Modelplace: AI Model Marketplace by OpenCV | Hacker News Reader

Modelplace: AI Model Marketplace by OpenCV

modelplace.ai

127 pointsphilnelson37 comments

I can see value in being able to casually integrate vision models into different applications.

I would urge everyone involved (OpenCV and people using the models) to not use this in any safety related application. The example given on the site is person detection for construction site safety. If you're going to use ML for something like this, hire someone with experience using it for such applications, that can understand the operating condition and failure modes. Your worksite is not safe if you just plugged in an online person detection model to a video feed.

If this becomes something like huggingface for Computer Vision - awesome. For now, it's a shame model descriptions seem to often be lifted straight from README.

Having a more standardized description, something like model cards [1] (CV example [2]) would be hugely beneficial IMO.

[1] https://arxiv.org/pdf/1810.03993.pdf

[2] https://drive.google.com/file/d/1f39lSzU5Oq-j_OXgS67KfN5wNso...

It's a good suggestion, thanks.

They looks quite similar. What did you find useful in this card and can't get from a model description?

I hadn't heard of model cards before - thanks for the link!

I wonder how feasible it would be to develop some formal ontology to describe the capabilities of models and attach them to model cards.

That could open up some interesting applications:

* automated search for a set of models to accomplish some task

* a human usable search engine for finding specific models

EDIT: to complete a sentence

I don't think this will be a successful business model. Niche AI models cost a lot of money to gather the right dataset and train, but they would probably only sell to <100 companies/individuals. So pricing a model at $50-100 isn't profitable. If you're selling general CV models, you have to compete with the plethora of open source ones, including ones that Google and Facebook release for free, which are trained on huge datasets and using a lot of compute resources.

It looks like model-as-a-service. Cool feature, isn't it?

I agree, it seems like fine-tuning the massive open source models is better than buying small niche models. Curating the dataset is also a non-trivial amount of work that has to be customised per client. However with further adoption of AI into new markets new clients may emerge.

Are they selling models or making introductions? As you say, niche models have small audiences which makes it all the more likely the models will require modifications. Discussing those modifications provides an opening to adjust the pricing.

How do you stop piracy on something like this?

Surely I could take a model, refine it slightly to get distinct weights (ie. not a flat clone) and unload it as my own novel variant?

...and I mean, is the problem not utterly fundamental?

When is a model “yours” or sell?

When you trained it? When you’re not using transfer learning? When you wrote the paper? When you own the training data? When you can recreate it from scratch?

I see this being problematic to look after...

The value of these could be in private datasets. Model architectures are not really patentable and ownership of a trained model has always been very muddy water.

That being said, if I am selling a bird classifier chances are that to train it I had to combine multiple datasets and someone can't easily finetune it to get better results.

They dont need to fine tune it for better results, they only need to fine tune it to give different results and sell it for $5 less than you are.

I believe it has a kind of pre-moderation.

I misunderstood your point.

The "attack" that you are describing could probably be mitigated by doing activation analysis. Given random initialization even with fine-tuning the activation distribution will be similar. Same method should be used to weed out people just repackaging the ImageNet pretrained model from torchvision.

That being said you can still distill a network into another with a teacher-student approach and that would be undetectable.

The marketplace should probably be on datasets.

I'd rather buy a model than a dataset that I have to spend money to train a model with.

You are limited in expanding your dataset and making your model better, if you only have the model. And I would rather see how clean/balanced the dataset my model was built from was.

When using models becomes more mainstream, I think it's better to strive for transparency than expandability.

Right, you could steal the model by querying lots of images and using teacher-student model distillation.

Disclaimer: I'm not very familiar with the current state of CV and the way models are trained.

What authors could do is train the model on a dataset, but add a specific image that it flags as a key.

That way, if you keep the image private, you can check if a model is a clone of yours if recognises that specific image.

Cool idea. I keep looking for a search/filter/facet function to leverage the tagging and classification they've done with the models, but I can't find one.

Thanks! This is definitely a feature we want to add in the future.

We also expored ways of presenting hundreds [1] of AI models in a better way. Recently we updated the model zoo so that it is arranged according to benchmark datasets [2] and papers [3]. Do you think it satisfies the needs?

[1] https://mmpose.readthedocs.io/en/latest/modelzoo.html [2] https://mmpose.readthedocs.io/en/latest/topics/body(2d,kpt,i... [3] https://mmpose.readthedocs.io/en/latest/papers/algorithms.ht...

Weird, the account registration wouldn't work on my normal IP, claiming 'too many requests'

Worked fine on a VPN however (sorry, I know you probably don't like this).

After the account registration though, I did quite like trying out a couple models out on a couple frames of footage to see if the models would "work".

Thanks for the report- it looks like we had our anti-spam set a little too sensitive. Glad you like the site!

Looks like https://modeldepot.io shut down, which was another model-as-a-service marketplace. You can check out https://paperswithcode.com/

A lot of these models are open source, I wonder who would this product market towards?

Can I ask where one can download the pretrained weights? Is there some online repository?

Some for YOLOv4 https://github.com/AllanYiin/YoloV4

You can look up the torchvision model zoo for pretrained weights of most popular architectures.

Tensorflow as an equivalent tool but I can't remember the name.

The models have to be trained. Trained towards a given task.

And then once you have the weights you have to figure out what to do with them. Data science (training a good model) and engineering (deploying it as a service to be consumed by end users) are pretty distinct tasks.

Good point.

Interesting concept. Would be great to have more technical details about how a model performs. Having a sense of the size, accuracy, platforms supported, and other simple benchmarks would be really helpful to evaluate a model before making a purchase.

This seems like an attempt to cash in and steal the branding behind the library, OpenCV. (I realise now it's the actual authors of the libary.. I've become too jaded here).

>>Did you really name your company OpenCV? As in.. Open Computer Vision, which you know is an incredibly well-known brand for a 20-year old library, likely fundamental to most the libraries you're now trying to commission for in your market?

This looks deliberate because the Chief Scientist & President, Gary Bradski[1], created the OpenCV library that you refer to.[2]

[1] https://www.oreilly.com/pub/au/3270

[2] https://www.opencv.ai/#About-us

Ah, well, that's fair. Egg on my face.

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