Pass image objects to the logo detection service
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	mfossati
	Apr 25 2024, 5:15 PM

Description

The current logo detection service expects image URLs from the upload stash, e.g., https://commons.wikimedia.org/wiki/Special:UploadStash/file/1avpfxdmdb4c.deuia.10893556.png.
Passing image objects would certainly improve the service performance.
See https://gitlab.wikimedia.org/mfossati/scriptz/-/merge_requests/8#note_75813 for more details.

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	Subject	Repo	Branch	Lines +/-
	logo-detection: process image objects instead of image URLs	machinelearning/liftwing/inference-services	main	+58 -25

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Status	Assigned	Task
Open	None	T349641 [EPIC] Logo machine detection on Commons
In Progress	kevinbazira	T358676 Host a logo detection model for Commons images
Open	kevinbazira	T363506 Pass image objects to the logo detection service

Event Timeline

mfossati created this task.Apr 25 2024, 5:15 PM

Restricted Application added a subscriber: Aklapper. · View Herald TranscriptApr 25 2024, 5:15 PM

mfossati added a parent task: T358676: Host a logo detection model for Commons images.Apr 29 2024, 2:21 PM

mfossati added a project: Machine-Learning-Team.

kevinbazira moved this task from Unsorted to Ready To Go on the Machine-Learning-Team board.Apr 30 2024, 10:21 AM

isarantopoulos moved this task from Ready To Go to Unsorted on the Machine-Learning-Team board.Apr 30 2024, 11:55 AM

@mfossati I am in favor of passing the image object in some serialized form.
We would need the upload wizard to send a resized image (224x224) instead of the whole file. Is that something you are already considering or think it would be easy to try?

In T363506#9757394, @isarantopoulos wrote:

We would need the upload wizard to send a resized image (224x224) instead of the whole file. Is that something you are already considering or think it would be easy to try?

We haven't thought of this yet, mainly because pre-processing logic on the model side already handles resizing. That said, I agree it'd be better to directly send the 224x224 image object.

mfossati mentioned this in T362749: Deploy logo-detection model-server to LiftWing staging.Mon, May 6, 3:08 PM

We haven't thought of this yet, mainly because pre-processing logic on the model side already handles resizing. That said, I agree it'd be better to directly send the 224x224 image object.

Preprocessing will just make sure that the images passed to the model for inference are of the right size, which means that if we pass a 224x224 image it will basically do nothing to it, which is fine.
The main reason to do this would be to guarantee specific latencies especially in the case of larger images as we wouldn't have to download the files (which causes unpredictable response times from the model server).
If you agree we can look into the upload stash code and come up with a proposal.
cc: @kevinbazira

@isarantopoulos , totally agree, makes a lot of sense.

As discussed in today's meeting, adding image objects to the API request significantly increases the payload size. See sample payloads in P62085. If one user sends a request with 50 image URLs and another sends a request with 50 serialized images objects, the latter is likely to exceed the server's request body size limit faster.

@mfossati We noticed that the user can define the width in the url like in this example http://commons.wikimedia.org/w/index.php?title=Special:FilePath&file=Cambia_logo.png&width=224. If we can use this then it would be sufficient and we can stick with using urls in the request.
In this case we can change the request to just include the image name and we can construct the remaining url. Do you know if the name is the unique identifier for the image?
An request then would look like this

{
  "instances": [
    {
      "filename": "Cambia_logo.png",
      "target": "logo"
    }
  ]
}

In T363506#9781301, @isarantopoulos wrote:

@mfossati We noticed that the user can define the width in the url like in this example http://commons.wikimedia.org/w/index.php?title=Special:FilePath&file=Cambia_logo.png&width=224. If we can use this then it would be sufficient and we can stick with using urls in the request.

Hmm, I've just given it a try and I think it won't work for stashed images, which is a hard requirement for us.

Regarding image sizes, at the moment Wikimedia Commons cannot serve a file larger than 1MB from the UploadStash. I am getting the following error:

Wikimedia Commons UploadStash File Serving Error - Screenshot from 2024-05-09 11-49-01.png (308×1 px, 69 KB)

To reproduce this, please follow the steps below:

visit the Commons UploadWizard: https://commons.wikimedia.org/wiki/Special:UploadWizard
use the UploadWizard to upload an image that is above 2MBs but don't publish it
visit the Commons UploadStash: https://commons.wikimedia.org/wiki/Special:UploadStash
copy URL of stash key and try to access it in a new tab. you'll get an internal server error: Cannot serve a file larger than 1048576 bytes.

