liyiersan

Baidu Cloud Disk fort BraTS2018 dataset: https://pan.baidu.com/s/1vyhPa1z_LJm6IMOUNGKHhA code：vt99

Well, in test function, the size of pred_out is [batch_size*4,1,128,128], so firstly you should change it into the shape of [160,180,batch_size]. And this can be done by function prediction_syn_results, and...

 这样在选择时间、地址的时候会比较方便一点

感谢感谢

@DegardinBruno I hope this works for you. I provide an example of loading a pre-trained vit-base. Please refer to https://github.com/liyiersan/MSA/blob/22243186133369941bb78bbd93e6e2cd04317f66/models/vit.py#L133-L211. or you can refer to https://github.com/Sebastian-X/vit-pytorch-with-pretrained-weights.

Hi, @shahJaimin77 , I met some problems when calculating metrics on windows , did the evaluate_predicts.py work for on Windows?

Comment out the load pretrain in the train.py file like this: ```python # net.load_from(weights=np.load(config_vit.pretrained_path)) # load pretrain ```

My codes to test 2D slice with 3channels: ```python def test_single_volume(image, label, net, classes, patch_size=[256, 256], test_save_path=None, case=None, z_spacing=1): image, label = image.squeeze(0).cpu().detach().numpy(), label.squeeze(0).cpu().detach().numpy() slice = image[:] # 3, h,...

The errors may happen when data argumentation, an easy way to solve this is that zoom first and argumentation later. Change the code like this: ```python class RandomGenerator(object): def __init__(self,...

> it seems that the problem cames out not only yolov8 ultralytics with paddleocr, but also paddlepaddle-gpu with torch. Is there any possible way to fix this. Try to reinstall...