Closed puyiwen closed 1 year ago
For evaluation, inverse depth norm is required. You can find the procedure in inference.py
inv_prediction = self.model(image)
prediction = self.inverse_depth_norm(inv_prediction)
max_depths = {
'kitti': 80.0,
'nyu' : 10.0,
'nyu_reduced' : 10.0,
}
def inverse_depth_norm(self, depth):
depth = self.maxDepth / depth
depth = torch.clamp(depth, self.maxDepth / 100, self.maxDepth)
return depth ```
The output of the network is a predicted depth value, so what post-processing is needed to obtain the true depth value?Thank you very much!!