Comments (8)
@lolsatdanger It is certainly possible and is relatively easy to get it running in-browser. This is certainly on my to-do list. Currently I am very stretched for time, but I will definitely add tensorflow js version of this when i get some time.
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i have it working with tfjs in browser without issues.
see issue #54 for discussion on the topic.
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Awesome! I'm glad to hear that it is on your list. I was not familiar with tensorflow js, but looking up that github now, it seems great. I look forward to it when you have the time!
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You might find my project to be helpful for providing a bit of the backbone: https://github.com/wingman-jr-addon/wingman_jr
That one hooks image requests via filterResponseData, so it is Firefox only.
Or you might find the Purify.ai plugin to be a good starting base:
https://github.com/purify-ai/geacc-crx
I think that a different use case for such a plugin would involve censoring only certain parts due to sensitivity and cultural norms - I don't think fetishes would have to be the only use case here.
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Hello,
I had a go at this myself using wingman-jr and tfjs-converter. I was able to replace the original model with NudeNet's model but I couldn't convert the detector model because it seems to use layers that aren't supported by tfjs (resnet?). Both classifier models have similar performance on my machine.
Side question: Would a browser extension be capable of running using multithreading?
That exhausts my understanding of ML. Maybe a tfjs version of the detector needs training from scratch?
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@nn12343456 I am currently working on a new version of the detector. I am planning to use https://github.com/faustomorales/retinanetjs as a starting point for the js version.
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@nn12343456 Fascinating! Yes, I imagine you might run into layers not supported by TF.js. They are adding support for different layers relatively frequently, so definitely keep an eye on new versions.
Regarding multi-threading, the answer is yes, but with some caveats. Generally speaking you use "web workers" to get processing in the background, and they act more similarly to processes with pipes than threads if you ask me. However, plugins using WebExtensions cannot use web workers (at least in the main background processing script), but might be able to in the content scripts. I'm curious - when you want do multithreading are you more looking at the GPU or CPU part of the workload?
Perhaps @bedapudi6788 's approach using retinanetjs will already handle the threading concerns?
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Im curious how did the project end ornhows going. There is no mention of brownser support afterwards, but the only use for NudeNet for me is to block stuff on brownsers
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Related Issues (20)
- Not Predicting unsafe on some nsfw images HOT 1
- Censor type HOT 1
- why is web version much better than python library? HOT 1
- how to cover parts after detected ? HOT 1
- New detector only inputs path, can't use with cv images. HOT 3
- Centering censorship area around specific points HOT 2
- Error: no available backend found. ERR: [wasm] RangeError: Out of memory, [cpu] Error: previous call to 'initWasm()' failed., [webnn] Error: previous call to 'initWasm()' failed. HOT 1
- Docker container Error HOT 5
- Inference new models
- OpenCV's `imread()` fails to read image with non-ASCII filename HOT 4
- Detection of the larger model is worse HOT 2
- the box is wrong point HOT 8
- img byte array HOT 2
- Docker curl multipart/form-data not possible with every Language HOT 7
- Dataset for adding better models
- Cannot import name 'NudeDetector' from 'nudenet' HOT 1
- Model Unsupported model IR version: 10, max supported IR version: 9 HOT 2
- how do I get this script to run on GPU?
- Convert to Pytorch and how to load the pytorch models, i.e.,"320n.pt" HOT 1
- The Classifier Performs way better than the Detector HOT 1
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