{"action":"created","issue":{"url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1438","repository_url":"https://api.github.com/repos/NVIDIA/DIGITS","labels_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1438/labels{/name}","comments_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1438/comments","events_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1438/events","html_url":"https://github.com/NVIDIA/DIGITS/issues/1438","id":205508895,"number":1438,"title":"Some questions about Image Segmentation using Digits 5 ","user":{"login":"4575759ww","id":22930904,"avatar_url":"https://avatars.githubusercontent.com/u/22930904?v=3","gravatar_id":"","url":"https://api.github.com/users/4575759ww","html_url":"https://github.com/4575759ww","followers_url":"https://api.github.com/users/4575759ww/followers","following_url":"https://api.github.com/users/4575759ww/following{/other_user}","gists_url":"https://api.github.com/users/4575759ww/gists{/gist_id}","starred_url":"https://api.github.com/users/4575759ww/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/4575759ww/subscriptions","organizations_url":"https://api.github.com/users/4575759ww/orgs","repos_url":"https://api.github.com/users/4575759ww/repos","events_url":"https://api.github.com/users/4575759ww/events{/privacy}","received_events_url":"https://api.github.com/users/4575759ww/received_events","type":"User","site_admin":false},"labels":[{"id":188540314,"url":"https://api.github.com/repos/NVIDIA/DIGITS/labels/question","name":"question","color":"cc317c","default":true}],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":6,"created_at":"2017-02-06T07:49:51Z","updated_at":"2017-02-12T09:51:28Z","closed_at":null,"body":"Hi, I have worked with FCN models for image segmentation using digits 5, my dataset is about UAV remote sensing images, and I labeled them, all images are spilted into 512*512. However, the result is not good, and the network is indiscriminately classifying everything as one class which is crop with 48% accuracy,   and also, I have tested the Sythina dataset, the network has just learnt to achieve 35% accuracy by labeling everything as building.\r\n\r\nSo how could I deal with this problem, I have read the article \"Image Segmentation Using DIGITS 5\",but I’m having trouble understanding the part: transfer learning. I have downloaded the FCN-Alexnet caffemodel as pre-trained caffe model, but it doesn't work in increasing accuracy, so If there are other methods to deal with the question by adjusting some parameters or  something else? \r\n\r\nHope your feedback and advice! Thanks\r\n"},"comment":{"url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/comments/279207594","html_url":"https://github.com/NVIDIA/DIGITS/issues/1438#issuecomment-279207594","issue_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1438","id":279207594,"user":{"login":"4575759ww","id":22930904,"avatar_url":"https://avatars.githubusercontent.com/u/22930904?v=3","gravatar_id":"","url":"https://api.github.com/users/4575759ww","html_url":"https://github.com/4575759ww","followers_url":"https://api.github.com/users/4575759ww/followers","following_url":"https://api.github.com/users/4575759ww/following{/other_user}","gists_url":"https://api.github.com/users/4575759ww/gists{/gist_id}","starred_url":"https://api.github.com/users/4575759ww/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/4575759ww/subscriptions","organizations_url":"https://api.github.com/users/4575759ww/orgs","repos_url":"https://api.github.com/users/4575759ww/repos","events_url":"https://api.github.com/users/4575759ww/events{/privacy}","received_events_url":"https://api.github.com/users/4575759ww/received_events","type":"User","site_admin":false},"created_at":"2017-02-12T09:51:28Z","updated_at":"2017-02-12T09:51:28Z","body":"@gheinrich ,when I test one image which size is 4096*4096 or 2048*2048 in the last , there is no output image with warning : list index out of range.  when the size of  input source image is 1024*1024, I can obtain the output  inference visualization image , so could you please tell me the reason for these results?"}}
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