Comments (1)
Here (XNet-TF.Keras) is the XNet updated with tf 2.x
. However, I'm using it just for casual stuff and so I only use keras
official EfficientNet as an encoder. But other models can be integrated.
@MrGiovanni thanks for such concise implementation of unet++ in keras
. One request, could you please consider adding XNet
and NestNet
to the qubvel/segmentation_models. The keras
implementation of these two is missing there and not has been included yet. I think If it's included it surely will reach many practitioners to use xnet and nestnet models arch. Also, qubel repo is updated with tf 2.x
. But the good thing is there is nothing big code changing is needed on your side and others. Please let me know if there's any known issue regarding this.
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Related Issues (20)
- Task058 have RuntimeError: Given transposed=1, weight of size [128, 64, 1, 2, 2], expected input[2, 64, 16, 160, 160] to have 128 channels, but got 64 channels instead HOT 8
- The detail of paper HOT 2
- Getting very bad validation metrics HOT 2
- how to train on my designated GPU? HOT 1
- Can this model be trained on multi GPUs ?
- importlib_metadata.PackageNotFoundError: No package metadata was found for nnunet HOT 1
- 周学长您好,我在配置环境中发现个小坑想提醒大家
- RuntimeError: Given transposed=1, weight of size [256, 128, 2, 2], expected input[12, 64, 256, 256] to have 256 channels, but got 64 channels instead HOT 2
- 您好!请问pytorch官方实现版提供的LITS预训练模型,是关闭deep_supervision跑的么 HOT 7
- Question : why use " l = weights[0] * self.loss(x[-1], y[0])" in loss_functions/deep_supervision.py ?
- issue in resize_segmentation HOT 3
- 'unet_final_features' referenced before assignment HOT 1
- Generic_UNetPlusPlus测试报错
- legacy_upsampling2d_support
- How to Train on nnunet 2d mode?
- PermissionError: [Errno 13] Permission denied: '/media/yang/nnUNet_raw_data_base'
- AttributeError: 'Generic_UNetPlusPlus' object has no attribute 'upsample_mode'
- Pre-trained model
- UNetPlusPlus如何基于自定义数据集完成实例分割任务?(而不是语义分割)
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