In T363506#9780991, @kevinbazira wrote:

If one user sends a request with 50 image URLs and another sends a request with 50 serialized images objects, the latter is likely to exceed the server's request body size limit faster.

Thinking out loud: what about sending multiple requests if the limit is reached? I speculate that 50 uploads are an edge case: if this happens, we could dispatch different requests.

More context: we're planning to plug the logo detection inside the Upload Wizard workflow, so I think that the actual LiftWing service user will be some client-side logic that lives in Upload Wizard's codebase.

mfossati awarded a token.Thu, May 9, 9:09 AM

In T363506#9757394, @isarantopoulos wrote:

We would need the upload wizard to send a resized image (224x224) instead of the whole file.

I can imagine we can tackle that from within the Upload Wizard with some JavaScript library. I can create a ticket to look into that if you think this would be the best solution.

In T363506#9782659, @mfossati wrote:

In T363506#9757394, @isarantopoulos wrote:

We would need the upload wizard to send a resized image (224x224) instead of the whole file.

I can imagine we can tackle that from within the Upload Wizard with some JavaScript library. I can create a ticket to look into that if you think this would be the best solution.

Yes, let's do that!

mfossati mentioned this in T364551: [SPIKE] Send an image thumbnail to the logo detection service within Upload Wizard.Thu, May 9, 2:36 PM

In T363506#9781491, @mfossati wrote:

In T363506#9781301, @isarantopoulos wrote:

@mfossati We noticed that the user can define the width in the url like in this example http://commons.wikimedia.org/w/index.php?title=Special:FilePath&file=Cambia_logo.png&width=224. If we can use this then it would be sufficient and we can stick with using urls in the request.

Hmm, I've just given it a try and I think it won't work for stashed images, which is a hard requirement for us.

@isarantopoulos @kevinbazira , I think I found how to get a thumbnail from a stashed image. There you go: https://commons.wikimedia.org/wiki/Special:UploadStash/thumb/1awuam969hko.2tkfbz.10893556.png/224px-1awuam969hko.2tkfbz.10893556.png, where 1awuam969hko.2tkfbz.10893556.png is the stash file key. The 224px- prefix is the width size.
Of course, I feel there's a caveat, as it seems that the thumbnail is generated on the fly at request time. Still not optimal, but sounds like a workable solution.

In T363506#9757394, @isarantopoulos wrote:

@mfossati I am in favor of passing the image object in some serialized form.
We would need the upload wizard to send a resized image (224x224) instead of the whole file.

I've opened T364551: [SPIKE] Send an image thumbnail to the logo detection service within Upload Wizard to investigate the feasibility of this solution.

@isarantopoulos @kevinbazira, I'd like to set expectations right here: my team is aiming at a workable solution in roughly one month. Optimization can then come as a subsequent step. I think that T363506#9783689 is fair enough for now. Do you agree?

CC our product manager @AUgolnikova-WMF .

In T363506#9783710, @mfossati wrote:

I've opened T364551: [SPIKE] Send an image thumbnail to the logo detection service within Upload Wizard to investigate the feasibility of this solution.

Thank you for dedicating a task to investigate the feasibility of this solution.

I'd like to set expectations right here: my team is aiming at a workable solution in roughly one month. Optimization can then come as a subsequent step. I think that T363506#9783689 is fair enough for now. Do you agree?

100% agree, I am able to reproduce the 224px- thumbnail solution on my end and the inference results are not far apart:

# request without thumbnail
$ time curl -s localhost:8080/v1/models/logo-detection:predict -X POST -d '{"instances": [ { "filename": "woman-with-dog--on-a-beach.jpeg", "url": "https://commons.wikimedia.org/wiki/Special:UploadStash/file/1aww29uyg1ik.hl80le.7972071.jpg", "target": "logo" } ] }' -i -H "Content-type: application/json" -H "Cookie: <redacted>"
HTTP/1.1 200 OK
date: Thu, 09 May 2024 16:28:54 GMT
server: uvicorn
content-length: 121
content-type: application/json

{"predictions":[{"filename":"woman-with-dog--on-a-beach.jpeg","target":"logo","prediction":0.015,"out_of_domain":0.985}]}
real	0m0.730s
user	0m0.000s
sys	0m0.022s


# request with thumbnail
$ time curl -s localhost:8080/v1/models/logo-detection:predict -X POST -d '{"instances": [ { "filename": "woman-with-dog--on-a-beach.jpeg", "url": "https://commons.wikimedia.org/wiki/Special:UploadStash/thumb/1aww29uyg1ik.hl80le.7972071.jpg/120px-1aww29uyg1ik.hl80le.7972071.jpg", "target": "logo" } ] }' -i -H "Content-type: application/json" -H "Cookie: <redacted>"
HTTP/1.1 200 OK
date: Thu, 09 May 2024 16:28:28 GMT
server: uvicorn
content-length: 123
content-type: application/json

{"predictions":[{"filename":"woman-with-dog--on-a-beach.jpeg","target":"logo","prediction":0.0206,"out_of_domain":0.9794}]}
real	0m0.824s
user	0m0.012s
sys	0m0.012s

During the meeting between the Structured Content team and ML team, it was concluded that passing image objects is preferable to passing image URLs. This is because passing image URLs raises security concerns related to sharing a user cookie, as discussed in T362749.

@mfossati, currently the logo-detection model-server takes the following input with an image URL:

{
  "instances": [
    {
      "filename": "Cambia_logo.png",
      "url": "http://commons.wikimedia.org/w/index.php?title=Special:FilePath&file=Cambia_logo.png&width=224",
      "target": "logo"
    }
  ]
}

To facilitate the transition to image objects, please specify:

what the new input will look like
what serialization format will be used

Thanks!

We concluded that we will figure out the format after the team figures out the spike (accessing the image and sending a thumbnail to Lift Wing).
I'd suggest we proceed with a base64 encoded image for now. Something like this would work:

{
  "instances": [
    {
      "image": BASE_64_ENCODED_STRING
      "target": "logo"
    }
  ]
}

In this context I would recommend we don't rewrite the whole app. We can add a new function loading the image in memory and use that one instead of fetching the urls.
We also said that it would be great to include the content-length header in the request so that we will know what to expect.

In T363506#9794241, @isarantopoulos wrote:

We concluded that we will figure out the format after the team figures out the spike (accessing the image and sending a thumbnail to Lift Wing).

See T364551: [SPIKE] Send an image thumbnail to the logo detection service within Upload Wizard

I'd suggest we proceed with a base64 encoded image for now.

With binary being the preferred format, right?

We also said that it would be great to include the content-length header in the request so that we will know what to expect.

Sure, noted in the spike.

isarantopoulos set the point value for this task to 5.Tue, May 14, 2:32 PM

isarantopoulos assigned this task to kevinbazira.Tue, May 14, 2:40 PM

isarantopoulos moved this task from Unsorted to In Progress on the Machine-Learning-Team board.

kevinbazira mentioned this in T363505: Pass the maximum number of uploads to the logo detection service.Tue, May 14, 3:06 PM

The logo-detection model-server has been updated to process base64 image objects instead of image URLs. Below is what the new input and output look like. We tested it with the same images used during the prototype validation, and the output results are not far apart, as shown in P58917#237882.

1.Request with sample payload that has 6 base64 image objects:

