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Hi,
Thanks for your code, and after I ran the slow network to predict the trainingH datasets, I got much worser results than the results displayed on the Middlebury website, I wonder where I did something wrong, can you help me out ?
The command is as follows: ./main.lua mb slow -a predict -net_fname net/net_mb_slow_-a_train_all.t7 -left im0.png -right im1.png -disp_max 190
And one of the results can be compared as follows: The error rate(nocc) for Vintage by running the code is 34% while the result of Vintage image on Middlebury (MC-CNN-acrt ) is 24.8%.
Do I miss something important? Thanks a lot !
The text was updated successfully, but these errors were encountered:
@shuluoshu Hello, i set disp_max to 380. Unlike the official result, the error is still very large. Can you solve this problem? if you address the problem, please tell me some detail.
Hi,
Thanks for your code, and after I ran the slow network to predict the trainingH datasets, I got much worser results than the results displayed on the Middlebury website, I wonder where I did something wrong, can you help me out ?
The command is as follows:
./main.lua mb slow -a predict -net_fname net/net_mb_slow_-a_train_all.t7 -left im0.png -right im1.png -disp_max 190
And one of the results can be compared as follows: The error rate(nocc) for Vintage by running the code is 34% while the result of Vintage image on Middlebury (MC-CNN-acrt ) is 24.8%.
Do I miss something important? Thanks a lot !
The text was updated successfully, but these errors were encountered: