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Hi, @dong03
sorry to disturb you, I find that MVSSNet is baseline model in TIANCHI challenge round1.
I wonder if checkpoint provided is only training on this dataset.
If so, there are all fake images, how you train model in this condition.
By the way, when will MVSSNet's training script is available? (open source when TIANCHI challenge round is over?)
To reproduce this repo, we need to generate edge map first to train edge_loss, but even if we have know cv2.findContours is used, it's still hard to reproduce.
I use default setting in opencv functions, but the edge extraction result is so bad. The normal process of edge extract as follow:
bgr2gray
generate binary image, use cv2.threshold to do this.
cv2.findContours also has some setting.
Considering above these setting unknown, it is hard to reproduce your result.
Can you share some code only about edge map extraction process?
I don't think the disclosure of these pre-processing codes will directly affect your benefit.
wishing for your reply and thanks again.
The text was updated successfully, but these errors were encountered:
Hi, @dong03
sorry to disturb you, I find that MVSSNet is baseline model in TIANCHI challenge round1.
I wonder if checkpoint provided is only training on this dataset.
If so, there are all fake images, how you train model in this condition.
By the way, when will MVSSNet's training script is available? (open source when TIANCHI challenge round is over?)
To reproduce this repo, we need to generate edge map first to train edge_loss, but even if we have know
cv2.findContours
is used, it's still hard to reproduce.I use default setting in opencv functions, but the edge extraction result is so bad. The normal process of edge extract as follow:
cv2.threshold
to do this.cv2.findContours
also has some setting.Considering above these setting unknown, it is hard to reproduce your result.
Can you share some code only about edge map extraction process?
I don't think the disclosure of these pre-processing codes will directly affect your benefit.
wishing for your reply and thanks again.
The text was updated successfully, but these errors were encountered: