{"action":"opened","issue":{"url":"https://api.github.com/repos/opencv/opencv/issues/10467","repository_url":"https://api.github.com/repos/opencv/opencv","labels_url":"https://api.github.com/repos/opencv/opencv/issues/10467/labels{/name}","comments_url":"https://api.github.com/repos/opencv/opencv/issues/10467/comments","events_url":"https://api.github.com/repos/opencv/opencv/issues/10467/events","html_url":"https://github.com/opencv/opencv/issues/10467","id":285153379,"number":10467,"title":"Inconsistent return type from CascadeClassifier.detectMultiScale in Python","user":{"login":"orenht","id":18380832,"avatar_url":"https://avatars0.githubusercontent.com/u/18380832?v=4","gravatar_id":"","url":"https://api.github.com/users/orenht","html_url":"https://github.com/orenht","followers_url":"https://api.github.com/users/orenht/followers","following_url":"https://api.github.com/users/orenht/following{/other_user}","gists_url":"https://api.github.com/users/orenht/gists{/gist_id}","starred_url":"https://api.github.com/users/orenht/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/orenht/subscriptions","organizations_url":"https://api.github.com/users/orenht/orgs","repos_url":"https://api.github.com/users/orenht/repos","events_url":"https://api.github.com/users/orenht/events{/privacy}","received_events_url":"https://api.github.com/users/orenht/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2017-12-29T20:48:36Z","updated_at":"2017-12-29T20:48:36Z","closed_at":null,"author_association":"NONE","body":"##### System information (version)\r\n\r\n- OpenCV =>  3.3.1\r\n- Operating System / Platform => Windows 10 64 Bit\r\n- Compiler =>Python 3.6.3\r\n\r\n##### Detailed description\r\n\r\nin CascadeClassifier.detectMultiScale, I expected the library to return an empty ndarray when there is no detection.\r\nThe library returns a single empty tuple when there is NO detection, and a numpy.ndarray when there are detections.\r\n"}}
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