rapisurazurite / camodiffusion Goto Github PK

train.py中通过如下代码构建了模型：
cond_uvit = instantiate_from_config(cfg.cond_uvit, conditioning_klass=get_obj_from_str(cfg.cond_uvit.params.conditioning_klass)) model = recurse_instantiate_from_config(cfg.model, unet=cond_uvit) diffusion_model = instantiate_from_config(cfg.diffusion_model, model=model)
其中cond_uvit模块的构建参数都是model.net.EmptyObject这个空函数，是否可以理解为模型并没有用到CondUViT这个类呢？如果我的理解有误请您解答一下这三行代码是如何构建出最终的模型的，感谢。
我的邮箱是[email protected],我对您的工作很感兴趣，希望可以与您交流。

Hi, according to the code of train.py and the file config/dataset_352x352.yaml, are the training sets in the five datasets COD10K, CAMO, CHAMELEON, NC4K, and CDS2K combined for training?

def get_loader(cfg):
train_dataset = instantiate_from_config(cfg.train_dataset)
train_loader = DataLoader(
train_dataset,
batch_size=cfg.batch_size,
shuffle=True,
num_workers=cfg.num_workers)

test_dataset = instantiate_from_config(cfg.test_dataset.CAMO)
test_dataset_expand = SampleDataset(full_dataset=instantiate_from_config(cfg.test_dataset.COD10K), interval=10)
test_dataset = torch.utils.data.ConcatDataset([test_dataset, test_dataset_expand])
test_dataset_expand = SampleDataset(full_dataset=instantiate_from_config(cfg.test_dataset.NC4K), interval=30)
test_dataset = torch.utils.data.ConcatDataset([test_dataset, test_dataset_expand])

test_loader = DataLoader(
    test_dataset,
    batch_size=cfg.batch_size,
    collate_fn=collate
)
return train_loader, test_loader

如果是的话，那么生成过程中还需要gt参与吗？