curl -s localhost:8080/v1/models/logo-detection:predict -X POST -d '{"instances": [{"filename": "12_rue_de_Condé_-_detail.jpg", "image": "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"target": "logo"},{"filename": "120px-Abv.png", "image": 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", 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kE9FU8h3uVF26Dst4cHSAiVCAck8WT1xTHcSSGqqhIxAk9CTasknUOTtB5+w4kkhl6O+vbVmXnj05Ncpl3ywOi8LzTVvxKDYkBN3z0+wf6btxgP3x6IpM0WGx3BbxH9VU/uXSGQJpQv6Ryjqerd+4box+7cpFopqKnBbLy0Lw1uQwfb7ZNWrPVFMipCY4OTWCLEm8t6Y5U1fbLakVbJgmgUSU2qy8FTsT3IoVR1pd4Y9HCWuJzLHqrFx+Y9tDDAYW8Cei6yYyM5EQ//fyeUzgExt3rtI5i/ToLXmjmUgoc6zPN5tZfZXenHVdbTyZ5I3hXhJ6kuqsXD6xcSe7yqoxMIlqKq8P9WbC1dsCPJFuLCy5l9vdedDnm+XU9BiyEDgVKx9q2LyCuLi2c7Uk5NtTUUelNweTlILz2PjgqvN98QhCpDLYA6P95DtcK9zptc2D99U2U+HNyXzvtdmpTH8fS2qreq7PN23jc098iB1FFRQ43WsmWN/uPcfZmXE2FZTy0eZtqyeh3Z7WUpssJuJMhhczx0aCPkxSiVdddj4562iu94308fpQL1bZwk81b6M+p4CnapqxSDKyJPHGcC9f7DyObhrXB9jEZDoczGR9siStyQXfjE2EF4kmVUxSorttReXrxulv9ZxlKhIkz+HkV7fuZndZDWZ6Ze8fubxqllqklNoiltRYjMcocXvXVEzopkFNVh4/UbfSc7gVG09WNyEJQURTWUiXSoZpopupmNmUV8TmwjJ2lVavqmFPTAzxte4OHBYLv7T5PRQ5PWt4MI1IUkUg0Ayd8VAgw5n3++cxzdRCimgqyTUAOj09xl91HCCkxnlfTRPPN21LE0J1tOYVY5gG8WSSL50/wXcud9Hvn1vV2JCWuxOvzZ5xyCag3Obembcmh1GTKYYn1+7Cs45Q4NDoAC/1ngPgw41beE9pDe+tacZhsSALwcX5afYNr4w1XuuyGS8Ej1c2kLOMsLDLFnTTYGthOX/32HM0rVHubS4sxWu1E0tqdM9PAXBsfJDPnz2amVCSEDxZ3YhVthDXtUz8/PTh7zIeWuSjTdv4QF3rdRmqpf+/cfEUb472IwSZUCKEoN8/x2iaTl3KCb556TS/tu9len0zPFXbwou7n8owYcUuDz/bel8qkUxzBp8+/F2e+86Xee3KxfVddKpzcrVGW4+5udHseS4aTpP+Ip3IaKvOeWO4lz8++j3mYxF2l9Xyn7c+hBCCtvxiarPyMdPEw192HODC3NSKDPXqfYtVW0EeLK/lN7c9zN8+9iy7SqvX7PdWe3MpdntJGganpkYwTJNIUuVL50+wd7An4/a2FpbjVKycn53kjeE+fvPAK1wJzPNcwyZ+Z8eedWN0ls1OicubIUouzk/zxnAvspAy4UESgvFQgBeOvMaXu9r5clc7v/zGS/zhkdcYCfp4qqaF//rgj69KTD/YuJln6zeiGwaGaRJSE7Tll/BY1Uphn/ziiy++uERy/HNXO0OLvkw3Zk9l/bpu9UYz6EsL00iSRDypUZudz4bsPJKGyZXAPP9w5gh/e/ogE+EgH27czH958KkMUG6rDc3QOTQ2gCQEvniUztkJzs2Mo+o6CT3JvuE+DEzyHClR/fIdA3kOF49U1F13T6/baiOe1Dg2MUhQTfBAaTWbCkrZO9TDq/0XGAn6sUgysaTGRChAx9QIX73QwUQ4wM+07uC/Pfj+6/bI7RaFoBrn2PgQhmnywcbNvPDAE7itNhwWhaNjVzKJ1mjQz4GRy+wb6WPAP0++080nNz7AH+16kpI1tNSKJGdyDosk8VzDZv5g5xMr8gwAsfwxSp8/d5S/aN+fjkMGv771If70Pe+9ZYC/3n2SF45+L1WgmyY5DicNOYVIQjAS9DEa9ONSbPxEXRt/+MCTq/brTIaD/Pzef+HszDgWSUIzdDxWO599+GkSus6nDn6HptwifmXLbj7SuOWGm+AreOREnC90HuPLXe205pfwuSc+xJGxK/zhkdeIaCouxYpNthDREmiGTp7DxYcaNvO79z16QyrJQCLG60O9BBIxnqvfSOGyWP1q/wX+8ewRFhMxfGlevcjpoS4nn0+07WRLUfnbbvPRTYOopuJWbGt6qRW+xWlZuaXzwtxU5kPeiv1E3UaOjF3he4OXMIH5aITZyCAmJg6Lws6SKn5+4wM8VduMY43sutTt5c92v48/Ofp9+vyzNOcV8bv3PcpTtc20T47wTF0bv7Njz5otvBs1r83O793/GE25Rbzc18lUJMhHmragGjov9Z6j3z+HVZapzy1na2EZH2zYTFt+yQ1Ppmybg+ebtq557Jm6Nh4sryGiqVwJLFDgcFPlzcGhKDcsWZKFtG5us2oF7x/p4xd/8O2Mlqnck80rz/58Jl7cik1Fgrw+1MNsNEzH5AiV3pz0LC3gsar6Vb3T9cj8SwvTbCkso8SdlenOqLp+x3YKmKaJZugospxp8QUTcXp9s7gVG5XeHFyK9Y5p0t4pWwHw4bEBfu77/0JCT2b8/B/t+jF+afOuOzKA0aSGVZZvWVB3z27eVmTRxS4vHqstU/PFkxpvjl4moqk3feGQmuBKYJ7pSDCtSRLpFSAR1VT88RhBNZ4Rtt17ouIPx1b4twpPNluKynl9qAc5rce9MDdF78IM24srbvii05Egf3psL+2Tw1R4cvj8kx+mOiuXWFLjc2ePcmh0gLiuYZcVCl1uFEnGYVEocXspcnpwKVbKPNkUOd04MnmBiSLLeKx2bLLlHXeVScNIdZk07Tr+MOX1FEki2+bAIKX5UtPPI7HKKflsIB5Lc9RglWWssoWopqHqSQKJGJqupx93IeO2WrFKMrIk47XacCjKTdHHK5MsxcqjFXW8MdSbKcIXYhH+4cxh/v7xD95QvBwN+vn04e9yaGwA3TCwSHKG/pSFxObCUoJqnPbJYU5Oj2RIljRfkRF6OywKbqvtajJjpsqOQqebMk82pW4v+Q4XVtmS2b2Xa3elmwyCCk8ObmtKlyUJgWYYzESCzEbDqHqSmUiIkJqgJisvIzJIGgbBRJxQul1olS24FStxPclI0MdQwMeiGme9zoNAYJctOBUrzXlFxJIac9EwYU3FaVEodHnQDYN+/xyxpIZIl1IuxUogESORTBJNqiSNlFTHIiRs6XanVZYpcnqoyc6jJisXr9WO12anyOmh2J3yvB7FvionEdc+bXYiFOA3DrzCiYmhzCoRQvD+NJtS6l6trjSBYCLGobEBvnqhg46pUQzTxCbLfGrHHn5j+8OrnskxGV7kn7vaeeXyeWYiIQzM9GavlQzQWrHcXDYZrq0Nl+45z+HCqSj4YlGEEOlyQstop8y0nEZKCadYavcaprlio7dYBqdY/q+49r6uNuOXnqtlpIkSiyQj0sekZWI/WUiZ1uySRGrpnKX2pSxJWNM5i5TewipEar+y3aKQNHScihW3YmNXaTW/v/PxFVWPWOtxwj8Y6uGXX38p40aWQLy/pJKPNm1jU0EpkhAE1RSB3jkzQefcBJ0zE0STKookU+rO4mMt2/nVLbvXLIGWarg+3yz7hy/zg6Eeen2zRLQEFiFT4vYSUuPEk0mShp4e+GtWTLrjJKeb6WLZzRrpL5ZPghRFmHKhspBQZJmkbiAJgSLLuK02XEshQZAZWIsk47XZM/uCIppKWEug6Xpm4PMcLvIcLso92ZS4vJn61AS86bBiky04FIWEniSiqnhttlXKyCWAl1hEqyxnxi/l/mXMtOu3yhYC8SjRpIZppgifhtyCFYtpTYB98Si/8vpLHB4bWKEvWiLhc2wOhBBENTXDKpmmiZzWcP1U8zaerG6iNjvvhmKlSapve25mnK65SdyKjYfKNxDREszFIgTiMeK6liHn4+n3c1lTM9epWHEpyg1t0LbKMjbZkon7cT2JLAR2WcFusVylHQWZ/cBL7lKSUi18PS0IyAxd+vFQd+OTg8R6DwTvnp/iU2++yvm5ifTMuuo+l9ykmf5akWV2lVbz9IZWHqmooyYr9176ercDvNSj/ealM4wEfZyaGmU+FsnEKJtsocKTQ212Hk9WN/L0htYbSsLu2V0EMMsYo46pEaYjQcJqgkhSpSYrj+1FFeQ5nDe1nfFO2nzAz6xvgZbaldtOhicnEELgdbmZmp9ddfxGbc7vY2BslPvbNl13X9GdNNM0icRjuOwOYok4F68MsKWxGeUWGbu3fZUkBHaLhUfu4PaVO2Vzfh/dAwOrAByaHEcIwaa6RtTr1a1vY7phEFcTV1Pkd8DiqsreY0d4764HkWWZhKreFgn07/o0UMM06R7op294CKfdzgObNqNYLHQP9KMlk0zNz1FfWcW2phYWw2FOXbzAfMBPXlY2D23bgSQk/KEge48fIRyN0lhdy6b6hrQWSiDLEnabnWg8Tt/wIOFojInZaWrKKtjR2kZCTdBxoYs5v4/C3Dwcdjvbmloyq8Uiy7gcTmKJON0D/SQ0jan5OapKSrm/dSM9w4P4g4ssBAIIIXjP5q0U5OQyOj3Fud5LqJpGU3UtTTW1nO29RG1ZOQU5uYzNTLMYClFdVsap7gvMLMyT7fFyf9smeocH6RkaJDcrmx0trTgdDiRJYta3wOlL3YSiUSqLS9jR0sa838+V8VEi8TiLoRBbGptoqKpen6p8p+3y8BDnei/RtqEOm9XKG28dZ87v5wcnjmGaJk3VNRw81cH4zDQdF84TjcfZ0dLGxNws3QOXkSWJmYV5crxZ1FdWc+zcGYYnJ5CklOzWt7hIz+AAsUSc1986jmkaNNXUcvJiF/N+HyfOdzLjW2BTQyMTc7McPn2SpK4v8xB+2rs6CUWj7Ot4C1XTaN1QR8eF84zPztB1uY/Ovl4aq2tI6jr7O95izu/jlTf3kePNoqGqmsNnT9E/OsL4zDRd/ZdTXbr+yyyGQ3T3XyYYCbM9/Zne6uqkMDcPj8tFUW4ecVXl9MVuAqEgrx48gCQkNtY1cKH/MqcvdTM5P8ubpzrIz86mpKCA7x87TCgSuXtW8PnLfYSjUSbnZ0moCaYX5gkEg2S53WxrasHlcNB+4TzhWIyW2g0sLC4y5/fhDy4SSyTI8pjUllews21TSgzuW+D85V5yPN6M5GNp81ZBTi73tW3CbrXSOzzErN/H0MQ4Tz+8h5L8AmRJ4rWFhRUs1ZIiEsDtcLKjpY1sj4dTFy8QS8QRQtBaW0dzzQZME46dO8PYzDQ5Hi8PbtmWXnk+uq/0s7WxiUOnT7GlsYnphTl2tm1C05O4nE4WFgMEw2Gy3G7KC4vI9ngoLypG13UkSWI+4EcIwaP37cRmtSIEnL50kfrKKuoqKtne3EowEqazr4eEpuLBdXcALIQgLyuL6pIyND1JjjcLhz21t0da0iwhMAydE12deJwumms3UFVSuqpkE9cwStea3WrFkqY9l7/WSBMKSX2prl27bl/yCksSJHF1BmVylbUa7iYmpmFSVVKGYjnH2Z5LZLk8ZHs8vHroAIpFYWNdPaWFhUDq+quZ0KW9TWaGOFh6L2mZtmstHuDf1UVvamggmkiQ0FQWAgFGpiaxWOQVNKVpmuiGiT8YxKpYiMXjjE1PMx8IYOgGg+NjdFw4z/nLvQyMjbK5oTE9SOYKwM1rYr/TZqe+soqDp09ycXCA9q5O9GsE9ubS680l6tRcyQOY5tX3AQzDoLSgkEAoxNFzZ+js66FveJhN9Q1YFYWq0jIOnT5JXWUVQpKY9/tRLBZUTWNmYYHFUBDd0EloGiNTE+iGjmEYFGTnIITgzZPtXLwywJFzp6mvrMIiy1cTMHPtZ2lmNFn/HpablYUiWxgYG0U3DHZt2kxuVjZuh5PSgkIssoxVUagoKqakIJ+x6RkSqkpdRQWyLFNZXEpBTg6RaJQZn4+tTU00VtcgSzK5WVlkezy4HE7ys7Nx2u0U5OQiSRKKxUJhbh5FuXloSY1gJILdaiUaj7GjpQ05vdJlSSLL7aa0sBCXw0lZQVHmnorz8vG63BTl55Pl9iBLEl63iw3lFZQXFTE+M83CYoDtLa0019RmvFWO10trbR1WRaEoN4/x2RlCkQiN1bXYrAqVxaW4HHYSqkZxfj5up5OK4hJqSsuY8S0wPT9HQ3UN25tasFgs5Hi95KcngN1mo7SgYEVJJf4j/2q7Y+fO4FtcTCVO3V3kZefw3l27/2MRHT/KFo5GOXnxAv7gIoW5eexoacVhs98D+J69e+zer7a7B/A9ezfb/weII/DP7SbbWQAAAEx0RVh0Y29tbWVudABGaWxlIHNvdXJjZTogaHR0cHM6Ly9jb21tb25zLndpa2ltZWRpYS5vcmcvd2lraS9GaWxlOkNhbWJpYV9sb2dvLnBuZ3z9QBcAAAAldEVYdGRhdGU6Y3JlYXRlADIwMTYtMDQtMDlUMDU6NDQ6NDMrMDA6MDAtJHL/AAAAJXRFWHRkYXRlOm1vZGlmeQAyMDE2LTA0LTA5VDA1OjQ0OjQzKzAwOjAwXHnKQwAAAEd0RVh0c29mdHdhcmUASW1hZ2VNYWdpY2sgNi43LjctMTAgMjAxNC0wMy0wNiBRMTYgaHR0cDovL3d3dy5pbWFnZW1hZ2ljay5vcmdvn6KiAAAAGHRFWHRUaHVtYjo6RG9jdW1lbnQ6OlBhZ2VzADGn/7svAAAAGHRFWHRUaHVtYjo6SW1hZ2U6OmhlaWdodAA0NDBSa68PAAAAF3RFWHRUaHVtYjo6SW1hZ2U6OldpZHRoADgyMNGHomAAAAAZdEVYdFRodW1iOjpNaW1ldHlwZQBpbWFnZS9wbmc/slZOAAAAF3RFWHRUaHVtYjo6TVRpbWUAMTQ2MDE4MDY4M0TnYQYAAAATdEVYdFRodW1iOjpTaXplADQxLjJLQkKhAP4wAAAAAElFTkSuQmCC", "target": "logo"},{"filename": "Elizabeth_Drive_-_border_of_Edensor_Park_and_Bonnyrigg_Heights_in_New_South_Wales_62.jpg", "image": "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", "target": "logo"}] }' -i -H "Content-type: application/json"

