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The mask is currently calculated by looking at the first HMI image and selecting where pixels > 0:
pixels > 0
hmi = torch.Tensor(self.hmi_data[2010][ALL_COMPONENTS[0]][0]) hmi_mask = (torch.abs(hmi) > 0.0).to(dtype=torch.uint8) hmi_mask_ratio = hmi_mask.sum().item() / hmi_mask.numel()
When applied to AIA this looked to be too agressive when reprojected:
This will be worth revisiting if we wish to focus on limb activity.
The text was updated successfully, but these errors were encountered:
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The mask is currently calculated by looking at the first HMI image and selecting where
pixels > 0
:When applied to AIA this looked to be too agressive when reprojected:
This will be worth revisiting if we wish to focus on limb activity.
The text was updated successfully, but these errors were encountered: