Closed yyy809643573 closed 1 year ago
You can also try to resize to the training resolution for prediction and finally resize the output back to the original resolution (https://github.com/autonomousvision/unimatch/blob/master/evaluate_stereo.py#L782-L813).
thank you! I see that in the row 813 of evaluate_stereo.py is pred_disp = pred_disp * ori_size[-1] / float(inference_size[-1]), when resizing back, predicted disp is only considered in the width dimension, whether the height dimension is needed to consider,thank you!
No since the displacement in the vertical direction is 0.
how can I set the input size,when the new image size is not euqal with training data size, using padding or crop ? it seems that crop or padding will influence the stereo matching result,is there any general ways ?