{"action":"created","issue":{"url":"https://api.github.com/repos/MaybeShewill-CV/lanenet-lane-detection/issues/18","repository_url":"https://api.github.com/repos/MaybeShewill-CV/lanenet-lane-detection","labels_url":"https://api.github.com/repos/MaybeShewill-CV/lanenet-lane-detection/issues/18/labels{/name}","comments_url":"https://api.github.com/repos/MaybeShewill-CV/lanenet-lane-detection/issues/18/comments","events_url":"https://api.github.com/repos/MaybeShewill-CV/lanenet-lane-detection/issues/18/events","html_url":"https://github.com/MaybeShewill-CV/lanenet-lane-detection/issues/18","id":338830100,"node_id":"MDU6SXNzdWUzMzg4MzAxMDA=","number":18,"title":"speed","user":{"login":"mosjoker","id":40882852,"node_id":"MDQ6VXNlcjQwODgyODUy","avatar_url":"https://avatars2.githubusercontent.com/u/40882852?v=4","gravatar_id":"","url":"https://api.github.com/users/mosjoker","html_url":"https://github.com/mosjoker","followers_url":"https://api.github.com/users/mosjoker/followers","following_url":"https://api.github.com/users/mosjoker/following{/other_user}","gists_url":"https://api.github.com/users/mosjoker/gists{/gist_id}","starred_url":"https://api.github.com/users/mosjoker/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mosjoker/subscriptions","organizations_url":"https://api.github.com/users/mosjoker/orgs","repos_url":"https://api.github.com/users/mosjoker/repos","events_url":"https://api.github.com/users/mosjoker/events{/privacy}","received_events_url":"https://api.github.com/users/mosjoker/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":7,"created_at":"2018-07-06T07:11:57Z","updated_at":"2018-11-14T03:19:37Z","closed_at":"2018-07-20T05:11:58Z","author_association":"NONE","body":"hi,i tested the model  on GTX-1080 , but i found it's too slow approaching 1 fps.\r\n\"The deep neural network inference part can achieve around a 50fps\"--can u tell me the reason?\r\nthank you,@MaybeShewill-CV "},"comment":{"url":"https://api.github.com/repos/MaybeShewill-CV/lanenet-lane-detection/issues/comments/438523526","html_url":"https://github.com/MaybeShewill-CV/lanenet-lane-detection/issues/18#issuecomment-438523526","issue_url":"https://api.github.com/repos/MaybeShewill-CV/lanenet-lane-detection/issues/18","id":438523526,"node_id":"MDEyOklzc3VlQ29tbWVudDQzODUyMzUyNg==","user":{"login":"derekwong66","id":26414519,"node_id":"MDQ6VXNlcjI2NDE0NTE5","avatar_url":"https://avatars0.githubusercontent.com/u/26414519?v=4","gravatar_id":"","url":"https://api.github.com/users/derekwong66","html_url":"https://github.com/derekwong66","followers_url":"https://api.github.com/users/derekwong66/followers","following_url":"https://api.github.com/users/derekwong66/following{/other_user}","gists_url":"https://api.github.com/users/derekwong66/gists{/gist_id}","starred_url":"https://api.github.com/users/derekwong66/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/derekwong66/subscriptions","organizations_url":"https://api.github.com/users/derekwong66/orgs","repos_url":"https://api.github.com/users/derekwong66/repos","events_url":"https://api.github.com/users/derekwong66/events{/privacy}","received_events_url":"https://api.github.com/users/derekwong66/received_events","type":"User","site_admin":false},"created_at":"2018-11-14T03:19:37Z","updated_at":"2018-11-14T03:19:37Z","author_association":"NONE","body":"@MaybeShewill-CV  I tried 32 and 8. seems not different.\r\nbatch 32:\r\nI1114 11:16:56.971650 29045 test_lanenet.py:196] [Epoch:6] 预处理32张图像, 共耗时: 0.49305s, 平均每张耗时: 0.01541\r\nI1114 11:17:12.432114 29045 test_lanenet.py:203] [Epoch:6] 预测32张图像车道线, 共耗时: 15.46036s, 平均每张耗时: 0.48314s\r\nI1114 11:17:13.926787 29045 test_lanenet.py:233] [Epoch:6] 进行32张图像车道线聚类, 共耗时: 0.41856s, 平均每张耗时: 0.01308\r\n\r\nbatch 8:\r\nI1114 11:19:20.011592 29256 test_lanenet.py:186] [Epoch:9] 开始图像读取和预处理...\r\nI1114 11:19:20.177321 29256 test_lanenet.py:196] [Epoch:9] 预处理8张图像, 共耗时: 0.16567s, 平均每张耗时: 0.02071\r\nI1114 11:19:24.116097 29256 test_lanenet.py:203] [Epoch:9] 预测8张图像车道线, 共耗时: 3.93867s, 平均每张耗时: 0.49233s\r\nI1114 11:19:24.546752 29256 test_lanenet.py:233] [Epoch:9] 进行8张图像车道线聚类, 共耗时: 0.08357s, 平均每张耗时: 0.01045"}}
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