libranet
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train dataset
Hi, can you explain more on the ground truth file (.csv in your preprocessed training dataset)? From my understanding, you divide the whole image into 32*32 patches and corresponding count value. So each element in the csv file represents its patch count and its patch relative location. Am I correct? For example: I use $ cat 9.csv and it shows: 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 1,5,14,20,23,16,5,1,10,1,12,23,32,36,40,42 37,37,40,42,39,39,44,44,40,42,39,45,45,47,42,44 26,29,20,20,19,23,23,27,22,22,29,27,32,32,30,30
Moreover, can you release the pre-process code? So people can train the model on other dataset. Thank you so much!