issues

Table actions

11 rows where repo = 256834907, state = "open" and user = 9599 sorted by updated_at descending

✖
✖
✖
✖

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: comments, created_at (date), updated_at (date)

type 1

state 1

  • open · 11 ✖

repo 1

  • dogsheep-photos · 11 ✖
id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association pull_request body repo type active_lock_reason performed_via_github_app reactions draft state_reason
602533481 MDU6SXNzdWU2MDI1MzM0ODE= 3 Import EXIF data into SQLite - lens used, ISO, aperture etc simonw 9599 open 0   Apple Photos online and securely browsable 5324096 2 2020-04-18T19:24:31Z 2021-10-05T12:38:24Z   MEMBER  
dogsheep-photos 256834907 issue     
{
    "url": "https://api.github.com/repos/dogsheep/dogsheep-photos/issues/3/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
    
602585497 MDU6SXNzdWU2MDI1ODU0OTc= 7 Integrate image content hashing simonw 9599 open 0     2 2020-04-19T00:36:58Z 2021-08-26T02:01:01Z   MEMBER  

To spot duplicate images (where the file content differs such that the sha256 is no longer a match) it would be useful to calculate and store perceptual hashes of some sort.

 dogsheep-photos 256834907 issue     
{
    "url": "https://api.github.com/repos/dogsheep/dogsheep-photos/issues/7/reactions",
    "total_count": 1,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 1,
    "rocket": 0,
    "eyes": 0
}
    
621486115 MDU6SXNzdWU2MjE0ODYxMTU= 27 photos_with_apple_metadata view should include labels simonw 9599 open 0     0 2020-05-20T06:06:17Z 2020-05-20T06:06:17Z   MEMBER  

https://dogsheep-photos.dogsheep.net/public/photos_with_apple_metadata?place_city=New+Orleans&_facet=place_city&_facet_array=albums&_facet_array=persons

Here's one way to add that: sql select rowid, photo, ( select json_group_array( json_object( 'label', normalized_string, 'href', '/photos/labelled?_hide_sql=1&label=' || normalized_string ) ) from labels where labels.uuid = photos_with_apple_metadata.uuid ) as labels, date,

 dogsheep-photos 256834907 issue     
{
    "url": "https://api.github.com/repos/dogsheep/dogsheep-photos/issues/27/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
    
621323348 MDU6SXNzdWU2MjEzMjMzNDg= 24 Configurable URL for images simonw 9599 open 0     1 2020-05-19T22:25:56Z 2020-05-20T06:00:29Z   MEMBER   dogsheep-photos 256834907 issue     
{
    "url": "https://api.github.com/repos/dogsheep/dogsheep-photos/issues/24/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
    
615626118 MDU6SXNzdWU2MTU2MjYxMTg= 22 Try out ExifReader simonw 9599 open 0     4 2020-05-11T06:32:13Z 2020-05-14T05:59:53Z   MEMBER  

https://pypi.org/project/ExifReader/

New fork that should be able to handle EXIF in HEIC files.

Forked here: https://github.com/ianare/exif-py/issues/102#issuecomment-626376522

Refs #3

dogsheep-photos 256834907 issue     
{
    "url": "https://api.github.com/repos/dogsheep/dogsheep-photos/issues/22/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
    
612860758 MDU6SXNzdWU2MTI4NjA3NTg= 18 Switch CI solution to GitHub Actions with a macOS runner simonw 9599 open 0     1 2020-05-05T20:03:50Z 2020-05-05T23:49:18Z   MEMBER  

Refs #17.

 dogsheep-photos 256834907 issue     
{
    "url": "https://api.github.com/repos/dogsheep/dogsheep-photos/issues/18/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
    
612287234 MDU6SXNzdWU2MTIyODcyMzQ= 16 Import machine-learning detected labels (dog, llama etc) from Apple Photos simonw 9599 open 0     13 2020-05-05T02:45:43Z 2020-05-05T05:38:16Z   MEMBER  

Follow-on from #1. Apple Photos runs some very sophisticated machine learning on-device to figure out if photos are of dogs, llamas and so on. I really want to extract those labels out into my own database.

 dogsheep-photos 256834907 issue     
{
    "url": "https://api.github.com/repos/dogsheep/dogsheep-photos/issues/16/reactions",
    "total_count": 2,
    "+1": 0,
    "-1": 0,
    "laugh": 1,
    "hooray": 1,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
    
602533300 MDU6SXNzdWU2MDI1MzMzMDA= 1 Import photo metadata from Apple Photos into SQLite simonw 9599 open 0   Apple Photos online and securely browsable 5324096 8 2020-04-18T19:23:26Z 2020-05-04T02:41:40Z   MEMBER  

Faces, albums, locations, that kind of thing.

 dogsheep-photos 256834907 issue     
{
    "url": "https://api.github.com/repos/dogsheep/dogsheep-photos/issues/1/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
    
608512747 MDU6SXNzdWU2MDg1MTI3NDc= 14 Annotate photos using the Google Cloud Vision API simonw 9599 open 0     5 2020-04-28T18:09:03Z 2020-04-28T18:19:06Z   MEMBER  

It can detect faces, run OCR, do image labeling (it knows what a lemur is!) and do object localization where it identifies objects and returns bounding polygons for them.

 dogsheep-photos 256834907 issue     
{
    "url": "https://api.github.com/repos/dogsheep/dogsheep-photos/issues/14/reactions",
    "total_count": 3,
    "+1": 2,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 1,
    "rocket": 0,
    "eyes": 0
}
    
607888367 MDU6SXNzdWU2MDc4ODgzNjc= 13 Also upload movie files simonw 9599 open 0     2 2020-04-27T22:11:25Z 2020-04-28T00:39:45Z   MEMBER  

The upload command currently only handles static images:

https://github.com/dogsheep/photos-to-sqlite/blob/d939455af00e07866686457ee2fcb9b2d1b7194e/photos_to_sqlite/utils.py#L26-L33

Need to cover movies taken by my phone and DSLR too.

 dogsheep-photos 256834907 issue     
{
    "url": "https://api.github.com/repos/dogsheep/dogsheep-photos/issues/13/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
    
606033104 MDU6SXNzdWU2MDYwMzMxMDQ= 12 If less than 500MB, show size in MB not GB simonw 9599 open 0     1 2020-04-24T04:35:01Z 2020-04-24T04:35:25Z   MEMBER  

Just saw this: Uploading 0.05 GB

 dogsheep-photos 256834907 issue     
{
    "url": "https://api.github.com/repos/dogsheep/dogsheep-photos/issues/12/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
    

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

CREATE TABLE [issues] (
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [number] INTEGER,
   [title] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [state] TEXT,
   [locked] INTEGER,
   [assignee] INTEGER REFERENCES [users]([id]),
   [milestone] INTEGER REFERENCES [milestones]([id]),
   [comments] INTEGER,
   [created_at] TEXT,
   [updated_at] TEXT,
   [closed_at] TEXT,
   [author_association] TEXT,
   [pull_request] TEXT,
   [body] TEXT,
   [repo] INTEGER REFERENCES [repos]([id]),
   [type] TEXT
, [active_lock_reason] TEXT, [performed_via_github_app] TEXT, [reactions] TEXT, [draft] INTEGER, [state_reason] TEXT);
CREATE INDEX [idx_issues_repo]
                ON [issues] ([repo]);
CREATE INDEX [idx_issues_milestone]
                ON [issues] ([milestone]);
CREATE INDEX [idx_issues_assignee]
                ON [issues] ([assignee]);
CREATE INDEX [idx_issues_user]
                ON [issues] ([user]);