MIC-DKFZ / nnDetection

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Hi,
Can data enhancement be turned off during prediction？
When the statement “transformed= transform(**batch)” is executed, I save the result of “batch[0]” and the result of "transformed[0]", and find that they are exactly the same, as if the transformation did not work. As follows：

`
def predict_with_transformation(self,
model: AbstractModel,
batch: Dict,
batch_num: int,
transform: Callable,
inverse_transform: Callable,
):
"""
Run prediction with the specified transformations

    Args:
        model: model to predict
        batch: input batch to model
        batch_num: batch index
        transform: transform to apply to batch.
        inverse_transform: inverse transform to apply to batch and resuls
    """
    batch = to_device(batch, device=self.device)
    if self.pre_transform is not None:
        batch = self.pre_transform(**batch)

    x1 = batch['data'].cpu().numpy()[0]
    Data = np.squeeze(x1)
    tem = sitk.GetImageFromArray(Data)
    sitk.WriteImage(tem, "batch0.nii.gz")

    transformed = transform(**batch)

    t1 = transformed['data'].cpu().numpy()[0]
    Data1 = np.squeeze(t1)
    tem1 = sitk.GetImageFromArray(Data1)
    sitk.WriteImage(tem1, "transformed0.nii.gz")

`
Thank you!
Lynclock

It is possible to disable TTA in the inference commands. Regarding your observation:

nnDetection/nndet/inference/transforms.py

Lines 38 to 39 in 06c2eb4

    
           transforms = [NoOp()] 
        
           inverse_transforms = [NoOp()]

The first transform is intended to perform "nothing" and the remaining transforms will mirror the data in the different directions.

I see.Thank you!

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[Question]Can data enhancement be turned off during prediction？

❓ Question