{"action":"closed","issue":{"url":"https://api.github.com/repos/apache/incubator-mxnet/issues/7406","repository_url":"https://api.github.com/repos/apache/incubator-mxnet","labels_url":"https://api.github.com/repos/apache/incubator-mxnet/issues/7406/labels{/name}","comments_url":"https://api.github.com/repos/apache/incubator-mxnet/issues/7406/comments","events_url":"https://api.github.com/repos/apache/incubator-mxnet/issues/7406/events","html_url":"https://github.com/apache/incubator-mxnet/issues/7406","id":249205782,"number":7406,"title":"inconsistent accuracy: ImageRecordIter vs ImageIter","user":{"login":"melody-rain","id":2832736,"avatar_url":"https://avatars2.githubusercontent.com/u/2832736?v=4","gravatar_id":"","url":"https://api.github.com/users/melody-rain","html_url":"https://github.com/melody-rain","followers_url":"https://api.github.com/users/melody-rain/followers","following_url":"https://api.github.com/users/melody-rain/following{/other_user}","gists_url":"https://api.github.com/users/melody-rain/gists{/gist_id}","starred_url":"https://api.github.com/users/melody-rain/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/melody-rain/subscriptions","organizations_url":"https://api.github.com/users/melody-rain/orgs","repos_url":"https://api.github.com/users/melody-rain/repos","events_url":"https://api.github.com/users/melody-rain/events{/privacy}","received_events_url":"https://api.github.com/users/melody-rain/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":6,"created_at":"2017-08-10T01:16:56Z","updated_at":"2017-11-13T12:26:30Z","closed_at":"2017-11-13T12:26:30Z","author_association":"CONTRIBUTOR","body":"ImageRecordIter gets much better accuracy. Any reasons for that?\r\n```\r\ndata = mx.io.ImageRecordIter(\r\n        data_name          = 'data',\r\n        label_name         = 'softmax_label',\r\n        path_imgrec        = data_val,\r\n        label_width        = 1,\r\n        data_shape         = data_shape,\r\n        batch_size         = batch_size,\r\n        mean_r             = rgb_mean[0],\r\n        mean_g             = rgb_mean[1],\r\n        mean_b             = rgb_mean[2],\r\n        )\r\n\r\ndata = mx.image.ImageIter(\r\n        data_name='data',\r\n        label_name='softmax_label',\r\n        path_imgrec=data_val,\r\n        label_width=1,\r\n        data_shape=data_shape,\r\n        batch_size=batch_size,\r\n        mean = np.ndarray(shape=(3, 1, 1), buffer=np.array(rgb_mean)),\r\n    )\r\n```"}}
{"actor":{"display_login":"szha"}}