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6 rows where "created_at" is on date 2020-04-28, "updated_at" is on date 2020-04-28 and user = 9599 sorted by updated_at descending
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- simonw · 6 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | issue | performed_via_github_app |
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620774507 | https://github.com/dogsheep/dogsheep-photos/issues/14#issuecomment-620774507 | https://api.github.com/repos/dogsheep/dogsheep-photos/issues/14 | MDEyOklzc3VlQ29tbWVudDYyMDc3NDUwNw== | simonw 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.
|
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Annotate photos using the Google Cloud Vision API 608512747 | |
620771067 | https://github.com/dogsheep/dogsheep-photos/issues/14#issuecomment-620771067 | https://api.github.com/repos/dogsheep/dogsheep-photos/issues/14 | MDEyOklzc3VlQ29tbWVudDYyMDc3MTA2Nw== | simonw 9599 | 2020-04-28T18:12:34Z | 2020-04-28T18:15:38Z | MEMBER | Python library docs: https://googleapis.dev/python/vision/latest/index.html I'm creating a new project for this called simonwillison-photos: https://console.cloud.google.com/projectcreate https://console.cloud.google.com/home/dashboard?project=simonwillison-photos Then I enabled the Vision API. The direct link to https://console.cloud.google.com/flows/enableapi?apiid=vision-json.googleapis.com which they provided in the docs didn't work - it gave me a "You don't have sufficient permissions to use the requested API" error - but starting at the "Enable APIs" page and searching for it worked fine. I created a new service account as an "owner" of that project: https://console.cloud.google.com/apis/credentials/serviceaccountkey (and complained about it on Twitter and through their feedback form)
```python from google.cloud import vision client = vision.ImageAnnotatorClient.from_service_account_file("simonwillison-photos-18c570b301fe.json") Photo of a lemurresponse = client.annotate_image(
{
"image": {
"source": {
"image_uri": "https://photos.simonwillison.net/i/1b3414ee9ade67ce04ade9042e6d4b433d1e523c9a16af17f490e2c0a619755b.jpeg"
}
},
"features": [
{"type": vision.enums.Feature.Type.IMAGE_PROPERTIES},
{"type": vision.enums.Feature.Type.OBJECT_LOCALIZATION},
{"type": vision.enums.Feature.Type.LABEL_DETECTION},
],
}
)
response
|
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Annotate photos using the Google Cloud Vision API 608512747 | |
620772190 | https://github.com/dogsheep/dogsheep-photos/issues/14#issuecomment-620772190 | https://api.github.com/repos/dogsheep/dogsheep-photos/issues/14 | MDEyOklzc3VlQ29tbWVudDYyMDc3MjE5MA== | simonw 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 } |
Annotate photos using the Google Cloud Vision API 608512747 | |
620771698 | https://github.com/dogsheep/dogsheep-photos/issues/14#issuecomment-620771698 | https://api.github.com/repos/dogsheep/dogsheep-photos/issues/14 | MDEyOklzc3VlQ29tbWVudDYyMDc3MTY5OA== | simonw 9599 | 2020-04-28T18:13:48Z | 2020-04-28T18:13:48Z | MEMBER | For face detection:
|
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Annotate photos using the Google Cloud Vision API 608512747 | |
620769348 | https://github.com/dogsheep/dogsheep-photos/issues/14#issuecomment-620769348 | https://api.github.com/repos/dogsheep/dogsheep-photos/issues/14 | MDEyOklzc3VlQ29tbWVudDYyMDc2OTM0OA== | simonw 9599 | 2020-04-28T18:09:21Z | 2020-04-28T18:09:21Z | MEMBER | Pricing is pretty good: free for first 1,000 calls per month, then $1.50 per thousand after that. |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Annotate photos using the Google Cloud Vision API 608512747 | |
620309185 | https://github.com/dogsheep/dogsheep-photos/issues/13#issuecomment-620309185 | https://api.github.com/repos/dogsheep/dogsheep-photos/issues/13 | MDEyOklzc3VlQ29tbWVudDYyMDMwOTE4NQ== | simonw 9599 | 2020-04-28T00:39:45Z | 2020-04-28T00:39:45Z | MEMBER | I'm going to leave this until I have the mechanism for associating a live photo video with the photo. |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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issue 2