A small tool to view real-world ActivityPub objects as JSON! Enter a URL
or username from Mastodon or a similar service below, and we'll send a
request with
the right
Accept
header
to the server to view the underlying object.
{
"@context": [
"https://www.w3.org/ns/activitystreams",
{
"ostatus": "http://ostatus.org#",
"atomUri": "ostatus:atomUri",
"inReplyToAtomUri": "ostatus:inReplyToAtomUri",
"conversation": "ostatus:conversation",
"sensitive": "as:sensitive",
"toot": "http://joinmastodon.org/ns#",
"votersCount": "toot:votersCount"
}
],
"id": "https://piaille.fr/users/gmic/statuses/113442117070439301",
"type": "Note",
"summary": null,
"inReplyTo": "https://framapiaf.org/users/davidrevoy/statuses/113442041438733895",
"published": "2024-11-07T14:22:15Z",
"url": "https://piaille.fr/@gmic/113442117070439301",
"attributedTo": "https://piaille.fr/users/gmic",
"to": [
"https://www.w3.org/ns/activitystreams#Public"
],
"cc": [
"https://piaille.fr/users/gmic/followers",
"https://framapiaf.org/users/davidrevoy"
],
"sensitive": false,
"atomUri": "https://piaille.fr/users/gmic/statuses/113442117070439301",
"inReplyToAtomUri": "https://framapiaf.org/users/davidrevoy/statuses/113442041438733895",
"conversation": "tag:piaille.fr,2024-11-07:objectId=91830207:objectType=Conversation",
"content": "<p><span class=\"h-card\" translate=\"no\"><a href=\"https://framapiaf.org/@davidrevoy\" class=\"u-url mention\">@<span>davidrevoy</span></a></span> That's fine ! I'll write you ASAP.<br />Yes, the downscale is simulated during the training. For the images, the more is probably the best :) In the training data set I used here (DIV2K), there are 800 images, but I guess a hundred would be already enough (yes, that's already a lot...).<br />We can try with less anyway, and see what happens.<br />We could also try not only with lineart, but also flat-colorized images, to have a bigger dataset.</p>",
"contentMap": {
"fr": "<p><span class=\"h-card\" translate=\"no\"><a href=\"https://framapiaf.org/@davidrevoy\" class=\"u-url mention\">@<span>davidrevoy</span></a></span> That's fine ! I'll write you ASAP.<br />Yes, the downscale is simulated during the training. For the images, the more is probably the best :) In the training data set I used here (DIV2K), there are 800 images, but I guess a hundred would be already enough (yes, that's already a lot...).<br />We can try with less anyway, and see what happens.<br />We could also try not only with lineart, but also flat-colorized images, to have a bigger dataset.</p>"
},
"attachment": [],
"tag": [
{
"type": "Mention",
"href": "https://framapiaf.org/users/davidrevoy",
"name": "@davidrevoy@framapiaf.org"
}
],
"replies": {
"id": "https://piaille.fr/users/gmic/statuses/113442117070439301/replies",
"type": "Collection",
"first": {
"type": "CollectionPage",
"next": "https://piaille.fr/users/gmic/statuses/113442117070439301/replies?only_other_accounts=true&page=true",
"partOf": "https://piaille.fr/users/gmic/statuses/113442117070439301/replies",
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}
},
"likes": {
"id": "https://piaille.fr/users/gmic/statuses/113442117070439301/likes",
"type": "Collection",
"totalItems": 2
},
"shares": {
"id": "https://piaille.fr/users/gmic/statuses/113442117070439301/shares",
"type": "Collection",
"totalItems": 0
}
}