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File "D:\A\segmentation\PIDNet-main\tools..\utils\utils.py", line 42, in forward
ph, pw = outputs[0].size(2), outputs[0].size(3)
IndexError: Dimension out of range (expected to be in range of [-3, 2], but got 3)
base_size and crop_size :512*512
IMAGE_SIZE:
512
512
BASE_SIZE: 512
Not using pre-trained models, the model in train.py:
model = models.pidnet.get_pred_model(config,6)
Is this error caused by the size of the image?
The text was updated successfully, but these errors were encountered:
Hello, have you encountered a situation during training where the loss doesn't converge, and both semantic loss and sb loss remain consistently at zero? If not, could you provide details on how you set the parameters during training?
We use our own data to train .
File "D:\A\segmentation\PIDNet-main\tools..\utils\utils.py", line 42, in forward
ph, pw = outputs[0].size(2), outputs[0].size(3)
IndexError: Dimension out of range (expected to be in range of [-3, 2], but got 3)
base_size and crop_size :512*512
IMAGE_SIZE:
BASE_SIZE: 512
Not using pre-trained models, the model in train.py:
model = models.pidnet.get_pred_model(config,6)
Is this error caused by the size of the image?
The text was updated successfully, but these errors were encountered: