length of dataset: 59 =====> Dataset statistics data['classWeights']: [ 1.4705521 9.505282 10.492059 10.492059 10.492059 10.492059 10.492059 10.492059 10.492059 10.492059 10.492059 10.492059 10.492059 10.492059 10.492059 10.492059 10.492059 10.492059 5.131664 ] mean and std: [72.3924 82.90902 73.158325] [45.319206 46.15292 44.91484 ] single GPU for training =====> beginning training =====> the number of iterations per epoch: 30 Traceback (most recent call last): File "/media/ll/L/Efficient-Segmentation-Networks/train.py", line 401, in train_model(args) File "/media/ll/L/Efficient-Segmentation-Networks/train.py", line 218, in train_model lossTr, lr = train(args, trainLoader, model, criteria, optimizer, epoch) File "/media/ll/L/Efficient-Segmentation-Networks/train.py", line 301, in train for iteration, batch in enumerate(train_loader, 0): File "/home/ll/anaconda3/envs/t1.2/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 819, in next return self._process_data(data) File "/home/ll/anaconda3/envs/t1.2/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 846, in _process_data data.reraise() File "/home/ll/anaconda3/envs/t1.2/lib/python3.7/site-packages/torch/_utils.py", line 369, in reraise raise self.exc_type(msg) cv2.error: Caught error in DataLoader worker process 0. Original Traceback (most recent call last): File "/home/ll/anaconda3/envs/t1.2/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop data = fetcher.fetch(index) File "/home/ll/anaconda3/envs/t1.2/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/ll/anaconda3/envs/t1.2/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in data = [self.dataset[idx] for idx in possibly_batched_index] File "/media/ll/L/Efficient-Segmentation-Networks/dataset/cityscapes.py", line 64, in getitem label = cv2.resize(label, None, fx=f_scale, fy=f_scale, interpolation=cv2.INTER_NEAREST) cv2.error: OpenCV(4.5.1) /tmp/pip-req-build-7m_g9lbm/opencv/modules/imgproc/src/resize.cpp:4051: error: (-215:Assertion failed) !ssize.empty() in function 'resize'

Process finished with exit code 1

[GitHubmalajava]

I use the dataset is cityscapes but have a error: ValueError: num_samples should be a positive integer value, but got num_samples=0 .what should be do