2.Response with results that are not so different from previous ones:

{"predictions":[{"filename":"120px-Abv.png","target":"logo","prediction":0.9994,"out_of_domain":0.0006},{"filename":"12_rue_de_Condé_-_detail.jpg","target":"logo","prediction":0.0024,"out_of_domain":0.9976},{"filename":"BackupVault_Logo_2019.png","target":"logo","prediction":0.989,"out_of_domain":0.011},{"filename":"Blooming_bush_(14248894271).jpg","target":"logo","prediction":0.0172,"out_of_domain":0.9828},{"filename":"Cambia_logo.png","target":"logo","prediction":0.9997,"out_of_domain":0.0003},{"filename":"Elizabeth_Drive_-_border_of_Edensor_Park_and_Bonnyrigg_Heights_in_New_South_Wales_62.jpg","target":"logo","prediction":0.003,"out_of_domain":0.997}]}

Change #1031590 had a related patch set uploaded (by Kevin Bazira; author: Kevin Bazira):

[machinelearning/liftwing/inference-services@main] logo-detection: process image objects instead of image URLs

https://gerrit.wikimedia.org/r/1031590

gerritbot added a project: Patch-For-Review.Wed, May 15, 2:00 PM

Change #1031590 merged by jenkins-bot:

[machinelearning/liftwing/inference-services@main] logo-detection: process image objects instead of image URLs

https://gerrit.wikimedia.org/r/1031590

kevinbazira mentioned this in rMLISc5ac91ec1b1c: logo-detection: process image objects instead of image URLs.Thu, May 16, 2:54 PM

Maintenance_bot removed a project: Patch-For-Review.Thu, May 16, 3:31 PM

kevinbazira mentioned this in T363449: Configure the logo-detection model-server hosted on LiftWing to process images from Wikimedia Commons.Wed, May 29, 10:33 AM

	F51334989: Wikimedia Commons UploadStash File Serving Error - Screenshot from 2024-05-09 11-49-01.png
	Thu, May 9, 8:54 AM

Pass image objects to the logo detection serviceOpen, Needs TriagePublic5 Estimated Story PointsActions

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Pass image objects to the logo detection service
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