github
html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | issue | performed_via_github_app |
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https://github.com/dogsheep/dogsheep-photos/issues/14#issuecomment-620771698 | https://api.github.com/repos/dogsheep/dogsheep-photos/issues/14 | 620771698 | MDEyOklzc3VlQ29tbWVudDYyMDc3MTY5OA== | 9599 | 2020-04-28T18:13:48Z | 2020-04-28T18:13:48Z | MEMBER | For face detection: ``` {"type": vision.enums.Feature.Type.Type.FACE_DETECTION} ``` For OCR: ``` {"type": vision.enums.Feature.Type.DOCUMENT_TEXT_DETECTION} ``` | { "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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https://github.com/dogsheep/dogsheep-photos/issues/14#issuecomment-620772190 | https://api.github.com/repos/dogsheep/dogsheep-photos/issues/14 | 620772190 | MDEyOklzc3VlQ29tbWVudDYyMDc3MjE5MA== | 9599 | 2020-04-28T18:14:43Z | 2020-04-28T18:14:43Z | MEMBER | Database schema for this will require some thought. Just dumping the output into a JSON column isn't going to be flexible enough - I want to be able to FTS against labels and OCR text, and potentially query against other characteristics too. | { "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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https://github.com/dogsheep/dogsheep-photos/issues/14#issuecomment-620774507 | https://api.github.com/repos/dogsheep/dogsheep-photos/issues/14 | 620774507 | MDEyOklzc3VlQ29tbWVudDYyMDc3NDUwNw== | 9599 | 2020-04-28T18:19:06Z | 2020-04-28T18:19:06Z | MEMBER | The default timeout is a bit aggressive and sometimes failed for me if my resizing proxy took too long to fetch and resize the image. `client.annotate_image(..., timeout=3.0)` may be worth trying. | { "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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