{"action":"created","issue":{"url":"https://api.github.com/repos/yu4u/age-gender-estimation/issues/48","repository_url":"https://api.github.com/repos/yu4u/age-gender-estimation","labels_url":"https://api.github.com/repos/yu4u/age-gender-estimation/issues/48/labels{/name}","comments_url":"https://api.github.com/repos/yu4u/age-gender-estimation/issues/48/comments","events_url":"https://api.github.com/repos/yu4u/age-gender-estimation/issues/48/events","html_url":"https://github.com/yu4u/age-gender-estimation/issues/48","id":345523742,"node_id":"MDU6SXNzdWUzNDU1MjM3NDI=","number":48,"title":"Age accuracy issues - For both IMDB and UTK","user":{"login":"idanh","id":614496,"node_id":"MDQ6VXNlcjYxNDQ5Ng==","avatar_url":"https://avatars2.githubusercontent.com/u/614496?v=4","gravatar_id":"","url":"https://api.github.com/users/idanh","html_url":"https://github.com/idanh","followers_url":"https://api.github.com/users/idanh/followers","following_url":"https://api.github.com/users/idanh/following{/other_user}","gists_url":"https://api.github.com/users/idanh/gists{/gist_id}","starred_url":"https://api.github.com/users/idanh/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/idanh/subscriptions","organizations_url":"https://api.github.com/users/idanh/orgs","repos_url":"https://api.github.com/users/idanh/repos","events_url":"https://api.github.com/users/idanh/events{/privacy}","received_events_url":"https://api.github.com/users/idanh/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":34,"created_at":"2018-07-29T11:36:44Z","updated_at":"2018-11-12T17:21:55Z","closed_at":null,"author_association":"NONE","body":"Hi,\r\n\r\nI've been doing some simple analysis over both pre-trained models, validating using appa-real dataset.\r\nHere's what I'm doing:\r\n\r\nFor each cropped and rotated image i.e. (_face.jpg) prefix:\r\n- Resize it to 256x256\r\n- Create 2 copies of each image, one is gray scaled and the other RGB\r\n- For each of those, I pass them through dlib frontal face detector,\r\n- If needed, for UTK I crop the face (margin=0) and with IMDB I'm giving it some margin of .4 (default in your code), for the margin part I did grid search and found that those values work (also noted in your documentations and I'm assuming after seeing UTKFaces that that's the way the models were trained)\r\n- At prediction step the image is begin resized to 64x64, this part is a copy-paste from demo.py code\r\n\r\nNote that I'm using real_age as supplied by appa dataset and not the expected value of apperent_age.\r\nIn total I've sampled 1978 images, I see that:\r\n\r\n- Both models are struggling with younger and older ages, imdb handles it a bit better for some reasons (which I still yet to check why, I have assumptions tho.) and the range I'm getting from both is around 12-68 where the domain of my ages are 0 to 100.\r\n- Using gray scaled images, even tho at least with UTK I'm assuming was trained with color images, is giving better results.\r\n\r\nI'm attaching some plots I've done, where my goal is to find if either I'm doing something incorrectly or maybe the accuracy is just off a bit? Maybe best to re-train on another dataset?\r\n\r\n![screen shot 2018-07-29 at 14 35 37](https://user-images.githubusercontent.com/614496/43365902-b72312a4-933c-11e8-9820-8626a34801bb.png)\r\n\r\n![screen shot 2018-07-29 at 14 35 41](https://user-images.githubusercontent.com/614496/43365903-bb38fc6e-933c-11e8-8a4a-5476f0f4b21d.png)\r\n\r\n![screen shot 2018-07-29 at 14 35 46](https://user-images.githubusercontent.com/614496/43365905-bd5317b4-933c-11e8-85e7-199d764d7ef6.png)\r\n\r\n![screen shot 2018-07-29 at 14 35 49](https://user-images.githubusercontent.com/614496/43365906-bfd10b0e-933c-11e8-96f8-bdbdc1d9d459.png)\r\n\r\nAgain, thank you @yu4u for this project, I'm assuming I'm at fault here. Would love to get your feedback."},"comment":{"url":"https://api.github.com/repos/yu4u/age-gender-estimation/issues/comments/437962322","html_url":"https://github.com/yu4u/age-gender-estimation/issues/48#issuecomment-437962322","issue_url":"https://api.github.com/repos/yu4u/age-gender-estimation/issues/48","id":437962322,"node_id":"MDEyOklzc3VlQ29tbWVudDQzNzk2MjMyMg==","user":{"login":"yu4u","id":618466,"node_id":"MDQ6VXNlcjYxODQ2Ng==","avatar_url":"https://avatars0.githubusercontent.com/u/618466?v=4","gravatar_id":"","url":"https://api.github.com/users/yu4u","html_url":"https://github.com/yu4u","followers_url":"https://api.github.com/users/yu4u/followers","following_url":"https://api.github.com/users/yu4u/following{/other_user}","gists_url":"https://api.github.com/users/yu4u/gists{/gist_id}","starred_url":"https://api.github.com/users/yu4u/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/yu4u/subscriptions","organizations_url":"https://api.github.com/users/yu4u/orgs","repos_url":"https://api.github.com/users/yu4u/repos","events_url":"https://api.github.com/users/yu4u/events{/privacy}","received_events_url":"https://api.github.com/users/yu4u/received_events","type":"User","site_admin":false},"created_at":"2018-11-12T17:21:55Z","updated_at":"2018-11-12T17:21:55Z","author_association":"OWNER","body":"I tried sigma = 2, 3, 4 and found 3 is the best choice."}}
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